Journal of Mechanical Engineering no. 7-8 year 2022 volume 68 Strojniški vestnik – Journal of Mechanical Engineering (SV-JME) Aim and Scope The international journal publishes original and (mini)review articles covering the concepts of materials science, mechanics, kinematics, thermodynamics, energy and environment, mechatronics and robotics, fluid mechanics, tribology, cybernetics, industrial engineering and structural analysis. The journal follows new trends and progress proven practice in the mechanical engineering and also in the closely related sciences as are electrical, civil and process engineering, medicine, microbiology, ecology, agriculture, transport systems, aviation, and others, thus creating a unique forum for interdisciplinary or multidisciplinary dialogue. The international conferences selected papers are welcome for publishing as a special issue of SV-JME with invited co-editor(s). Editor in Chief Vincenc Butala University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Technical Editor Pika Škraba University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Founding Editor Bojan Kraut University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Editorial Office University of Ljubljana, Faculty of Mechanical Engineering SV-JME, Aškerceva 6, SI-1000 Ljubljana, Slovenia Phone: 386 (0)1 4771 137 Fax: 386 (0)1 2518 567 info@sv-jme.eu, http://www.sv-jme.eu Print: Demat d.o.o., printed in 250 copies Founders and Publishers University of Ljubljana, Faculty of Mechanical Engineering, Slovenia University of Maribor, Faculty of Mechanical Engineering, Slovenia Association of Mechanical Engineers of Slovenia Chamber of Commerce and Industry of Slovenia, Metal Processing Industry Association President of Publishing Council Mihael Sekavcnik University of Ljubljana, Faculty of Mechanical Engineering, Slovenia Vice-President of Publishing Council Bojan Dolšak University of Maribor, Faculty of Mechanical Engineering, Slovenia Image Courtesy: University of Ljubljana, Faculty of Mechanical Engineering, Chair of Materials, Science and Technology Laboratory for Welding, Slovenia Photo: Željko Stevanic, IFP, d.o.o. International Editorial Board Kamil Arslan, Karabuk University, Turkey Hafiz Muhammad Ali, King Fahd U. of Petroleum & Minerals, Saudi Arabia Josep M. Bergada, Politechnical University of Catalonia, Spain Anton Bergant, Litostroj Power, Slovenia Miha Boltežar, University of Ljubljana, Slovenia Filippo Cianetti, University of Perugia, Italy Janez Diaci, University of Ljubljana, Slovenia Anselmo Eduardo Diniz, State University of Campinas, Brazil Igor Emri, University of Ljubljana, Slovenia Imre Felde, Obuda University, Faculty of Informatics, Hungary Imre Horvath, Delft University of Technology, The Netherlands Aleš Hribernik, University of Maribor, Slovenia Soichi Ibaraki, Kyoto University, Department of Micro Eng., Japan Julius Kaplunov, Brunel University, West London, UK Iyas Khader, Fraunhofer Institute for Mechanics of Materials, Germany Jernej Klemenc, University of Ljubljana, Slovenia Milan Kljajin, J.J. Strossmayer University of Osijek, Croatia Peter Krajnik, Chalmers University of Technology, Sweden Janez Kušar, University of Ljubljana, Slovenia Gorazd Lojen, University of Maribor, Slovenia Darko Lovrec, University of Maribor, Slovenia Thomas Lübben, University of Bremen, Germany George K. Nikas, KADMOS Engineering, UK Tomaž Pepelnjak, University of Ljubljana, Slovenia Vladimir Popovic, University of Belgrade, Serbia Franci Pušavec, University of Ljubljana, Slovenia Mohammad Reza Safaei, Florida International University, USA Marco Sortino, University of Udine, Italy Branko Vasic, University of Belgrade, Serbia Arkady Voloshin, Lehigh University, Bethlehem, USA General information Strojniški vestnik – Journal of Mechanical Engineering is published in 11 issues per year (July and August is a double issue). 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Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8 Contents Contents Strojniški vestnik - Journal of Mechanical Engineering volume 68, (2022), number 7-8 L jubljana, July-August 2022 ISSN 0039-2480 Published monthly Papers O guz Dogan: Short-term Creep Behaviour of Different Polymers Used in Additive Manufacturing under Different Thermal and Loading Conditions 451 R agul Kumar Kittusamy, Velavan R ajagopal, Paul G regory Felix: Preparation and Thermal Characteriz ation of N anographene-Enhanced Fatty Acid-Based Solid-Liquid O rganic Phase Change Material Composites for Thermal Energy Storage 461 Prabhakaran Jayasankar, Jayabal Subbaian: O ptimiz ation of in-Vehicle Carbon Dioxide Level in a 5-Seat Car 471 Davood Afshari, Ali G haffari, Z uheir Barsum: O ptimiz ation in the R esistant Spot-Welding Process of AZ 61 Magnesium Alloy 485 Marzena M. Lachoicz, Tadeusz Lenieski, Maciej B. Lachoicz: Effect of Dual-stage Ageing and R R A Treatment on the Three-body Abrasive Wear of the AW7075 Alloy 493 Marek Binienda, Robert Pietrasik, Sylester Pata, Krzysztof Matczak, itold Kroteicz: Nitriding HS6-5 -2 Steel in I nductively Coupled Plasma 506 Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, 451-460 Received for review: 2022-05-08 © 2022 The Authors. CC BY 4.0 Int. Licensee: SV-JME Received revised form: 2022-06-22 DOI:10.5545/sv-jme.2022.191 Original Scientific Paper Accepted for publication: 2022-08-05 Short-term Creep Behaviour of D ifferent Polym ers U sed in Additive Manufacturing under D ifferent Thermal and L oading Conditions * O guz Dogan Kahramanmaras Sutcu I mam University, Department of Mechanical Engineering, Turkey Polymer materials produced by additive manufacturing undergo significant changes in their dimensions under continuous loading conditions. This situation affects the operation of polymer structures produced by additive manufacturing within safe limits. Therefore, it is crucial to determine the creep behaviour of polymers produced by the additive manufacturing method. This study investigates the creep behaviour of six different materials, acrylonitrile butadiene styrene (ABS), chlorinated polyethylene (CPE), polylactic acid (PLA), tough polylactic acid (TPLA), polycarbonates (PC), and nylon most commonly used in additive manufacturing. The creep test specimens are firstly produced with a three-dimensional (3D) printer, and then their final dimensions are given using computer numerical control (CNC) milling. The creep experiments are carried out at three different ambient temperatures (25 °C, 40 °C, and 60 °C) and two different stress levels (10 MPa, 20 MPa). According to the test results, it was determined that the material type, temperature, and loading levels significantly influenced the creep behaviour of the 3D printed polymer materials. Keywords: Additive manufacturing, creep experiments, polymer materials, thermal effect Highlights • Creep test specimens are produced with a 3D printer and CNC milling. • Creep tests are performed for different temperatures and loading conditions. • Short-term creep behaviours of polymers are investigated experimentally. • Material type, heat, and loading significantly affected the creep behaviour of the polymer materials. 0 INTRODUCTION Fused deposition modelling (FDM) is a production method that allows parts to be processed layer by layer and produced as one piece. As a basic principle, in FDM, the raw material is heated, fluidiz ed, and passed through a noz z le to produce the part in layers. With this production technique, products that cannot be produced in one step with traditional production methods have become easily produced. The FDM technique has started to increase its importance in practical life day by day with the increase and cheapening of three-dimensional (3D ) printers. The advantages of FDM are summariz ed by N go et al. [1] as design freedom, customiz ation, waste minimiz ation, and the ability to produce complex structures. The FDM method allows many different polymer materials to be used in 3D production. PLA, TPLA, ABS, PC, nylon, and CPE are the most commonly used polymer materials in the studies carried out with the FDM method in the literature. PLA is the most commonly used biopolymer and thermoplastic produced from corn starch and sugar cane in 3D printing. PLA enables fast and reliable 3D production with high surface quality [2]. ABS is also commonly used in 3D printing; it is tough and durable, provides high dimensional stability, and is resistant to physical impacts and chemical corrosion [3]. PC is a thermoplastic with a wide range of uses in the modern manufacturing industry; it can be defined as strong, temperature resistant, and tough. PC provides high mechanical strength, ultimate printing quality, and thermal resistance up to 1 10 C [4]. N ylon is well known for good elongation, abrasion resistance, high strength-to-weight ratio, and low friction coefficient but a much lower strength [5]. Compared to other materials, the use of CPE with FDM is limited. CPE is defined as chemically resistant and tough [6]. The determination of the mechanical properties of the products produced using the FDM method has attracted great interest with the widespread use of FDM technology. Thus, many researchers have carried out extensive studies on the determination of the mechanical properties of the products produced by FDM. I n these studies, generally, the tensile [7], bending [8], and impact [9] strengths of materials produced by the FDM method are experimentally investigated. While the mechanical properties of different materials have been investigated [10], the effects of FDM process parameters on mechanical properties have also been studied [11]. I n addition, the fatigue strength of the materials produced with 3D printers has been experimentally investigated [12]. Creep is the permanent deformation that occurs over time in materials under the influence of a constant temperature, stress, or loading. The creep behaviour of polymer materials is significant in industrial applications where dimensional stability is essential. For this reason, the creep behaviour of polymer materials should be determined, and the designs should be carried out accordingly. Many studies examine the creep behaviour of different polymer materials in the literature. G enerally, the researchers are focused on the effects of the printing process parameters on the creep behaviour of the 3D printed materials. Z hang et al. [13] investigated the tensile, creep, and fatigue behaviour of the 3D printed ABS samples. The effects of the printing orientation on the creep properties of the ABS test samples were defined experimentally. The effect of printing orientation on short-term creep behaviour of the 3D printed PLA samples is investigated in another comprehensive study [14]. I n addition, the effects of layer thickness and different PLA types on creep are investigated experimentally. Mohammed et al. [15] investigated the flexural creep stiffness behaviour of PC-ABS material produced with FDM. I n another study, the authors experimentally investigated the effects of process parameters on the creep and recovery behaviours of samples produced using the FDM method [16]. The creep and recovery behaviour of the reinforced 3D composites are investigated by Al Rashid and Ko [17]. Waseem et al. define the most effective process parameters on the tensile creep behaviour of the 3D printed PLA parts. They proposed the optimal combination of the process parameters using categorical response surface methodology [18]. Some researchers have experimentally investigated the effects of environment variables on creep. Temperature-humidity [19] and creep load [20] are considered variable parameters when these studies are examined. Various models have been used to predict creep in some studies. Lim et al. [21] developed a long-term creep model using the short-term creep test results for PC and ABS. Ye et al. [22] proposed a modified Burger model to predict the creep behaviour of the 3D printed test samples. The proposed model is validated with the creep experiments. As a result of the study, the modified model can accurately calculate the creep behaviour of the PLA-max samples with different printing angles. According to the literature review, it is seen that the effect of process parameters on the creep behaviour of materials produced by the FDM method has been generally investigated. N o study has been found that investigated the creep behaviour of different materials produced by the FDM method. I n addition, temperature is one of the most influential parameters on the creep behaviour of the polymer materials. Similarly, when the literature is examined, the studies examining the effects on the creep behaviour of the samples produced with FDM temperature are very limited. These shortcomings in the literature have been the biggest motivation for this study. The present investigates the creep behaviour of six different polymer materials (ABS, CPE, PLA, TPLA PC, nylon) produced by the FDM method. I n addition, experiments are carried out for each material type at three different temperatures (room temperature, 40 C, and 60 C) and two different stress levels (1 0 MPa and 20 MPa). The effect of temperature and stress on the creep behaviour of materials produced by the FDM method has been explained. 1 MATERIAL METHOD 2.1 Production of Creep Test Specimens I n this study, the creep behaviour of the different polymer materials produced with a 3D printer was experimentally investigated. The polymer test specimens were produced by combining FDM and CN C milling operations. The creep test specimens were produced with the Ultimaker 2+ Extended 3D printer. The printing area is 230 mm 230 mm 305 mm, and the resolution is 12.5 m – 12.5 m – 5 m for the x – y – axes, respectively. The dimensions of the creep test specimens were determined according to ASTM D638 Type I V [23]. The computer-aided design (CAD) data of the test specimens were created in Solidworks software. The designed data were converted into the stl file format and sent to the Ultimaker Cura (version 4.13.1) software to define the 3D printing parameters. The G – codes of the test specimens were created in Ultimaker Cura software. The manufacturing parameters of the test specimens determined in Ultimaker Cure are given in Table 1. The creep test specimens were produced with the Ultimaker brand filaments with a diameter of 2.75 mm. The 3D printing parameters of the test samples were defined according to the manufacturer’ s technical data sheets [24] to [29]. The test samples were produced with the same G – codes and one by one in the middle of the printing table in order to produce the test samples as similar as possible. Each specimen was produced three times for the repeatable experiments. When the samples are produced in a 3D printer, the notch effect and different wall pattern geometries Table 1. 3D printing parameters of the test samples Material Extrusion temperature [°C] Table temperature [°C] Printing speed [mms-1] Nozzle diameter [mm] Layer thickness [mm] Infill density [%] Infill pattern PLA [24] (Pearl-White) 200 60 60 ABS [25] (Yellow) 230 80 55 Nylon [26] (Black) PC [27] (Transparent) 245 270 60 110 45 45 0.4 0.2 200 Lines CPE [28] (Yellow) 240 85 45 TPLA [29] (Black) 205 60 60 occur on the test samples. To eliminate this problem, the creep test samples were subjected to CN C milling after the 3D printing process, minimiz ing the notch effect and possible siz e and dimensional defects. The CN C milling process was completed in two steps. First, holes were drilled to connect the specimens to the creep test device. Then, 2 mm from the outer region of the creep test specimen was machined to achieve a homogeneous structure. To carry out these operations, two special drilling and milling dies were designed and produced. The produced special drilling and milling dies are seen in Fig. 1a . Creep test specimens produced with a 3D printer for CN C milling were produced in siz es 2 mm larger than the dimensions specified in ASTM D6 38 Type I V. After the CN C milling process, the samples were brought to the dimensions in ASTM D638 Type I V (Fig. 1b) . Four flutes milling cutter, with 6 mm diameter, were used in both drilling and milling operations. The cutting direction is defined as climb. The spindle speed is selected at 3500 rpm, and the x -, y-axis speeds are defined as 500 m m/min. 2.2 Creep Tests The primary purpose of this study is to determine the creep behaviour of different polymer materials produced in 3D printers with the FDM method under different temperatures and loads. Various creep tests have been carried out to achieve this aim. The experiments were performed on the standard creep test device shown in Fig. 2. As seen in the figure, two measurement devices on the creep test device measure the temperature and the amount of test sample elongation. An Etopoo brand electronic micrometer was used to measure the time-dependent creep deformations of the test samples. The micrometer can measure between 0 mm to 12.7 mm with an accuracy of 1 m. The temperature of the test area was measured instantaneously with the PT10 0 temperature sensor. This sensor can measure the temperature between –50 C and 250 C with an accuracy of 0.1 C. The temperature and elongation data collected over the temperature sensor and micrometer are sent to the PLC module on the creep tester. The data on the PLC module is instantly transferred to the computer environment. The data transmitted to the computer environment can be obtained in Excel format with the software of the creep test device. Creep tests were carried out as specified in the ASTM D2990-17 [30] standard. Moreover, the creep tests were performed in a climate-controlled room and on a vibration-insulated table. The creep tests were performed for three different temperatures (25 C, 40 C, and 60 C) and two various stress levels (10 MPa and 20 MPa). The temperature is set to the Fig. 1. Production of creep test specimens; a) produced drilling and milling dies, and b) machining stages Fig. 2. General view of the creep test device and detailed view of the test region desired level in the creep tests, and the heater starts to heat the test area. When the ambient temperature reaches the desired temperature, the heater turns off. I f the ambient temperature drops 1 degree below the desired temperature, the heater works again and brings the environment to the desired level. I n this way, the ambient temperature is controlled with minimal fluctuations. Creep tests are started when the test z one temperature reaches equilibrium at the desired temperature. Experiments begin by lowering the protective latch, and temperature and elongation data are instantaneously collected and recorded from the computer environment. Each creep test was carried out for 3 hours (10800 s); during this time, the creep elongation was measured and recorded with a micrometer. 2 RESULTS AND DISCUSSIONS This study performed creep tests for six different materials (ABS, PLA, TPLA, CPE, PC, and nylon) under three different temperatures and two different loading conditions. Each experiment was repeated until three successful results were obtained. The amount of elongation obtained depending on time has been interpreted by presenting different graphs. R esult graphs were created by considering the test result closest to the mean for each material, temperature, and loading condition. Short-term creep behaviours (primary and secondary creep phases) of different materials are investigated in this study. Tertiary creep behaviour is also seen under specific ambient temperature and stress levels in some cases. However, this study is mainly interested in the short-term creep behaviour of different polymers. The creep test results for ABS material for different ambient temperatures and stress levels are seen in Fig. 3. The creep characteristic’ s first and second stages can be seen for all tests except the 60 C and 20 MPa case. The ABS sample ruptured quickly in approximately 3 min at 60 C temperature and 20 MPa stress conditions. The first stage creep region extends over a longer period with the increase in temperature. I n the first creep stage, the sample elongates due to the Fig. 3. Creep test results of ABS under different ambient temperatures for; a) 10 MPa, and b) 20 MPa stress levels Fig. 4. Creep test results of PLA and TPLA under different ambient temperatures and stress levels; a) 10 MPa PLA, b) 20 MPa PLA, c) 10 MPa TPLA, and d) 20 MPa TPLA (left column normal, right column zoomed views) effect of the load, where the dislocation movements are pretty large. As the temperature increases, the first stage creep z one expands because the ability to move on dislocations in the material increases. The creep resistance of the ABS material decreases with the increase in the ambient temperature and stress levels. Fig. 4 indicates the creep test results for PLA and TPLA for different ambient temperatures and stress levels. As the figures are unclear at high temperatures and loads, a z oomed-in view of each figure is shown in the right column of the Fig. 4. The creep samples produced from PLA are exposed to much more creep under the same test conditions than the samples produced from ABS. I t is determined that the increase in temperature and applied load reduces the creep strength of the samples produced from PLA more than ABS samples. I n addition, it has been tested that the sample breaks after a while in the case of 60 C and Fig. 5. Creep test results of CPE under different ambient temperatures for; a) 10 MPa, and b) 20 MPa stress levels Fig. 6. Creep test results of PC under different ambient temperatures for; a) 10 MPa, and b) 20 MPa stress levels Fig. 7. Creep test results of nylon under different ambient temperatures for; a) 10 MPa, and b) 20 MPa stress levels 10 MPa. However, the time to rupture is much longer than the 60 C – 20 MPa case. According to the test results, although PLA is the most commonly used polymer in additive manufacturing, its creep strength is quite low. I t can be said that both temperature and load significantly reduce the creep strength; therefore, parts made of PLA material are suitable for use at room temperature and very low constant loads. Similar to ABS and PLA materials, the creep increases in creep test specimens produced from TPLA with the increase in ambient temperature and load. When the total creep values are examined, the samples produced from TPLA showed less creep than PLA but more than ABS. The creep test samples were damaged quickly under both loading conditions at 60 C. In short, the TPLA material has better creep strength than PLA and worse strength than ABS. Fig. 5 illustrates the creep test results of CPE test samples under different ambient temperatures and stress levels. Similar to other materials, the creep rate of the CPE increases with the increase in the ambient temperature and stress levels. However, the creep resistance of the CPE materials is better than ABS, PLA, and TPLA. The CPE creep test samples break after a short amount of time in the case of 60 C and 20 MPa test conditions. This time is much longer compared to PLA, ABS, and TPLA samples. This shows that the creep strength of CPE samples is higher than PLA, ABS, and TPLA. The creep test results of PC test samples for different ambient temperature and loading conditions are illustrated in Fig. 6. According to the results obtained from the creep tests, it has been determined that the creep strength of PC material is very high compared to all other materials. I n addition, the test samples produced from PC are the least affected by temperature and loading conditions. N o damage occurred in the samples produced from PC material under this study’ s applied loading and temperature conditions. For this reason, PC materials should be used in parts that will operate under high temperature and high constant static loading conditions since creep is very low. The creep test results for the nylon samples are seen in Fig. 7. The first and second creep stages are clearly seen for the nylon test specimens. Because, the maximum creep values are seen for the nylon test samples. The flexibility of the nylon is much higher than the other materials. However, no damage is seen for this material, even in the case of 6 0 C and 20 MPa test conditions. The experiment was terminated because it went out of the measuring range of the micrometer. Parts produced from nylon with a 3D printer should be used in low loading and temperature conditions where flexibility is at the forefront. The comparison of the creep test results of the five different materials under 10 MPa stress levels and different ambient temperatures is shown in Fig. 8 . The first and second stage of the creep is seen clearly from the figures; also, the tertiary (accelerated) creep phase is seen only in PLA and TPLA under 60 C and 10 MPa test conditions. During the first stage of creep, the elongation rate is high. However, due to the strain hardening, the elongation rate slows down over time and reaches the lowest level, and remains constant. During the second stage of creep, the elongation increases approximately linearly with time. After the second stage creep z one, the elongation increases rapidly, and the specimens break. This region is called the creep region. The tertiary stage of creep is only seen for PLA and TPLA. Fig. 9 shows the creep behaviour of samples produced from five different materials under 20 MPa loading and different temperatures. N o rupture was observed in the experiments carried out at 25 and 40 C ambient temperatures. However, in the experiments carried out at an ambient temperature of 60 C, all other materials, except PC material, break quickly after a certain period of time. The amount of creep increases with the increase of the stress value from 10 MPa to 20 MPa. This increase in the amount of creep increases more with increasing temperature. Similar results are found in [14] to [20]. I n addition, the increase in the maximum creep value increases with the increase in the stress level. Therefore, it cannot be said that there is a direct linear relationship between stress level and creep. 3 CONCLUSIONS I n this study, the creep behaviour of test specimens produced from six different materials (PLA, ABS, TPLA, CPE, nylon, PC) by the additive manufacturing method was investigated experimentally under three different temperatures (25 C, 40 C, and 60 C) and two different stress values (10 MPa, and 20 MPa). The creep test samples are produced by using Ultimaker 2+ Extended 3D printer and CN C milling to obtain a homogeneous structure. Creep experiments were carried out for three hours. The results of the creep tests performed in this study can be summariz ed as follows. The creep rate increases ith the increase in ambient temperature and stress level for all materials used in this study. According to the test results, the load is a more effective parameter on creep than the temperature. PLA, hich is the most commonly used polymer in 3D printers, is determined as the material with the worst creep resistance. For this reason, it is recommended that the parts produced using PLA with a 3D printer should be used at room temperature with no load or under very low static loads. Although TPLA has slightly better creep behaviour than PLA, it is not suitable for high temperatures and loads. According to the results obtained from ABS and CPE samples, these materials can be used at medium loads and moderate temperatures, but they are not suitable for use at high loads and temperatures. Although more creep occurred in the test specimens made of nylon compared to other materials, no rupture was observed. PC is determined to be the most resistant material against creep. The lowest creep amounts are observed in PC material in all experimental scenarios. Therefore, PC material can be used more safely than other materials under high load and temperature conditions. After this study, the creep behaviour of polymer materials produced with 3D printers can be better understood by examining the effect of 3D printer production parameters (printing angle, noz z le diameter, layer thickness, extrusion temperature, printing speed, etc.) on creep under different temperature and loading conditions. 4 ACKNOWLEDGEMENTS This work has been partially supported by the Scientific R esearch Projects Coordination Unit of the R ectorate of Kahramanmaras Sutcu I mam University with the project number 2020/7-17M . 5 REFERENCES [1] Ngo, T.D., Kashani, A., Imbalzano, G., Nguyen, K.T.Q., Hui, D. (2018). Additive manufacturing (3D printing): A review of materials, methods, applications and challenges. 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Licensee: SV-JME Received revised form: 2022-06-13 DOI:10.5545/sv-jme.2022.148 Original Scientific Paper Accepted for publication: 2022-06-16 Preparation and Thermal Characteriz ation of Nanographene-Enhanced Fatty A cid-Based Solid-L iq uid O rganic Phase Change Material Composites for Thermal Energy S torage * R agul Kumar Kittusamy – Velavan R ajagopal – P aul G regory Felix PSG College of Technology, Department of Mechanical Engineering, I ndia In this research work, nano-phase change material (NPCM) composites were prepared by adding 1 %, 2 %, and 3 % mass fractions of highly conductive carbon-based graphene nanoparticles into the base phase change material (PCM). The existence and uniform graphene dispersion in the PCM was confirmed through Raman spectrometer and scanning electron microscope (SEM) analysis. The Fourier transform infrared (FTIR) and x-Ray diffraction (XRD) results showed that all three NPCM composites were chemically stable, and their crystallinity was similar to the base PCM. For the sample with 3 % graphene, the solid-state thermal conductivity was increased by 219.89 %, and liquid-state thermal conductivity was increased by 161.65 %, with a 3.52 % drop in latent heat capacity was revealed from differential scanning calorimetry (DSC) analysis. All NPCM composites have onset and peak melting temperatures closer to the base PCM. Hence, the NPCM composites can be employed for thermal energy storage (TES) integrated solar water heater (SWH) applications. Keywords: phase change material, graphene nanoparticles, nano-phase change material composite, thermal energy storage, solar water heater Highlights • Highly conductive nanographene was dispersed into the fatty acid-based PCM. • The prepared NPCM composites were thermally and chemically stable. • For 3 wt.% graphene in PCM, the solid-state thermal conductivity was improved by 219 %. • The DSC result shows a 3.52 % decline in latent heat capacity for NPCM 3 composite. • All NPCM composites have closer onset and peak melting temperatures with base PCM. 0 INTRODUCTION Solar energy is an essential sustainable resource since it is available in abundance. Considering the absorption and scattering losses, the total solar flux reaching the earth’ s surface is about 1.08 G W. Hence, the earth’ s surface receives 3.4 10 24 J of total energy annually, roughly around 7500 times the annual world primary energy use [1]. As a tropical country, I ndia receives about 5000 trillion kWh of solar radiation annually, resulting in a daily average solar irradiance of 4 kWh/m to 7 kWh/m . Currently, the residential sector contributes roughly about 84 % of I ndia’ s total solar water heater (SWH) installations. Solar water heating is a recogniz ed technology for cleaner hot water production from solar energy. A 100-litre SWH system can prevent up to 1.5 tonnes of CO 2 emissions each year [2]. However, the insolation of solar radiation at any point on the earth’ s surface is diurnal. I t depends on several factors, such as weather conditions, length of the day, latitude, and season at that particular surface [3]. Therefore, it requires a technology that stores the heat energy received from the sun during sunshine hours and uses it for off-shine hours. Thermal energy storage (TES) technology is an attractive option for storing solar energy effectively to reduce the mismatch between energy supply and demand [4]. I ntegrating phase change material (PCM) based latent heat thermal energy storage (LHTES) in SWH is an environment-friendly solution for passively obtaining additional hot water with the same system capacity. Using PCMs in TES systems has proliferated and received tremendous attention worldwide [5] and [6]. G enerally, PCMs, including organic, inorganic, and organic-inorganic categories, exhibit good potential for storing energy in the form of sensible and latent heat. The PCM-based LHTES can absorb and release substantial energy during the phase transition process at near isothermal working conditions [7]. Domestic solar water heating falls under low and medium-temperature applications with an operating temperature of around 65 C [8]. Among the PCMs, paraffin wax was widely used for TES in SWHs, typically having a melting temperature range between 50 C to 60 C, a latent heat capacity of 200 kJ/kg, and a solid-state thermal conductivity of 0.172 W/(m K) [9] to [11]. With paraffin as an energy storage medium for TES in SWHs, the maximum water temperature obtained from SWHs has been limited to 60 C, despite the heat energy supplied to TES being at an elevated temperature. This temperature limitation is due to the heat energy stored in paraffin PCM beyond 60 C is in the form of sensible heat, which is inferior to the latent heat stored at 60 C. Using appropriate PCM with melting temperatures close to the operating temperature of SWH is necessary to obtain hot water at the desired temperature. I t has been identified that the proper selection of PCM melting temperature plays a crucial role in the performance of TES systems [12]. This constitutes a research gap that could be bridged by utiliz ing alternative PCMs to paraffin, possessing a higher melting temperature than 60 C. The eutectic mixture of fatty acids offers a more comprehensive range of engineering applications because of its greater heat storage reliability [13]. Therefore, some recent studies on the synthesis and characteriz ation of fatty acids and their eutectic mixtures reported that the fatty acid-based PCMs are a potential candidate for TES applications [14] and [15]. The fatty acid-based PCMs fall under the organic category, and they have attracted broad attention in the field of TES applications. Compared to individual fatty acid PCMs, the eutectic combinations of organic fatty acids significantly impact the phase change temperature. Any desired phase transition temperature for the TES application could be obtained by proper mixing of two or more PCMs, forming a eutectic mixture of fatty acids. For the eutectic mixture, the melting temperature of the selected PCMs should be around the desired operating temperature range such that each component in the mixture melts and solidifies simultaneously [16]. I n contrast, the thermal conductivity of widely used contemporary PCMs in LHTES systems is relatively low, typically ranging from 0.5 W/ (m K) to 1 W/(m K), which prolongs the melting and solidification process of the PCM used in TES applications. This phenomenon seriously affects the overall efficiency of the TES system. Therefore, it is necessary to address this issue with potential heat transfer enhancement techniques [17]. The inclusion of smaller mass fractions of highly conductive metallic or carbon-based nanoparticles in a PCM significantly improves the effective thermal conductivity of PCM, leading to accelerated charging and discharging rates of PCM [18]. The nanoparticles have a greater surface-area-to-volume ratio. By increasing the mass concentration of nanoparticles in the base PCM, the thermal conductivity of PCM could be improved with a decrease in the latent heat of the PCM. Hence, the mass/volume fraction of nanoparticles added to the PCM is optimiz ed to obtain the lowest possible reduction in latent heat capacity [19]. For the previous two decades, the heat transfer enhancement in PCM-based TES applications by employing metal-based nanoparticles has been the subject of extensive research. Many researchers are currently focusing on carbon-based nano-additives (multi-wall carbon nanotubes, graphene nanoparticles, and nano-graphite) to enhance the effective thermal conductivity of PCM [20]. For the same mass fraction, metal-based nanoparticles have a higher mass-to-volume ratio when compared to carbon-based nanoparticles. Hence, this could reduce the effect of nanoparticles in PCM due to the aggregation and sinking of metal particles inside the liquid phase-change medium [21]. The use of graphene nanoparticles in energy storage and thermal management applications has been put in practice, and it outmatches metal nanoparticles, carbon-based nanotubes, and other carbon allotropes [22]. I t has been proved that adding nanographene to PCM improves its thermal conductivity and, at the same time, increases the viscosity of PCM, leading to the degradation of the effect of natural convection in its liquid state. As a result, compared to pure PCM, the temperature rise rate of nano-graphene-based PCM composites was more significant during the initial stage and lowered during later stages of the charging process [23]. The higher the mass fraction of graphene in PCM, the higher the viscosity of the liquid nano-phase change material (N PCM) composite. Hence, this was a limiting factor for adding higher mass concentrations of graphene in PCM to retain the liquid state temperature rise rate of N PCM composites [24]. This study addresses the aforementioned research gaps by using a new eutectic fatty acid-based solid-liquid organic PCM and graphene nanoparticles as a thermal conductivity booster. The PCM used in this study is selected based on its melting temperature by considering the operating temperature of the domestic SWH. The main objective of this research work is to prepare and characteriz e the thermal properties of the N PCM composites, considering their applicability for TES integrated domestic SWHs. The appropriate use of the prepared N PCM composites and the design of the LHTES system for practical applications requires basic knowledge about the material characteristics. 1 METHODS The research strategy followed in this work consists of three modules: material selection, preparation of N PCM composites, and characteriz ation of the samples. 1.1 Material Selection The base PCM, O M65, which is a mixture of organic fatty acids, was purchased from Pluss Advanced Technologies Pvt. Ltd., Haryana, I ndia. PCM selection was made by considering the applicability to LHTES for domestic SWHs. At room temperature, the PCM appeared to be a white flake solid. The highly conductive graphene nanoparticles were purchased from Ultrananotech Pvt. Ltd., Bangalore, I ndia. The physical appearance of graphene was that of a light black fluffy powder. All the materials were used exactly as they were procured, with no further modifications. The suppliers’ properties of PCM and nanographene are listed in Table 1. 1.2 Preparation of NPCM Composites The N PCM composites were prepared using a two-step mechanical dispersion method [25] and [26], as illustrated in Fig. 1. The PCM was heated up to 80 C (above its melting temperature), and the liquid PCM was stirred at 600 rpm using a hot plate magnetic stirrer. The graphene nanoparticles were then added to the liquid PCM in mass fractions of 1 wt.% , 2 wt.% , and 3 wt.% and stirred continuously for 1 hour to obtain N PCM 1, N PCM 2, and N PCM 3 samples, respectively. Table 1. Properties of PCM and graphene nanoparticles PCM (OM65) Graphene Melting temperature [°C] 65 Purity [%] > 99 Solid specific heat, 30 °C [kJ/(kg·K)] 2.83 Particle diameter [nm] 5 to 10 Latent heat [kJ/kg] 204 Length [”m] 5 to 10 Solid density, 30 °C [kg/m3] 924 Density [g/cmł] 3.1 Solid thermal conductivity @ 30 °C [W/(m·K)] 0.18 Surface area [mČ/g] 200 to 210 Liquid thermal conductivity @ 70 °C [W/(m·K)] 0.13 Thermal conductivity [W/(m·K)] 3000 The graphene concentration in PCM was limited to 3 wt.% by considering a minimum reduction in latent heat capacity of the N PCM composite [27]. The macro-level dispersion of nanoparticles in PCM with some agglomerated particles was obtained by shear mixing using magnetic stirring. The liquid N PCM was subjected to ultrasonication for 1 hour by maintaining water bath temperature at 8 0 C and sonication frequency at 40 kHz [28]. The dispersion quality was improved by ultrasonication, thus by untangling the agglomerated graphene nanoparticles, which are collapsed by microbubbles inside the liquid medium, forming a homogeneous composite. The homogeneously dispersed liquid N PCM samples were then allowed to solidify entirely at room temperature before being collected for characteriz ation. After complete solidification, the samples are turned into cake-like composites, subsequently ground into powder for characteriz ation by using a polished granite mortar and pestle. Fig. 1. Schematic of NPCM composite preparation by the two-step method 1.3 Characterization of the Samples The presence of graphene in the prepared samples was identified using a WI Tec alpha 300 R aman spectrometer with a 532 nm argon green laser source. A scanning electron microscope (SEM) (Z EI SS EVO 18, USA) with 10 kV accelerated voltage was used to examine the dispersion of graphene in PCM and the microstructures of all the prepared samples at a working distance of 10 mm. The chemical interaction between graphene nanoparticles and PCM was investigated using a Shimadz u I R Affinity 1 s model Fourier transform infrared spectrometer (FTI R ) with a wavenumber range from 4000 cm-1 to 400 cm-1 and a resolution of 0.5 cm-1 . The Empyrean, Malvern Panalytical multipurpose X -ray diffractometer (X R D) ith Cu K ( 1.54 ) as an -Ray source as used to study the crystal structures of PCM and N PCM 3 in the range of 0 2. 80 at a scanning rate of 6 s-1 . Thermal conductivities of PCM and N PCM composites were measured at solid state and liquid state using a TEMPO S thermal analyser (METER G roup). The energy storage properties, such as melting temperature, latent heat capacity, and thermal decomposition temperature of PCM and N PCM composites were characteriz ed using a N ETZ SCH STA 2500 R egulus analyser, a simultaneous differential scanning calorimetry-thermogravimetry analysis (DSC-TG A) instrument by heating the samples from 30 C to 200 C in an alumina crucible, and in an N 2 environment at a 10 C/min heat ramp. 2 RESULTS AND DISCUSSION 2.1 SEM Analysis The dispersion quality and microstructure of the prepared samples were examined through SEM. I t can be seen from Fig. 2a that the graphene nanoparticles have rough flake-shaped multiple layered structures with wrinkles and wrapped edges. This characteristic feature indicates the presence of small random porous structures in graphene that can hold a small quantity of PCM in it. I n comparison with the same mass concentration of metal nanoparticles, the carbon-based graphene with random void structures accommodates a smaller volume of liquid PCM, resulting in a minimum reduction in the latent heat capacity of the TES system. The typical graphene nanoparticle width as approximately 6.5 m, indicating the graphene nanoparticles’ larger aspect ratio. Fig. 2b to d shows the microstructures of N PCM 1, N PCM 2, and N PCM 3 composites comprising 1 wt.% , 2 wt.% , and 3 wt.% of the porous structured graphene nanoparticles in the base PCM. The solidified N PCM composites morphologies appear rougher, and uniformly distributed graphene in the base PCM was identified. More numerous rough protuberances were observed on the samples as the nanoparticle concentration increased, ensuring the graphene’ s strong embedment in crystal PCM, and establishing effective heat conduction paths within the N PCM composites [29]. 2.2 Raman Spectra Analysis A R aman spectrometer is commonly used to characteriz e carbon compounds because the strong R aman intensities were observed for conjugated carbon and carbon-carbon complexes [30]. The presence of graphene in all the N PCM composites was a) c) Fig. 2. SEM images of: a) graphene, b) NPCM 1, c) NPCM 2 and, d) NPCM 3 analysed using a R aman spectrometer, as illustrated in Fig. 3 . The graphene nanoparticle shows two strong peaks: a D peak at 1357 cm-1 and a G peak at 1594 cm-1 . The D band corresponds to the sp hybrid carbon atoms, the defect band whose intensity is directly related to the defect in the sample. A weak D band peak was seen for the graphene employed in this study, indicating that the graphene quality was acceptable. The G band is sharp, and the band is an in-plane vibrational mode involving the sp hybridiz ed carbon atoms contained in the graphene sheets [31]. The R aman spectrum of all three N PCM composites comprised D peak and G peak at its corresponding wavelength, as shown in Fig. 3 . Thus, the presence of graphene in all NPCM composites as confirmed. The inclusion of graphene into the base PCM resulted in modifications in some spectral peaks of PCM and the formation of new characteristics in the spectra, implying that only the vibrational modes were modified due to the attachment of the graphene flakes in the chains of fatty acid PCM [32]. Fig. 3. Raman spectra of graphene, PCM, and NPCM composites 2.3 FTIR Analysis The chemical characteristics of the fatty acid PCM, graphene nanoparticles, and N PCM composites are portrayed in Fig. 4. The peaks near 2920 cm-1 and 2850 cm-1 wavelengths indicate the stretching vibrations of the symmetric –C H3 and –C H2– groups of long-chain fatty acids. The absorption band of aliphatic C–H stretching vibration generally overlaps with the absorption band of O –H stretching vibration between the wavelength 3000 cm-1 and 2750 cm-1 . The peak at 1700 cm-1 represents the stretching vibrations of –CO. The peak at 1470 cm-1 represents the – CH2 and the peak at 1300 cm-1 represents the C–H and C–C groups bending peak. I t was observed that the characteristic peaks of the PCM and the N PCM composites were similar, indicating that the chemical structures of the PCM remain unchanged upon blending it with graphene nanoparticles. Therefore, all the prepared N PCM composites were in a chemically stable form. Fig. 4. FTIR spectra of Graphene, PCM, and NPCM composites 2.4 XRD Analysis The PCM and N PCM 3 composite phase structure was characteriz ed by X R D analysis. As illustrated in Fig. 5, the diffraction pattern of PCM includes two strong peaks at 21.54 and 24.12 , corresponding to the diffraction of (1 10) and (021) crystal planes of the fatty acid mixtures. Also, the X R D result of PCM shows a few weak diffraction peaks, such as the peak at 1 1.1 and 20.45 , as a result of the diffraction of (005) and (–1 1 1) crystal planes of PCM, respectively. I t can be seen that the X R D pattern of the N PCM 3 composite is similar to the PCM diffraction pattern, revealing that the graphene insertion does not affect the crystal structure of the base PCM. Therefore, it was clear that the graphene-enhanced PCM composites are a mere physical mixture of PCM and graphene, and their crystal structures remained unaltered. From the above X R D results of the sample having 3 wt.% graphene (N PCM 3) , it was inferred that the untested samples having 1 wt.% and 2 wt.% graphene in PCM (N PCM 1 & N PCM 2) are also a physical mixture of the PCM and the graphene. 2.5 Thermal Conductivity Measurement The variation of solid and liquid state thermal conductivity of the PCM and the N PCM composites with change in mass fraction of the graphene nanoparticles is shown in Fig. 6. I t was observed that when the mass concentration of graphene nanoparticles increases, so does the thermal conductivity of PCM composites. The percentile increase in the thermal conductivity of the N PCM composites compared to PCM is summariz ed in Table 2. The solid-state thermal conductivity of the N PCM 1 composite was 0.39 W/(m K), measured at 30 C, with an increase of 1 13.2 % over the base PCM. The solid-state thermal conductivity of N PCM 2 and N PCM 3 composites was increased by 173.48 % and 219.89 % with 2 wt.% and 3 wt.% graphene in the base PCM. The liquid-state thermal conductivity of N PCM 1, N PCM 2, and N PCM 3 composites was enhanced by 75.94 % , 134.59 % , and 161.65 % , respectively, as compared to the base PCM (k PCM at 70 C is 0.13 /(mK)). This trend was attributed to the phenomenon called agglomeration of the nanoparticles in liquid PCM [33], which occurs in N PCM composites with higher concentrations of nanoparticles. Hence, the phenomenon mentioned above was another reason for restricting the graphene mass added in PCM to 3 wt.% . With a further increase in the mass concentration of nanoparticles in PCM, there may not be a proportional improvement in the thermal conduction paths created by nanoparticles inside the N PCM composite. 2.6 DSC-TGA Analysis Fig. 7 represents the DSC curves of PCM and N PCM composites. I t was observed that the DSC curves of the N PCM composites were consistent with that of the base PCM, with a sharp solid-liquid phase transition and a modest decline in the heat flow peak for every 1 wt.% increase in the graphene concentration. Therefore, the above observation indicates that all the prepared N PCM composites were thermally stable. The latent heats of corresponding peaks were calculated by integration method considering the peaks above the baseline using N ETZ SCH Proteus thermal analysis software. Fig. 7. DSC curves of PCM and NPCM composites The DSC data of the samples are listed in Table 2. The melting latent heat capacity of the base PCM was 201.5 J/g. As expected, the latent heat capacity of N PCM composites containing graphene nanoparticles limited to 3 wt.% did not reduce much. Specifically, a reduction in the latent heat capacity of 1.08 % , 2.4 % , and 3.52 % was observed for N PCM 1, N PCM 2, and N PCM 3 composites, respectively. The small reduction in the heat storage capacity was due to the addition of nanoparticles in PCM [34]; for the same quantity of the sample, the nanoparticles occupy some volume in place of PCM resulting in a drop in the latent heat capacity of the N PCM composites. I n contrast, the phase transition curve of PCM and N PCM composites had only a single peak within the defined temperature range, and there were no indications of solid-solid secondary peaks. This observation demonstrates that the obtained PCM was in a pure form with negligible contaminants and had thermally stable phase change properties. I t was clear from the Table 2 data that the temperature that characteriz es the melting was not markedly affected in the presence of nanographene in PCM. I t was noted that the onset and peak melting temperatures of the PCM and N PCM composites ere around 58 C and 65 C. This observation as a piece of significant evidence that the prepared N PCM composites could be used at the desired application temperature of 65 C. Fig. 8 depicts the TG A curve for the PCM and the N PCM composites, which shows that the mass loss has taken place in a single-step decomposition for all the samples. The steep decline curve indicates that the mass loss in PCM and N PCM composites are at very close proximities. As listed in Table 2, the onset thermal decomposition temperatures for PCM, N PCM 1, N PCM 2, and N PCM 3 composites were 183.6 C, 14.7 C, 15.4 C, and 17 C, respectively, which increases with an increase in the graphene mass concentration in the base PCM and follows a linear incremental trend with graphene concentration. The onset decomposition temperature for N PCM 3 composite as about 13 C higher than the base PCM. I t was noticed that the onset degradation temperature of the prepared N PCM composites was higher than that of the PCM, indicating that the N PCM composites had relatively greater thermal stability. The better thermal stability of N PCM composites was linked to graphene nanoparticles’ chemical inertness and its dominance in constructing the thermal barrier (i.e., retardation against the temperature) [35], which prolongs the thermal decompositiontemperature of the N PCM composites. The complete decomposition of the PCM in all the N PCM composites occurs near 300 C, whereas the graphene in N PCM 1, N PCM 2, and N PCM 3 composites remained undecomposed at this temperature. The final mass of each N PCM composite was near the initial mass of nanographene loaded in the composites. Fig. 8. TGA curves of PCM and NPCM composites 3 CONCLUSIONS The experimental investigations on the thermal characteriz ation of the prepared N PCM composites regarding its applicability for TES integrated domestic SWH have been presented in this article. The properties (i.e., microstructure, graphene presence, chemical characteristics, crystal structures, thermal conductivity) and thermal energy storage characteristics of the PCM and the N PCM composites Table 2. Thermal conductivity and DSC – TGA data of the PCM and the NPCM composites Thermal Percentage Melting onset Melting peak Latent heat Percentage Decomposition conductivity, k improved in Samples temperature temperature (LH) capacity reduced in temperature [W/(m·K)] k [%] [°C] [°C] [J/g] LH [%] [°C] Solid Liquid Solid Liquid PCM 0.181 0.133 --58.68 65.30 204.50 -183.60 NPCM 1 0.386 0.234 113.26 75.94 58.25 65.28 202.30 1.08 194.70 (99 wt.% PCM + 1 wt.% graphene) NPCM 2 0.495 0.312 173.48 134.59 58.00 65.15 199.60 2.40 195.40 (98 wt.% PCM + 2 wt.% graphene) NPCM 3 0.579 0.348 219.89 161.65 57.87 65.11 197.30 3.52 197.00 (97 wt.% PCM + 3 wt.% graphene) were investigated using their respective instruments. The key findings are summariz ed as follows: 1. The homogeneous dispersion of graphene and rougher protuberance in N PCM composites was observed via SEM analysis, ensuring the acceptable dispersion and strong embedment of graphene in PCM forms additional heat conduction paths inside the PCM network. 2. The presence of graphene in all the N PCM composites was confirmed using a R aman spectrometer. 3. The FTI R and X R D analysis results confirmed that the addition of nanographene does not affect the chemical structures and crystal structure of the base PCM, meaning that the PCM and nanographene in N PCM composites have only a physical connection where the graphene acts as a thermal conductivity enhancer. 4. Every 1 wt.% increase in graphene content in PCM resulted in a notable increase in the thermal conductivity of the prepared N PCM composites. 5. According to DSC analysis, the prepared N PCM composites had melting characteristics similar to the base PCM. The onset and peak melting temperatures for all the samples were around 61 C and 73 C, respectively, demonstrating that the selected PCM and N PCM composites would be ideal for the proposed application’ s temperature requirement. 6. Compared to the base PCM, there was a significant increase in the thermal conductivity of 219.89 % and 161.65 % in the solid and liquid states, respectively, and an insignificant drop in latent heat capacity of about 3.52 % was noted for the N PCM 3 composite. The significant increase in thermal conductivity of N PCM composites overshadows the minor decrease in their latent heat capacity. 7. The TG analysis demonstrated that the temperature at which the N PCM composites began to decompose increased linearly with increasing graphene mass fraction in the PCM. All the N PCM composites showed greater thermal stability when compared to the PCM because chemically inert graphene in N PCM composites had acted as a thermal barrier, increasing the thermal degradation temperature of the N PCM composites. The investigations mentioned above demonstrate that the dispersion of the graphene nanoparticles in the fatty acid-based PCM is a viable option for increasing the PCM’ s thermal conductivity. Due to the increased thermal conductivity of the N PCM composites, the rate of melting and solidification during charging and discharging cycles could be accelerated, and this phenomenon could improve the overall performance of the N PCM-based LHTES system. Therefore, the proposed N PCM composites could be the best alternative to the conventional paraffin wax PCM for TES-integrated domestic SWHs. The TES integrated SWH system could completely melt the N PCM composites faster than the base PCM with the available solar energy. For the maximum utiliz ation of the available solar energy, the N PCM-based TES system’ s volume capacity could be increased, as the charging duration is reduced, allowing a greater quantity of N PCMs to be used. As a result, the maximum potential of latent heat capacity of N PCMs could be utiliz ed to store additional thermal energy in it. From the application perspective, this advantage would enable the SWHs to deliver additional hot water at the desired temperature. However, the envisaged application of the proposed N PCM composites is not limited to TES integrated SWHs, they could also potentially be employed for TES integrated low-temperature waste heat recovery, and electronic thermal management applications. Furthermore, to ascertain the thermal behaviour of the N PCMs in the longer run, performing accelerated thermal cycling tests is required. 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Licensee: SV-JME Received revised form: 2022-04-29 DOI:10.5545/sv-jme.2022.84 Original Scientific Paper Accepted for publication: 2022-05-12 O ptimiz ation of in-Vehicle Carbon D ioxi de L evel in a 5-Seat Car * Prabhakaran Jayasankar-Jayabal Subbaian G overnment College of Engineering, Department of Mechanical Engineering, I ndia The air quality in a car’s cabin can be five times worse than that of residential and non-residential buildings, resulting in a variety of health issues, such as headache, sore throat, and nausea, which are all symptoms of in-vehicle air pollution. The monitoring of carbon dioxide, which is one of the principal pollutants in car cabins, is required before regulating it. The current research is focused on the recording of carbon dioxide levels for different levels of human load, air speed, and temperature. A statistical analysis and plots were obtained for recorded responses to determine air quality parameters for a minimum value of carbon dioxide level in a five-seat car cabin. Three algorithms (generalized reduced gradient (GRG), response surface methodology (RSM), and genetic algorithm (GA)) were successfully used in a 5-seat car to optimize the in-vehicle carbon dioxide level. The GRG method provided the minimum carbon dioxide level of 471.531 ppm for a one-human load at an air speed of 2 m/s and a temperature of 24 °C. For varying human loads of 2,3,4, and 5, the GRG and GA methods provided carbon dioxide levels of 508.785 ppm, 580.722 ppm, 659.839 ppm and 769.016 ppm, respectively. Comparing all three techniques, the RSM provided carbon dioxide levels of 471.876 ppm, 508.865 ppm, 580.79 ppm, 659.905 ppm, and 769.362 ppm for human loads of 1, 2, 3, 4, and 5, respectively. This study will provide a platform for the researchers working on indoor air quality characteristics to apply soft computing techniques effectively for the evaluation of comfortable healthy environments and for the benefit of the passengers in car cabins. Keywords: carbon dioxide, five-seat car, genetic algorithm, in-vehicle air quality, response surface methodology Highlights • Carbon dioxide level for varying human loads, air speeds, and temperatures in a 5-seat car are studied. • Influence of air quality parameter on response is studied with the help of ANOVA and statistical plots. • Statistical analysis and regression equation are developed for the prediction of carbon dioxide levels. • Air quality characteristics for minimum values of response are obtained through familiar optimization algorithms. 0 INTRODUCTION Human beings spend almost 80 % to 90 % of their time in confined spaces [1], such as houses, workplaces, classrooms, shopping malls, and theatres, as well as vehicles like cars. As a result, the indoor air quality (I AQ ) of living spaces has become a matter of concern. The in-vehicle air quality (I VAQ ) of automobiles, where pollution levels are much higher than the living indoor environments [2] to [4] is one such occupied space that has not been studied. The need for optimal indoor environmental quality (I EQ ) is especially vital in all living and working places with vulnerable populations [5]. This is an area that needs to be seriously researched and studied to ensure better in-vehicle air quality for the passengers. Particulate matter (PM), carbon dioxide (CO 2), carbon monoxide (CO ), volatile organic compounds (VO Cs), and other pollutants impair the I VAQ of the cabins. People employ varying degrees of temperature, velocity, and air-circulation modes for their preferences while commuting in a car with an air-conditioning system, without realiz ing the deleterious repercussions of those settings. The levels of pollutant concentration have higher values in indoor environments that use mechanical ventilation compared to natural ventilation [6]. These factors may lead to an increase in PM, the particle-health correlation has been thoroughly investigated and found to be both valid and confirmatory [7]. The carbon dioxide concentrations within inhabited living spaces are more than such concentrations outdoors, as people generate and exhale CO 2. The levels of the indoor-outdoor CO 2 concentration differential grow as the ventilation rate (i.e., supply of fresh air into the house) per individual reduces [8], As a result of the limited and closed aspect of public transit, contaminants accumulate and lead to rises in concentrations [9]. There is no major change in indoor CO 2 levels with changes in the average outdoor temperature [10]. There are a few factors that lead to the increase in cabin CO 2 levels. Various ventilation fan speeds may lead to variations in cabin CO 2 concentrations [11]. The month of the year when testing is being conducted will also have a significant impact on CO 2 levels in vehicles [12]. When the mode of travel is a subway rather than normal open roads the concentration levels will be high [13]. The CO 2 that the inhabitants breathe enters their bloodstream and creates respiratory problems, harms their health, and even leads to premature deaths [14] and [15]. This not only affects human health; it also triggers nutrition imbalances in plants that are exposed to higher levels of CO 2 [16]. As the amount of CO 2 inside the vehicle Fig. 1. CO2's effect on human decision-making cabin rises, so does the danger of an accident caused by the driver’ s tiredness and reduced agility [17]. Fig. 1 sourced from the research article documented by Satish et al. [18] shows the influence of the increase in CO 2 levels in human decision making. CO 2 is a widely used and practical metric for determining air quality [19]. As of September 2021 [20], the worldwide average ambient CO 2 concentration level was at 413.30 ppm. The permissible amounts of CO 2 in air-conditioned space for human beings are defined by ASHR AE Standard-62 [21]. According to ASHR AE (American Society of Heating, R efrigerating, and Air-Conditioning Engineers), the maximum CO 2 level limit is 700 ppm over ambient surroundings continuously. Even though the value does not apply to CO 2 levels inside cars, it is still significant because a car is a confined space. I n comparison to other small environments, automobile exposure is more difficult to comprehend because it is influenced by several interconnected factors, such as ventilation, motorway type, vehicle type, and self-pollution [22]. Many strategies are used to improve the I AQ for the inhabitants, and many researchers [23] and [24] have sought to optimise heating, ventilation, and air-conditioning (HVAC) systems for indoor conditions. R esearchers have proved that productivity has a significant relationship with indoor air quality [25]. Different monitoring techniques should be applied for natural and mechanical ventilation, as both have different characteristics [26]. Prior research in I VAQ optimiz ation has been documented, but the optimiz ation of input parameters for the vehicle cabin to minimiz e CO 2 levels concerning occupants in a subcompact car is very limited. I n this article, algorithms were used for optimiz ation. 1 EXPERIMENTS 1.1 Air Quality Parameters and their Characteristics I n the modelling process, some parameters gathered are irrelevant or redundant. As a result, before constructing the predictive model, parameter selection is critical. I n data mining, the availability of irrelevant or redundant parameters can obscure primary patterns [27], As a result, before beginning an experiment, identifying the right parameters is essential. O n indoor air quality metrics, the Environmental Protection Agency (EPA), ASHR AE, and Leadership in Energy and Environmental Design (LEED) are all interrelated. The conditions for a healthy environment of particulate matter are 10 micrometres or less in diameter of 50 g/m and 2.5 micrometres or less in diameter of 15 g/m . The humidity is below 60 % , ideally ranging from 30 % to 50 % (EPA). CO concentration should be less than 9 ppm and CO 2 is about 700 ppm above open-air air levels, and it is about 1000 ppm to 1200 ppm, and the temperature is 20.3 C to 23.3 C in winter and 23.9 C to 26.9 C in summer (ASHR AE). The air quality parameters, such as air speed and temperature, were varied at different levels for varying human loads and CO 2 characteristics were measured accordingly. 1.2 Assumptions To avoid ambiguity and maintain a regulated atmosphere inside the vehicle, the following assumptions were made, and similar ones were proposed to be applicable by Thirumal et al. [28] for optimiz ing I AQ characteristics using a multi-objective genetic algorithm. When the car’ s doors were closed, the leak is negligible. The air-conditioning is set in fresh air supply mode. The CO 2 may vary based on location and environmental conditions. Within the car, volatile organic component pollutants are not present. Before beginning the experiment, the indoor regulated space is allowed to reach equilibrium with the outdoor circumstances. Pollen, dander, dust solids, and particulate matter are not considered. Tobacco smoking, dust particles, and further unknown elements are not present in the space. The fan motor’ s input current and air speed will change when the engine rpm changes. Hence, the average air speeds were approximated as (1, 2, 3, 4, 5, 6, 7 a nd 8) m/s. 1.3 Experimental Set-Up 1.3.1 Description of Locale The assessment was recorded in an important roadway of the Karaikudi municipality, which is the 20th highest urban accumulation of Tamilnadu with a population of 106,714 (201 1 census survey data). I t is a heritage town situated in Sivagangai District, Tamilnadu, I ndia. Fig. 2 shows the location of the town. This place can be accessible by the Tiruchirappalli– R ameswaram highway that passes through Karaikudi. This locus is located at 10.07 N latitude and 78.78 E longitude. The average maximum temperature is about 3 4 C (~ 93 F), and the average lowest temperature is about 24 C (~ 75 F); the twelve-monthly middling rainfall in Karaikudi is about 920 millimetres, the topography of the place is predominantly flat and some gravel areas are also found in the surroundings. The area of the municipality is about 33.75 km . 1.3.2 Measurements To measure in-vehicle carbon dioxide concentration a portable I AQ CO 2 meter, the Extech device (Model CO 250) by FLI R commercial systems I nc., USA, has been utiliz ed. A similar experimental setup and equipment were used by Ayyakkannu et al. [29] for measuring in-vehicle pollutants. This measuring device works with the theory of the non-dispersive infrared (N DI R ) technique. The device can assess up to a maximum range of 5000 ppm with 1 ppm resolution. The device was positioned in the centre of the car cabin at breathing level. The instrument was Fig. 2. Location of Karaikudi town and experimental test route calibrated and field-tested before the measurement of CO 2. The measuring instrument is set to record data at a one-minute time interval; the data is then transferred to a laptop PC with an acquisition software provided by the device manufacturer to record the CO 2 values from the instrument. The schematic sketch is shown in Fig. 3, this set-up is used for carrying out our research. A five-seat hatchback car was chosen; it has air-conditioning with a variable temperature from 18 C to 25 C and with recirculation modes. Three tests are carried out for each human load varying from one to five, as the CO 2 concentration will significantly increase according to the number of passengers [30]. The mean values of three tests were considered for the final optimiz ation of the parameters. The route at Karaikudi, where the test was carried out was about 13 km per cycle, which includes a college road with trees, traffic signals, a petrol station, road junctions, and a bus stand. The test route is shown in Fig. 2. 1.3.3 Design of Experiments and Regression Line The design of experiments for the study was designed using full factorial design and regression modelling in statistical software. I n each comprehensive trial run or repetition of the studies, the full factorial design establishes experimental points utiliz ing all feasible combinations of the levels of the components. The vertices of a hypercube in the n-dimensional design space are determined by the least and highest values of each of the factors. These factors are the experimental design points in a full factorial design; therefore, these experimental points are also known as factorial points. R egression analysis is a type of predictive modelling approach that focuses on the correlation between a dependent (target) and an independent variable (predictor). This technique is used for the prediction of the finding of the fundamental effect relationship between the variables. The quartic non­linear regression model was suggested due to the better value of correlation coefficient and fitting to the data points. The refined model is also developed for predicting carbon dioxide levels for various human loads, which are further used for finding the better value of air quality parameters. 1.4 Search Optimization Methods Among the various algorithms, the statistical, gradient, and metaheuristic algorithms are popularly used by most researchers for finding the optimum value of responses. The familiar algorithms in the above three categories are effectively chosen for finding indoor air quality characteristics in the present investigation. R esponse surface methodology (R SM) is based on indirect optimiz ation self-organiz ation; G R G is the most commonly used reduced gradient method to solve nonlinear problems, which finds a local optimal solution; genetic algorithm (G A solves optimiz ation problems based on a natural selection process derived form biological evaluation; it uses high-level search procedures for minimiz ation of response variables. Fig. 3. Schematic sketch of the experimental setup 1.4.1 Response Surface Method The R SM is a commonly used arithmetical and mathematical approach for developing and evaluating a process in which many factors impact the response of interest. This strategy aims to optimiz e the response time. The development of an approximation model for the true response surface is required for the R SM to be used in reality [31]. The R SM searches for a suitable approximation relationship between input and output variables to find the best operating conditions for a system or a portion of the factor field that complies with the requirements. The R SM was used to optimiz e the conditions of the experiment by the author Yan et al. [32] for the optimiz ation and analysis of CO 2 surface assimilation by imidaz ole and tetraethylenepentamine operative sorbent material. The R SM includes three stages (i.e., design, analysis, and optimiz ation) using statistical software; a non-linear regression equation was developed and optimiz ed using this approach for varying human loads in the present investigation. The AN O VA Table and statistical plots were also generated to study the individual, interaction, and higher-order effects of air quality parameters. 1.4.2 Generalized Reduced Gradient The generaliz ed reduced gradient (G R G ) method is a nonlinear inequality constraint-aware expansion of the reduced gradient method. I n this method, a quest path is found in which the current dynamic limitations remain precisely effective for any move. Microsoft Excel uses three solving methods such as G R G N onlinear for problems that are smoothing nonlinear, LP Simplex for problems that are linear, and Evolutionary for non-smooth problems. G R G is used to find the optimum CO 2 level for various human loads by setting quadratic estimates, forward derivatives, and N ewton search in the solver option. The max time was set to 100 seconds for 100 iterations with the precision value of 0.000001, the tolerance was set to 5 % and the convergence was 0.0001i n the Microsoft Excel Solver. 1.4.3 Genetic Algorithm A genetic algorithm is a search heuristic based on Charles Darwin’ s natural-evolution hypothesis. This algorithm mimics natural selection, in which the fittest individuals are chosen for reproduction to create the next generation. G A have been used to solve a wide variety of systematic, engineering, and financial problems. G A are robust because they can find the global optimum in a multimodal landscape [33]. The initial population, fitness function, selection, crossover, and mutation are the five phases considered in a genetic algorithm. MATLAB’ s R 2016a graphical user interface was used to find the minimum value of the function. The double vector population type opted with the population type was left to default at 50 for five or fewer variables; otherwise, it was 200. The creation function was constrained dependent on keeping the initial population, initial scores, and initial range as default. For the fitness-scaling function, rank was chosen. The stochastic uniform was set for the selection function. I n the reproduction section, elite count and cross-over fraction were default. Mutation and crossover functions are constraint-dependent. Migration direction is forward keeping fraction and interval values as default 0.2 and 20, respectively. For the constraint parameters, the nonlinear constraint algorithm Augmented Lagrangian is used with an initial penalty and penalty factor as default. The hybrid function was set to none, and the stopping criteria were completely used with default settings. 2 RESULTS AND DISCUSSION 2.1 Experimental Observation of Air Quality Characteristics The three factors that are varied in three levels (5 8 8 320) contributed 320 experimental runs as per full factorial design. The standard deviation for human load, air speed, and temperature are 1.42, 2.29 and 2.29, respectively. A minimum value of 460 and a maximum value of 949 were observed in carbon dioxide level. The mean and standard deviations for the recorded value of responses are 633 and 128.9, respectively (Eq. (1) ). x °xx .2 °.. x ˜, ˆ˜ , (1) nn where x is mean, n number of observations, x individual observations, and s standard deviation. The observation of the highest frequency for 320 data in 18 bins was obtained, which is shown in Fig. 4. The frequency is calculated using number of counts in the histogram range specified in x axis whereas proportion is calculated using the Eq. (2). Frequency Proportion = . (2) n The proportion and density plots are also obtained in correlation with recorded values of carbon dioxide levels. The CO 2 level is ranged from 460 ppm to 949 ppm and the corresponding frequency values up to 60 and proportion up to 0.2 are plotted. 2.2 Development of NLRM for Carbon Dioxide Level The design is built, and response data is added to formulate a polynomial model of response design by including individual, interaction, and lower and higher-order terms. The polynomial degree of four, which is in the form of a quartic function was observed based on the best fit and the coefficient of correlation of 0.9975. The statistical summary of factors and response are in Table 1. ˜°4 32 fx .ax .bx .cx .dx .e . (3) The adjusted R 2 associates the explanatory power of regression replicas with varying numbers of predictors, whereas the projected R 2 shows how well a regression model predicts fresh observations’ responses. The predicted R 2 of 0.9968 is in satisfactory agreement with the adjusted of 0.9972 due to the variance of less than 0.2. The subgroup sample standard deviation divided by the subsection mean, multiplied by 100, yields the percentage of the CV plot point. I n practice, the percentage of CV is the proportion of the mean that the standard deviation. The model F -value of 3389.3 shows the model is considerable. There is only a 0.01 per cent probability that an F -value of this massive might appear due to noise. Model terms with P -values less than 0.0500 are noteworthy. x 1, x 3, x 1 x 2, x 1 x 3, x 1 2, x 3 2, x 1 x 2 x 3, x 12x 2, x 12x 3, x 1 3, x 12 x 22, x 12 x 3 2, x 13 x 2, x 13 x 3, x 1 x 23 , x 1 x 3 3, x 1 4, x 3 4 are significant model terms in this scenario. The model terms are not significant if the value is larger than 0.1000. The model decrease may enhance your model if there are several irrelevant model terms (not involving those necessary to support hierarchy). The nonlinear regression model was developed using statistical software, as given in Eq. (4) . f (x ) 10021.1427 1030.3478 x 1 – 254.83387 x 2 – 1784.46657 x 3 – 2.82325 x 1 x 2 – 213.63461 x 1 x 3 + 32.61305 xx + 261.08873 x 231 + 10.19365 x + 130.89552 x 23 –1.15965 xxx + 4.79252 xx 12312 + 0.610780 xx + 0.559092 xx 1312 + 10.14499 x 1 x 3 – 0.205609 x 2 x 3 Fig. 4. Histogram for response; a) frequency, and b) proportion Table 1. Statistical summary of factors and response Factor/ Response Factor 1 Factor 2 Factor 3 Response Name Human load [No.] Air speed [m/s] Temperature [°C] CO2 [ppm] Minimum 1 1 18 460 Maximum 5 8 25 949 Coded Low -1 . 1.00 -1 . 1.00 -1 . 18.00 - Coded High +1 . 5.00 +1 . 8.00 +1 . 25.00 - Mean 3.00 4.50 21.50 632.88 Std. Dev. 1 2 2 128.87 476 Prabhakaran, J. -Jayabal, S. – 1.43142 x 2 x 3 – 62.51457 x 1 transformation response as shown in Fig. 5a . A graph .24 08 0 x – 2 4 .3 31 26 x – 0.1 3 9 28 51 xx 1 2 of anticipated response values versus actual response – + 0.012856 x xx – 0.172513 xx 12313 – 0.030896 xx x + 0.028628 xxx 123123 + 0.005322 x 2 x 3 – 0.448041 x 1 x 2 + 0.803695 xx + 0.090972 xx 1312 – 0.143119 x 1 x 3 + 0.004359 x 2 x 3 4 + 0.0207 25 xx + 4.00456 x 231 + 0.048793 x 24 + 0.053101 x 34 . (4) The sequential p-value is less than 0.0001 and the difference between the adjusted and predicted coefficient of correlation is 0.0004 which indicated the best fit of the quartic model for 320 values of carbon dioxide level (Table 2). The sequential p-value is < 0.0001 for linear, two-factor interaction, quadratic, cubic, quartic, and quintic models. The best fit is selected based on the higher value of coefficient of correlation. Table 2. Fit summary and selection of model Source Sequential p-value Adjusted RČ Predicted RČ Remarks Linear < 0.0001 0.891 0.8889 - 2FI < 0.0001 0.9197 0.917 - Quadratic < 0.0001 0.9935 0.9933 - Cubic < 0.0001 0.9942 0.9938 - Quartic < 0.0001 0.9972 0.9968 Suggested Fifth < 0.0001 0.9985 0.9981 Aliased 2.3 ANOVA, Diagnostics and Statistical Plots The model includes the overall model test for significance and how much variance in the reaction is described by the model. I ndividual factors are removed from the model and tested separately. The residual indicates how much variation in the response remains unaccounted for. The degree to which the model predictions differ from the observed is referred to as “ lack of fit” . The amount of variation between replicate runs is known as “ pure error” . The degree of variation around the mean of the observations is shown by the corrected total. The individual effect of human load and temperature, combined effect of air speed and temperature, are significant terms in AN O VA listed in Table 3. The second-order effect of human load with air speed and temperature is also significant. The normal probability plot shows whether the residuals have a normal distribution and, as a result, follow a straight line. For better analysis, scatter with normal data in an s-shaped curve showed the values can be used to spot a value, or a collection of values, that the model cannot predict is shown in Fig. 5b. The assumption of constant variance is tested by plotting the residuals against the ascending expected response values as shown in Fig. 5c . A studentiz ed residual is calculated by dividing the residual by an estimate of its standard deviation. The standard deviation for each residual is computed with the observation excluded. A plot of the residuals against the experimental run order to look for hidden variables that could have influenced the response during the experiment is shown in Fig. 5d. I nternally studentiz ed residuals are defined for each observation as an ordinary residual divided by an estimate of its standard deviation. Cook’ s distance is a measurement of how much the entire regression function changes when the i th point is removed from the model fitting (Fig. 6a ). The plot of the residuals versus any factor if the variation not accounted for by the model varies depending on the level of the factor is in Fig. 6b. The response surface plot and contour plot for the interaction of variables are shown in Figs. 6c and d, respectively. Surface plots are diagrams of three-dimensional data that shows a functional relationship between a designated dependent variable and two independent variables. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices called “ contours” . 2.4 Optimization of Carbon Dioxide Level 2.4.1 RSM Optimization for Minimum Value of Carbon Dioxide Level The human load is set to 1, 2, 3, 4, and 5, whereas the air speed and temperature are set in range as criteria and the minimiz ation of carbon dioxide was carried out using response surface methodology. The minimum value of carbon dioxide levels for various human loads in accordance with air speed and temperature are given in Table 4. The optimiz ation looks for a set of factor values that satisfies all the criteria for each of the responses and factors at the same time. The desirability function indicates the desirable limits for each response. The maximum value of air speed and low value of temperature is needed for getting the minimum value of CO 2 level in a 5-seat car. The minimum value of air speed and upper limit of temperature provided a minimum value of carbon dioxide of 472. The setting of air speed and Table 3. ANOVA for response and significance of factors Source x x Sum of Squares df Mean Square F-value p-value Remarks Model 5.29E+06 34 1.55E+05 3389.3 < 0.0001 Significant x 1 3.76E+05 1 3.76E+05 8202.13 < 0.0001 x 2 145.96 1 145.96 3.18 0.0755 x 3 6182.8 1 6182.8 134.82 < 0.0001 x 1 x 2 851.29 1 851.29 18.56 < 0.0001 x 1 x 3 5184.82 1 5184.82 113.06 < 0.0001 x 2 x 3 31.56 1 31.56 0.6882 0.4075 x 1 461.81 1 461.81 10.07 0.0017 x 2 33.99 1 33.99 0.7412 0.39 x 3 532.36 1 532.36 11.61 0.0008 x 1 x 2 x 3 296.12 1 296.12 6.46 0.0116 x 2 x 3 2296.85 1 2296.85 50.08 < 0.0001 x 1 x 3 1101.23 1 1101.23 24.01 < 0.0001 x 1 x 2 15.47 1 15.47 0.3374 0.5618 x 1 x 3 0.7741 1 0.7741 0.0169 0.8967 x 2 x 3 3.98 1 3.98 0.0867 0.7686 x 2 x 3 54.02 1 54.02 1.18 0.2787 x 1 594.83 1 594.83 12.97 0.0004 x 2 0.4001 1 0.4001 0.0087 0.9256 x 3 162.26 1 162.26 3.54 0.061 x 1 x 2 699.53 1 699.53 15.25 0.0001 x 1 x 2 x 3 4.08 1 4.08 0.089 0.7657 x 1 x 3 559.98 1 559.98 12.21 0.0006 1 x 2 x 3 67.35 1 67.35 1.47 0.2266 1 x 2 x 3 57.83 1 57.83 1.26 0.2624 x 1 x 3 4 1 4 0.0871 0.768 x 1 x 2 971.26 1 971.26 21.18 < 0.0001 x 1 x 3 3125.25 1 3125.25 68.15 < 0.0001 x 1 x 2 393.27 1 393.27 8.58 0.0037 x 1 x 3 973.35 1 973.35 21.22 < 0.0001 x 2 x 3 2.37 1 2.37 0.0517 0.8203 x 2 x 3 53.58 1 53.58 1.17 0.2807 x 4 1 8445.27 1 8445.27 184.15 < 0.0001 x 4 2 172.39 1 172.39 3.76 0.0535 x 4 3 204.18 1 204.18 4.45 0.0357 Residual 13070.01 285 45.86 temperature for an intermediate value of human loads are effectively determined using response surface optimiz ation. The maximum value of air speed and lower limit of temperature provided a minimum value of carbon dioxide of 769.362 ppm for the maximum capacity of the vehicle. 2.4.2 GRG Optimization for Minimum Value of Carbon Dioxide Level The minimum CO 2 concentration value of 471.537 ppm was achieved in accordance with air speed and temperature of 2 m/s and 24 C, respectively, for a single human load using the G R G technique. I n a comparison of the three optimiz ation methods utiliz ed for one human load, among R SM (471.876) , G R G (471.537) , and G A (471.61 1) , the lowest CO 2 level Fig. 5. Plot of residuals; a) normal % probability, b) predicted vs. actual, c) residuals vs. predicted, and d) residuals vs. run was attained in G R G methods. The carbon dioxide levels of 508 .785 ppm, 580.722 ppm, 659. 839 ppm and 769.016 ppm were obtained for human loads 2, 3, 4 a nd 5, r espectively. When compared with R SM, G R G provided a minimum value of carbon dioxide level for all levels of human load. The search procedure in G R G found a better value of results when compared with statistical-based optimiz ation. R SM is a mathematical and statistical technique for the empirical model building which predicted better value of responses using indirect optimiz ation based on self-organiz ation whereas the N ewton method used a root-finding approach by polynomial approximation using Taylor’ s series. The air speed of 7 m/s and temperature of 18 C were obtained for a minimum value of carbon dioxide level of 769.016 ppm in G R G and G A methods. 2.4.3 GA Optimization for Minimum Value of Carbon Dioxide Level The minimum CO 2 concentration of 471,61 1 ppm for one human load was obtained for the air speed of 2 m/s and a temperature of 24 C using the G A method, which was slightly higher than the optimum value (471.537 ppm) obtained using the G R G method. The lowest ideal value for a five-person capacity is 769,016 at an air speed of 7 m/s and a temperature of 18 C, respectively. The carbon dioxide levels of 508.785 ppm, 580.722 ppm, 659.839 ppm and 769.016 ppm were obtained for human loads 2, 3, 4, and 5 respectively which is the same as the results obtained using the G R G method. When comparing the results acquired using the G A method in MATLAB software to the obtained results using R SM optimiz ation in Design-Expert software, the G A approach produced Fig. 6. Design plots; a) Cook’s distance, b) residual vs. factor, c) 3D surface plot, and d) contour plot Table 4. Optimum values of CO2 level for various human loads and confirmation of responses Sl. No. Algorithm Factors Airspeed [m/s] Air temp. [°C] CO2 [ppm] Predicted response Experimental response Absolute percentage of error 1 2 24 471.876 479.983 1.7 2 3 21 508.865 503.832 0.2 3 RSM 3 20 580.79 586.231 0.9 4 6 19 659.905 671.376 1.7 5 8 18 769.362 752.263 2.2 6 2 24 471.537 479.983 1.8 7 3 21 508.785 503.832 0.9 8 GRG 3 19 580.722 586.231 0.9 9 6 19 659.839 671.376 1.7 10 7 18 769.016 777.847 1.1 11 2 24 471.611 479.983 1.3 12 3 21 508.785 503.832 0.9 13 GA 3 20 580.722 589.124 0.9 14 6 19 659.839 671.376 1.7 15 7 18 769.016 777.847 1.1 480 Prabhakaran, J. -Jayabal, S. lower results due to the metaheuristic approach (High-level search procedure). I n addition, when compared to R SM, the air velocity for the five human load conditions is lowered by one level in the G A optimiz ation technique. The G A plots for optimiz ation plotting fitness value vs. generation are shown in Fig. 7. The values are obtained in between 50 to 100 generations for the better value of fitness. The same value of best fitness and mean fitness was obtained which indicated the minimum value of carbon dioxide level for various human loads. 2.4.4 Confirmation of Optimum Conditions The experiments were conducted for the optimum conditions obtained using R SM, G R G , and G A methods; the carbon dioxide levels values were reordered and compared with the optimum values. The comparison graph of experimental results and predicted results are shown in Fig. 8. The blue, green, and yellow lines indicated the optimum value of carbon dioxide levels for R SM, G R G , and G A, respectively, whereas the orange, red, and violet lines indicated the experimental value of carbon dioxide levels for R SM, G R G , and G A, respectively. R SM predicted carbon dioxide levels of 471.876 ppm, 508.865 ppm, 580.79 ppm, 659.905 ppm, and 769,362 ppm for human loads 1, 2,3,4, and 5 and the same is confirmed with experimental values of 479.983 ppm, 503.832 ppm, 586.231 ppm, 671.376 ppm, and 752.263 ppm. The absolute percentage error of values 1.8, 0.9, 0.9, 1.7, and 1.1 for human loads 1, 2, 3, 4, and 5 were obtained using the G R G method. G A predicted carbon dioxide levels of 471.61 1 ppm, Fig. 7. GA plot for optimization of carbon dioxide level for different human load 508.785 ppm, 580 .722 ppm, 659.83 9 ppm, and The absolute ratio of error is determined using the 769.016 ppm for human loads 1,2,3,4, and 5 and following formulation. the same is confirmed with experimental values of 479.983 ppm, 503.832 ppm, 589.124 ppm, 671.376 Percentage of error = ppm, 777.847 pp m, respectively. °Experimental valueOptimum value . ˜ . (5 ) Experim eentalvalue Fig. 8. Confirmation testing comparative graph between optimum and experimental value for all three algorithms; a) RMS, b) GRG, and c) GA The absolute percentage of error is less than 2.5, indicating good level of accuracy in the confirmation of results the maximum absolute percentage of error of 2.2 in R SM, 1.8 in G R G and 1.7 in G A were obtained. The close prediction of experimental value with the predicted value was obtained. 3 CONCLUSION Experimental runs were carried out for different values of human load, air speed, and temperature, and the observed value of carbon dioxide levels were recorded. R esponse surface design, analysis, and optimiz ation were done to find the minimum value of carbon dioxide levels for various human loads and corresponding air velocity and temperature. I n addition, with response surface methodology, the generaliz ed reduced gradient and genetic algorithm are also used to find the minimum value of carbon dioxide levels in the present investigation. The minimum carbon dioxide level of 471 .531 ppm for one human load was obtained for the air speed of 2 m/s and a temperature of 24 C using the G R G method. The carbon dioxide levels of 508.785 ppm, 580.722 ppm, 659.839 ppm and 769.0 16 ppm were obtained for human loads 2, 3, 4 and 5 , respectively, using G R G and G A methods. The experiment was conducted for the optimum value of I VAQ parameters, and the corresponding CO 2 level was measured. The absolute percentage of error was found for all three algorithms, which resulted in the genetic algorithm providing a better value of results for the current problem. O ther indoor air quality characteristics, such as relative humidity, particulate matter, carbon monoxide level, and oxygen level may be optimised using the optimiz ation techniques, and the optimal value for comfort and healthy living in an enclosed environment can be found. These methods can be used to determine the optimal inlet HVAC parameters such as inlet velocity, the quantity of fresh air supply, type of filtration, and required temperature for various human loads in a confined area. This application could lead to a better and healthier indoor living environment. Even though this method has a wide range of applications, the I AQ characteristics vary from place to place, and values in different countries may deviate at a significant pace depending on the environmental circumstances and abrupt climate changes of that country as well as the region under study. I n the future, the same study can be extended to other vehicle cabins, such as those of SUVs or seven-seat cars, trucks, buses and even trains by varying different passenger loads, elevation of location under study, ventilation type, and outside environmental weather conditions. 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ID 105639, DOI:10.1016/j. jece.2021.105639. [33] Huang, W., Lam, H.N. (1997). Using genetic algorithms to optimize controller parameters for HVAC systems. Energy and Buildings, vol. 26, no. 3, p. 277-282, DOI:10.1016/S0378­7788(97)00008-X. Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, 485-492 Received for review: 2022-04-25 © 2022 The Authors. CC BY 4.0 Int. Licensee: SV-JME Received revised form: 2022-06-20 DOI:10.5545/sv-jme.2022.174 Original Scientific Paper Accepted for publication: 2022-07-08 O ptimiz ation in the R esistant Spot-We lding Process of AZ 61 M agnesium Alloy Davood Afshari1,* – Ali G haffari1 – Z uheir Barsum2 1 University of Z anjan, I ran 2 R oyal I nstitute of Technology, Sweden In this paper, an integrated artificial neural network (ANN) and multi-objective genetic algorithm (GA) are developed to optimize the resistance spot welding (RSW) of AZ61 magnesium alloy. Since the stability and strength of a welded joint are strongly dependent on the size of the nugget and the residual stresses created during the welding process, the main purpose of the optimization is to achieve the maximum size of the nugget and minimum tensile residual stress in the weld zone. It is identified that the electrical current, welding time, and electrode force are the main welding parameters affecting the weld quality. The experiments are carried out based on the full factorial design of experiments (DOE). In order to measure the residual stresses, an X-ray diffraction technique is used. Moreover, two separate ANNs are developed to predict the nugget size and the maximum tensile residual stress based on the welding parameters. The ANN is integrated with a multi-objective GA to find the optimum welding parameters. The findings show that the integrated optimization method presented in this study is effective and feasible for optimizing the RSW joints and process. Keywords: resistance spot welding, residual stresses, artificial neural network, genetic algorithm, AZ61 magnesium alloy Highlights • A full factorial design of experiments has been utilized to investigate the effects of the welding parameters on the nugget size and the residual stresses in the AZ61 resistance spot welded joint. • The nugget size and the residual stresses have been measured experimentally based on the DOE. • Two separate ANN models have been created to predict the nugget size and the maximum residual stress using the welding parameters. • An integrated ANN-ANN-GE algorithm has been developed to optimize the welding process. • The results show that the welding current and the welding time have significant effects on the nugget size and the maximum residual stress, respectively. • The findings confirm that the presented algorithm is effective and feasible to optimize the RSW process. 0 INTRODUCTION I n recent years, alloys of Magnesium (Mg) have become of great attraction and significance as easy-to-machine metals with exceptional strength-to-weight ratios, for various sectors including automotive, aerospace, and structural applications [1]. Magnesium is the lightest of all commonly used structural metals; with a density that is approximately two thirds that of aluminium and one quarter that of steels. O ther than this, magnesium alloys have a high strength-to-density ratio, high specific heat, low melting temperature, and good castability, hot formability, recyclability, and sound-damping capabilities [1] to [5]. These properties bring a significant interest in many industrial applications to reduce the weight of the structures. Despite these considerable interests, using magnesium alloys in the industry remains limited compared with aluminium and steel alloys due to some technical problems. For example, the resistance spot welding (R SW) of magnesium alloys is more complex than in steel and aluminium alloys and needs different welding parameters. Although many new welding processes have been developed and presented for magnesium alloys (such as friction stir welding [6] to [9], laser welding [10] and [11]), R SW remains the most common joining process. I n R SW, a high electric current is passed through the sheets via electrodes for a short time, which results in the generation of a melting z one between the sheets. After switching off the electrical current and undergoing a cooling process, a nugget is created in the welding area. Studies have shown that the nugget siz e is the most important controlling factor to determine the mechanical strength of the joint. The larger nugget results in higher mechanical strength [12] to [14]. I n addition, when the molten metal starts cooling down to room temperature, a large temperature gradient occurs in the heat-affected z one (HAZ ). This non-uniform temperature change leads to residual stresses in the welded joint. The residual stresses significantly affect stress corrosion cracking, hydrogen-induced cracking, and fatigue strength. R egardless of the loading conditions on spot-welded joints, tensile residual stress deteriorates the fatigue strength and the quality of the joint [15] to [17]. Therefore, selecting the optimum welding parameters to achieve the maximum nugget siz e and the minimum tensile residual stress is the key factor in obtaining high-quality welding and joint strength. Yi et al. [18] introduced a non-linear multiple orthogonal regression assembling model to optimiz e the welding parameters of R SW on galvaniz ed steel sheet. They evaluated the effects of the welding parameters on the nugget siz e and optimiz ed the parameters to maximiz e it. Hamidinejad et al. [19] predicted the mechanical strength of the R SW in the galvaniz ed steel joints based on the welding parameters. They also optimiz ed the welding parameters with a genetic algorithm (G A) to improve the tensile-shear strength. A multi-objective Taguchi method was applied to optimiz e the welding parameters in R SW of low-carbon steel by Muhammad et al. [20]. The main purpose of the study was to select the optimum R SW parameters to increase the nugget siz e and decrease the heat-affected z one (HAZ ). Z hao et al. [21] utiliz ed the response surface methodology (R SM) to optimiz e the nugget siz e, the mechanical strength, and the failure load in small-scale R SW of titanium alloy. A hybrid AN N -G A model was developed by Pashaz adeh et al. [22] to optimiz e the welding parameters of R SW on AI SI 1008 steel alloy and achieve the maximum nugget siz e. Mirz aei et al. [23] developed a finite element (FE) model to predict the nugget siz e in R SW on galvaniz ed steel. They used the R SM to optimiz e the welding parameters and obtain the maximum nugget siz e and maximum mechanical strength. Valera et al. [24] applied the Taguchi design of experiments to optimiz e the R SW of TR I P steel. The optimiz ed electrical parameters were presented to increase the tensile-shear strength of the welded joints. The dissimilar R SW of AI SI 316L austenitic stainless steel and 2205 duplex stainless steel were optimiz ed by Vignesh et al. [25] using Taguchi’ s L27 orthogonal array (O A) design. Their results revealed that the welding current is the most dictating factor in achieving the highest tensile strength with superior weld quality. The literature indicates that the optimiz ation in the R SW of magnesium alloys has not been studied extensively. The purpose of this study is to contribute to the optimiz ation of the welding parameters: electrical current, welding time, and electrode force of AZ 61 magnesium alloy R SW joints. A full factorial design of the experimental (DO E) results is carried out and then two separate AN N models are developed to predict the nugget siz e and the maximum residual stress. Finally, an integrated AN N -AN N -G A algorithm is developed to optimiz e the welding parameters. 1 METHODS I n this study, AZ 61 magnesium alloy has been used to prepare the welded samples. The nugget siz e has been measured experimentally for all the samples and an X -ray method has been utiliz ed to measure the residual stresses. To predict the nugget siz e and the residual stresses, two AN N models have been developed. Finally, the welding parameters have been optimiz ed by an integrated AN N -AN N -G E to obtain the maximum nugget siz e and the minimum tensile residual stress. 2 EXPERIMENTAL AZ 61 magnesium alloy sheets have been used to prepare the welding samples and their chemical composition is given in Table 1. Table 1. Chemical compositions of AZ61 Mg alloy [wt.%] CaCuFe SiMnZn AlMg 0.001 0.001 0.003 0.04 0.19 0.72 6.3 92.7 Fig. 1 shows the specification of the specimens (100 m m 25 m m 1.2 m m) and the welded joints. performed by using a N ovin Saz an Company Machine (model SSA014, I R AN , Fig. 2) with a CU08 controller and nominal welding power of 1 20 kVA. Both copper electrodes were cooled by circulating water during the welding. The welded samples have been cut along the centreline and the nugget siz e has been measured using an optical microscope (Fig. 3) . A SEI FER T -ray diffractometer (model 3000P TS, Fig. 4) has been utiliz ed for the residual stress measurements. Measurements have been performed in the centre of the welded z one where the maximum tensile residual stress occurs [17]. The residual stresses have been measured on both sides of the welded samples in radial and transverse directions. The average of measured residual stresses has been reported as the maximum tensile residual stress in the welded z one. Fig. 4. The SEIFERT X-ray diffractometer model 3000PTS 3 RESULTS AND DISCUSSION 3.1 The Full Factorial Experiment Design I n this study, a full factorial design of an experiment has been used to design the welding parameters schedule. Electrical current, welding time, and electrode force have been considered to be the main influencing welding parameters. The lower bond of each welding parameter was selected to achieve the nugget siz e recommended by AWS [26], and the higher bond was chosen to prevent weld splash and spatter. The appropriate ranges of the welding parameters are given in Table 2. The full factorial 2 design of experiments has been designed, k is the k number of variables, which is 3 here with lower and higher bonds of 1 and 1, respectively. According to the full factorial DO E, a total of 8 combinations of the input parameters were considered. Table 2. The higher and lower bond of RSW parameters Welding current [kA] Welding time [cycle] Electrode force [N] Higher bond (+1) 12 12 848 Lower bond (-1) 16 16 1130 The samples have been welded based on the welding parameters given in Table 3, and the results Table 3. The full factorial DOE Sample Welding current [kA] Welding time [cycles] Electrode force [N] Nugget size [mm] Maximum residual stress [MPa] 1 12 12 848 4.54 276 2 16 12 1130 5.76 255 3 12 12 1130 4.42 254 4 16 16 1130 6.34 216 5 16 12 848 5.75 280 6 12 16 1130 4.64 213 7 12 16 848 4.68 234 8 16 16 848 6.33 238 obtained from the nugget and the residual stress measurement are displayed in Table 3. Fig. 5 illustrates the results of the DO E analysis for the nugget siz e. The Pareto diagram shows that although the electrical current, welding time, and their interaction affect the nugget siz e, the electrode force and its interaction with other variables have almost no effect. I n addition, the electrical current is the most influential parameter on the nugget siz e. The N ormal diagram confirms the results obtained from the Pareto diagram. The electrical current is the furthest point from the normal line, which means it is the most significant parameter. The points close to the normal line have no impact on the output. Similar results have been reported in previous studies for other materials [12] to [15] and [18] to [24]. The results of the DO E analysis for the residual stress are displayed in Fig. 6. According to the Pareto and N ormal diagrams, the welding time and the electrode force affect the residual stresses. Although the welding time is the most influential parameter on the residual stress, the electrical current has almost no effect. The results are similar to those previously reported for R SW of Al joints [16]. 3.2 The Artificial Neural Networks AN N is a powerful and reliable model to predict complex phenomena with multiple variables. AN N is also very flexible in terms of the number of variables, the training algorithm, transfer functions, and the structure. An AN N consists of several layers: an input layer, some hidden layers, and an output layer. I n addition, each layer involves some neurons. The number of hidden layers is usually one or, in specific cases, two. Using more than two layers is rarely done and is not recommended [27]. Two separate multilayer backpropagation feedforward AN N s have been used to predict the nugget siz e and the maximum tensile residual stress. Theses AN N s have been implemented using Matlab. The Levenberg-Marquardt training algorithm has been utiliz ed to train the AN N s. This algorithm minimiz es a combination of squared errors and weights and then determines the correct combination. The transfers between layers have been done by using a combination of Tansig and Purelin transfer functions. Finally, the mean square error (MSE) function determines the ability of the AN N s to predict the outputs. According to the number of the welding parameters and the output, the number of neurons in the input and output layers of both AN N s are three and one, respectively. The performance of the AN N s depends on the number of hidden layers and the number of their neurons. Hence, many trials need to be made to find the optimum structure for the AN N by changing the number of hidden layers and their neurons. Since there were two different AN N , two different structures have been considered. The proper structure for the first AN N to predict the nugget siz e was 3 6 1. The best structure for the second AN N to predict the maximum residual stress has been found to be 3 10 1 using a trial-and-error procedure. I n addition, the values of the variables and outputs have been normaliz ed between 1 and 2 (Eq. (1) ) in order to since the experimental testing would have been time consuming. increase the accuracy and speed of training the AN N s. P n ˜ PP °min P °P max min .1, (1) Table 4. The levels of RSW parameters for running the ANNs RSW Parameters Levels Welding current [kA] 12-13-14-15-16 Welding time [cycles] 12-13-14-15-16 Electrode force [N] 848-990-1130 The overfitting is the usual phenomenon that may occur in the training of AN N . I t happens when the AN N memoriz es the training data instead of building input-output mapping for the problem. Thus, determining the number of training and test data has a very important role in avoiding overfitting. I n this study, approximately 10 % of the total tests (i.e., 7 tests) have been randomly selected as the test data, and the remaining 6 8 tests have been considered for training data. Fig. 7 illustrates the results obtained from the training and testing of the first AN N to predict the nugget siz e. The results indicate that the AN N has been trained successfully, and the first AN N can predict the nugget siz e very well. Table 5 displays the comparison between the results predicted from the first AN N and the results obtained from the experimental test. 6 .5 where P is the real value of each parameter, P is the n normaliz ed value, P min and P are the minimum and max maximum values respectively. Eq. (2) also has been used to de-normaliz e the results obtained from the model. 6 .0 Predicted nugget diameter [ mm] 5 .5 5 .0 4 .5 4 .0 Pn °1 P ˜.P . (2) n min ° max min According to the DO E results, the electrical current is the most effective parameter on the nugget siz e, and the welding time has the most influential impact on the residual stress. Although the electrode force has almost no effect on the nugget siz e, it affects the residual stress. To run the AN N s, the five levels have been considered for both electrical current and welding time and just three levels have been selected for the electrode force. A total of 75 sets of welding parameters have been chosen to run the AN N s. Table displays the level of the R SW parameters considered to run the AN N s. However, the nugget siz es have been measured experimentally; the maximum residual stresses have been obtained from the FE model [6] P P 3 .5 Measured nugget diameter [ mm] a) b) Fig. 7. The compression results of measured and predicted nugget diameter by the first ANN model a) train samples and b) test The results obtained from the second AN N model are almost similar to the first model. The results indicate that the second AN N model can predict the residual stress based on the R SW parameters with high accuracy. Fig. 8 presents the results of the training and testing of the second AN N model. Predicted residual stress [ MPa] 245 240 235 230 225 220 215 210 205 a) Measured residual stress [ MPa] b) Fig. 8. The compression results of measured and predicted residual stress by the second ANN model; a) train samples, and b) test 3.3 The Multi-Objective Genetic Algorithm The genetic algorithm (G A) is a repeat-based optimiz ation method and its principles are adapted from genetic science. I n the G A, a set of design variables are encoded by fixed-length or variable-length strings, which the biological systems refer to them as chromosomes or individuals. G A is based on natural and biological science, and it is widely used to solve optimiz ation problems in engineering. A non-dominated sorting genetic algorithm I I (N SG A I I ) has been developed to optimiz e the R SW parameters to obtain a set of desired values for maximiz ing the nugget siz e and minimiz ing the residual stress. Since the G A is the minimiz ing algorithm, Eq. (3) has been used as the fitness function to achieve the desired goal. MinM = aR – ßd, (3) where R is the residual stress, d is the nugget siz e, a and ß are the weight coefficients for the residual stress and the nugget siz e, respectively. Because in this study there is no priority between the nugget siz e and residual stress, both a and ß have been considered 12. Thus, the final fitness function is as follows: M inM = 1/2 R – 1/2 d. (4 ) The flowchart of the developed multi-objective AN N -AN N -G A algorithm is presented in Fig. 10. The initial population siz e was 100 and was the same for each generation. According to this presented optimiz ation algorithm, the nugget siz e and the residual stress were predicted by the AN N s. A different set of R SW parameters were born in each generation, and the nugget siz e and residual stress were predicted by AN N s inside of the integrated optimiz ation algorithm. A two-point crossover rate of 0.5 and a uniform mutation probability of 0.05 were considered for the G A. I n addition, 300 generations were chosen as the maximum generation and the condition for ending the algorithm. Fig. 1 1 displays the results of running the integrated optimiz ation algorithm. The optimiz ed R SW parameters are displayed in Fig. 12. Since all the variables and outputs have been normaliz ed between 1 and 2, the normaliz ed parameters have been used in both AN N s and multi-objective G A. Thus, the optimiz ed R SW parameters obtained from the proposed optimiz ation algorithm are between 1 and 2. The real values of optimiz ed R SW parameters are presented in Table 5. Table 5. The optimized RSW parameters Welding current [kA] 12 Welding parameters Welding time [cycles] 16 Electrode force [N] 1130 Measured [mm] 4.74 Nugget size Predicted [mm] 4.77 Error [%] 0.6 Maximum residual stress Measured [MPa] Predicted [MPa] 213 207 Error [%] 2.8 a) b) Fig. 11. The results of the optimization algorithm, a) the best fitness value, b) average distance between individuals n order to evaluate the accuracy of the proposed multi-objective G A, a sample was welded based on the optimiz ed R SW parameters. The nugget siz e and the residual stress were measured experimentally and were compared with the predicted one by the integrated optimiz ation algorithm. Table 5 presents the results of this comparison. The results indicate that the integrated AN N -AN N -G A presented in this study can predict the nugget siz e and residual stress with high accuracy, and the optimum R SW parameters lead to high strength and good joint quality. 4 CONCLUSIONS I n this study, the R SW parameters of the electric current intensity, welding time, and electrode force have been optimiz ed to achieve the largest nugget along with the lowest tensile residual stress in the R SW of the magnesium alloy AZ 61. The full factorial DO E has been employed to investigate the effects of the R SW parameters on the nugget and the residual stress. The results of the DO E have been used to develop two separated AN N models. The AN N models have been utiliz ed to predict the dimensions of the nugget and the maximum tensile residual stress in the welded z one. The results display that the proposed AN N s have a high accuracy in predicting the dimensions of the nugget and the residual stress. Finally, an integrated multi-objective AN N -AN N -G A has been developed to optimiz e the R SW parameters. The results show that the presented optimiz ation model can be used very well to optimiz e the R SW parameters. 5 REFERENCES [1] Danesh Babu, S.D, Sevvel, P., Senthil Kumar, R., Vijayan, V., Subramani, J. (2021). Development of thermo mechanical model for prediction of temperature diffusion in different FSW tool pin geometries during joining of AZ80A Mg alloys. 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Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, 493-505 Received for review: 2022-03-31 © 2022 The Authors. CC BY 4.0 Int. Licensee: SV-JME Received revised form: 2022-05-30 DOI:10.5545/sv-jme.2022.142 Original Scientific Paper Accepted for publication: 2022-06-01 Effect of D ual-stage Ageing and R R A Treatment on the Three-body A brasive We ar of the AW7075 A lloy * Marz ena M. Lachowicz Tadeusz Lenieski Maciej B. Lachoicz Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Poland The paper presents an analysis of the influence of the heat treatment state on the abrasive wear of the AW7075 aluminium alloy. To determine the hardening state, the material hardness was measured. It was found that hardness is not the only factor that influences this type of wear. For this reason, the influence of the emerging microstructure is also analysed in the considerations. After tribological tests, microscopic observations of surface features were carried out to determine the dominant mechanisms of surface damage. The results were extended by the hardness distribution carried out on the cross-section. There were no changes in hardness that could be related to either strain hardening or structural changes caused by friction. Keywords: aluminium alloys, AW7075, abrasive wear, heat treatment, hardness, microstructure Highlights • The hardness of the AW7075 alloy is not the only determinant of abrasive wear; with the microstructure of the tested alloy and the related heat treatment, the state also plays an important role in this respect. • The abrasive wear of the tested alloy can be ranked in the following order according to the heat treatment condition: dual ageing < RRA treatment < T6 state. • The wear features show a similar type of damage, regardless of the heat treatment state. Scratches, grooves, microcracks, and slight plastic deformation features be observed on the wear surface. • Decohesion developed mainly around grain boundaries and interfacial boundaries, which facilitates the loss of continuity with the matrix in the presence of coherent particles. Larger and incoherent precipitates in the matrix can act as an abrasive and increase the wear rate. • The presence of large particles of the primary phases, which do not dissolve at the stage of heat treatment, promotes their crushing and defragmentation during abrasive wear. • The surface hardness does not change due to the occurrence of mechanical effects resulting from friction. 0 INTRODUCTION There is relative movement between surfaces of components in some applications of aluminium alloys. Wear resistance then becomes an important property to consider. N umerous research studies show that heat treatment can have a significant impact on tribological wear. I n particular, the fragmentation of the microstructure components can significantly affect the obtained tribological parameters [1] to [3]. The presence of intermetallic phases in the microstructure offers a wide spectrum of possibilities for the strengthening of aluminium alloys. This group also includes the high-strength 7000 series alloys. Two treatments are used for this purpose: supersaturation and subsequent ageing. The sequence for ageing the 7000 series alloys is given as follows: solid solution (a) Guinier-Preston (GP) zones ¶ (Mgn2) (Mgn2) [4] and [5]. The typical hardness-ageing diagram for a heat-treatable aluminium alloy is shown in Fig. 1. G P z ones are formed during ageing at room temperature or the early stages of ageing. They are fully coherent with the matrix. The greatest hardening effect is achieved at the stage of separation of the intermediate phase, which is related to the change in the mechanism of the interaction of the precipitates with dislocations. This is a typical T6 state. The stresses that are needed to cut the particles by dislocation, as well as the stresses caused by the O rowan mechanism associated with the formation of a dislocation loop around these precipitates, obtain their maximum values. The material hardness drops significantly when there is a complete loss of the coherence of the precipitates. Ageing to the T6 state is associated with a continuous distribution of grain boundary precipitates (G BPs) [6] and [7]. A properly carried out heat treatment should end at the stage of forming the matrix of precipitates (MPs), which is partially coherent ith the intermediate phase . The T6 state is characteriz ed by high strength and hardness but is highly susceptible to stress corrosion cracking. When looking for greater resistance to this type of corrosion, dual-stage ageing (DA) and R etrogression and R e-Ageing (R R A) treatment are used [9] to [13]. The first stage of DA ageing is characteriz ed by a lower temperature when compared to conventional ageing, and it is responsible for the diffusion and homogeneous distribution of the G P z ones. The coarse-grained G P z ones and phases are formed during the second ageing and contribute to the peak hardness. MPs are coarser and partially incoherent ith phase hen compared to one- step ageing. This helps to reduce the hardness of the alloy [12] and [13]. Another solution is the multi­stage R R A heat treatment. R etrogression involves heating the alloy, which had earlier been hardened, at a temperature in the range of 200 C to 260 C for a short period (120 s), and then re-ageing the alloy to a condition typical for the T6 state. The use of the R R A treatment leads to the obtaining of a microstructure that is characteriz ed by the presence of fine-dispersed and coherent (Mgn2) MPs. They are characteristic of the T6 state. However, at the G BPs there are fragmented and discontinuous precipitations that are typical for T7 over-ageing. As a result, the grain boundary that is line blocked with continuous G BPs particles, as in the T6 state, is transformed into a state in hich the precipitates of the phase are coarse and discontinuous [9], [14], and [15]. After the R R A treatment, a larger fraction of the G BPs was observed [7]. Also, the copper content of G BPs increases with the time of heat treatment [6]. Fig. 1. Schematic illustration of the precipitate strengthening contributions as a function aging time (based on [8]) The effect of heat treatment of aluminium alloys on their strength is already known. I ts influence on the resistance to structural corrosion is also well understood [12] to [16]. R etrogression and re-ageing treatment improve the resistance to stress corrosion cracking (SCC) [6], while maintaining high strength, until the MPs become coarse [6]. However, the microstructure changes caused by heat treatment affect other functional properties of aluminium alloys. The high strength is maintained as long as the MPs are not coarse [6]. The R R A state is characteriz ed by high resistance to fatigue crack initiation and better impact toughness as a result of the increased discretion of the precipitates occurring at the grain boundaries [9], [17] and [18]. Coarse G BPs also increase electrical conductivity [9]. The DA state, in terms of microstructure, brings the alloy closer to the over-ageing condition, which in turn results in a reduction in strength and an increase in ductility [19]. I t seems obvious that the different hardnesses obtained for individual states should also affect the tribological wear. For this reason, in the present study, it was decided to consider the influence of microstructure on the abrasive wear of the AW 7075 a luminium alloy. 1 MATERIAL AND METHODS The tests were carried out on the AW 7075 aluminium alloy. The chemical composition of the alloy, which was determined by G DS-500A Leco glow discharge optical spectrometry (G D O ES), is shown in Table 1. I n the microstructure of all the tested samples, (Al) solid solution as observed ith grey, large precipitates of the -AlFeMnSi phase, and dark primary precipitates of the Mg2Si phase (Fig. 2). The type of these particles was determined on the basis of the EDS results conducted as part of the preliminary studies and compared with the literature data. The grains of the solid solution were heterogeneous in nature and were surrounded by large precipitates of the iron-rich phase. The main changes in the microstructure, which were caused by the applied heat treatment, concern the morphology, siz e, quantity, and coherence of the formed precipitates. For this reason, the microstructure of the material in the image of the light microscope was of a similar nature. These changes are subtle and can, therefore, only be observed with the use of transmission electron microscopy (TEM) methods. However, it can be seen that in the case of the DA state, the precipitations of the strengthening phases are more clearly visible, which indicates their larger dimensions. Table 1. Chemical composition of the tested AW7075 aluminium alloy Element Zn Mg Cu Fe Cr Si Mn Ti Al Content [%] 5.42 2.34 1.45 0.39 0.26 0.12 0.10 0.03 rest 494 Lachowicz, M.M. - Lesniewski, T. - Lachowicz, M.B. Fig. 2. Microstructure after; a) T6, b) DA, and c) RRA, light microscopy, etched with 10 % HF Fig. 3. Flow chart for the heat treatment process; a) T6, b) DA, and c) RRA The parameters of three various heat treatments were developed for 30 mm 100 mm sections with a thickness of 1 0 mm that were cut from the tested alloy (Fig. 3) . The microstructure was investigated on conventionally prepared metallographic microsections using a Leica DM6000M light microscope. The tests were carried out before and after etching with a 10 % aqueous solution of HF. To determine the material hardening, BHN hardness measurements were carried out using the Brinell method and a DuraJet G 5 hardness tester (Struers). To determine the abrasive wear resistance, tests were carried out on the T-07 tester made at the I nstitute of Sustainable Technology in R adom (Poland). The tribological tests were performed in the presence of the loose F90 electro-corundum abrasive, and all the tested samples were subjected to the same friction conditions. The used abrasive reflects the penetration of aluminium oxide or anodic coatings into the friction area very well. The oxide film is thin and can break off easily, in turn producing wear debris particles. The removal of the protective layer also accelerates the corrosive effects [20]. The method complied with the requirements of the G O ST 23.20 8-79 s tandard [21]. The tested system consisted of a sample (plate) made of the tested material, and a counter-sample (roll) with a rubber ring. During the test, the material sample was pressed with a defined force of (F ) to a N rubber disk with a diameter of d 50 mm, hich as rotating at a constant speed (n ). G ravity was used to deliver a loose abrasive between the rotating disc and the fixed sample. I n the presence of loose abrasive, the sample of the tested materials and the reference sample were subjected to abrasive wear under the used operating conditions, i.e., rotational speed n 60 rpm/min, test time t, and FN loads in accordance with the above standard (t 10 min, F 44 N). The reference sample was grade C45 normaliz ed steel. N ext, the mass loss of the reference sample (Z ) wwand the mass loss of the tested materials (Z wb ) were determined. The mass loss of the samples (weight difference before and after the tests) was determined after a defined test time (determined by the number of rotations of the rubber roller). Based on the mass loss measurements, the abrasive wear resistance index K (relative wear resistance) was calculated from the b following equation (Eq. (1) ): Z °.°N wwb b Kb ˜, (1) Zwb °.w °Nw where Z is the mass loss of the reference material ww (C45 steel), Z the mass loss of the tested material, wb .w the density of the reference material, . the density b of the tested material, N the number of revolutions w of the reference material’ s friction path, and N the b number of revolutions of the tested material’ s friction path. The density of the tested material (AW 7075) was 2.81 g/ cm . The morphology of the specimens after the tribological tests was observed using scanning electron microscopy (SEM), which also identified the wear features. The Phenom World ProX microscope was used for this purpose. Backscattered electrons (BSE) and second electrons (SE) detectors with an accelerating voltage of 15 kV were used. 2 RESULTS AND DISCUSSION 2.1 Hardness Measurements Based on the performed measurements, it can be stated that the proposed heat treatment contributed to the material strengthening (Fig. 4) . I t was found that the Brinell hardness (BHN ) of the AW7075 alloy increases in the following order: DA< T6< R R A. The highest hardness of the AW7075 alloy was obtained after the R R A heat treatment, while the alloy that was heat treated to the T6 state had a slightly lower hardness. The use of double-stage ageing adversely affected the alloy strengthening, with the hardness after this process being the lowest. Fig. 4. Results of hardness measurements of the AW 7075 alloy after various heat treatments 2.2 Abrasive Wear The AW 7075 aluminium alloy, with different levels of hardness obtained by heat treatment, was tested. Figs. 5 and 6 present the three-body dry abrasion of the AW 7075 alloy, which was determined as the weight loss for its heat-treated state. The results of the hardness and abrasive wear measurements can be summariz ed as follows: the abrasive wear kinetics of the T6 state were lower than for the DA and R R A states, the DA and R R A states, despite having different hardness values, had a comparable wear resistance, the hardest sample (R R A state) had worse wear resistance than the one with lower hardness (T6 state). Fig. 5. Mass loss (Z wb ) results obtained for the AW 7075 alloy after various heat treatments Fig. 6. Kb factor obtained for the AW 7075 alloy after various heat treatments Linear wear low theory (also called Archard’ s equation) indicates the relationship between the hardness of the material and its abrasive wear resistance. I n the case of the alloys in the DA state with the lowest hardness, the greatest weight loss, and thus the lowest wear resistance, was observed. However, in the remaining cases, this relationship did not work. O ther authors also note that the correlation between hardness and wear resistance is not always Fig. 7. General views of the wear features after the different heat treatments; a) T6, b) DA, and c) RRA, SEM clear [22] to [24]. However, Archard did not consider material. From the point of view of the microstructure, the role of the microstructure as one of the key factors aluminium alloys can be considered as “ composites” in abrasive wear. that consist of a soft matrix and hard precipitates The conducted research shows that the hardness formed during the heat treatment stage, which in turn of the AW 7075 alloy is not the only factor that affect the hardness and strength of these alloys. The determines its wear. N o linear relationship was presence of hard particles in the matrix effectively observed between the hardness of the material and reduces wear [25] and [26]. Microstructural parameters its wear; therefore, it can be concluded that the (e.g., the hardness, shape, siz e, volume fraction, and wear is also determined by the microstructure of the distribution of the second phases), the properties of the matrix, and the interfacial bonding between the second phase and the matrix significantly influence the abrasive wear resistance [27]. Even a subtle change in the siz e and distribution of these precipitates can significantly affect the AW707 5 alloy’ s operational properties. I t is not difficult to observe that the wear was lower in the states in which the microstructure mainly shows significant precipitation that is coherent with the matrix (T6 state). Literature data clearly indicate that in the T6 condition, G BPs are mainly continuous and coherent particles [6] and [7]. The hardening peak caused by the presence of coherent phases is also confirmed by hardness measurements (Fig. 4) . During micro-ploughing, the metallic material is mainly elastically-plastically deformed, and it flows around and beneath the sliding particle [27]. I n an ideal case, micro-ploughing, due to a single pass of one abrasive particle, does not result in any detachment of material from the wearing surface. A prow is formed ahead of the abrading particle, and the material is continuously displaced sideways to form ridges adjacent to the produced groove. As shown in Fig. 1, the particles coherent with the matrix will be sheared in accordance with the Friedel effect. This is conducive to maintaining the continuity of the matrix as well as the precipitations. Consequently, these particles are more difficult to detach from the matrix. I n this situation, the wear will be mainly caused by foreign abrasive particles that are involved in the abrasion, which contributes to reduced consumption and higher K ratios. For both the R R A treatment and b the T6 state, the particles that are partially coherent with the matrix constitute a significant contribution to the microstructure. The high degree of strengthening after R R A treatment is confirmed by high hardness (Fig. 4) . However, after R R A treatment, the MPs are similar to those occurring in the T6 state [6], [7], [9], [14], and [15]. The grain boundaries are close to the over-ageing state. The G BPs consist of incoherent, discontinuous, and coarse precipitations [6], [7], [9], [14], [15], and [19]. I n a situation in which a significant amount of precipitation is incoherent with the matrix, their presence in the microstructure may contribute to the decohesion of the material. However, it has been proved that a too high concentration of MPs deteriorates the resistance to stress corrosion cracking [6]. Material may be ploughed aside repeatedly by displacing particles, which may then detach due to micro-fatigue. The precipitations torn out in this Fig. 9. a) Exemplary SEM 3D-profilometry image, and b) surface texture of the wear tracks after the T6 heat treatment a) DA, SEM image, b) DA, SEM 3D-profilometry image, c) RRA, SEM image, and d) RRA, SEM 3D-profilometry image way, while moving in the mass of the material, may 2.3 Wear Surface contribute to increased wear. Volume loss may occur as a result of the action of many abrasive particles. To understand the reason for the different wear mechanisms better and to study the influence of matrix hardness on the wear performance, the morphology of the wear track was examined using SEM analysis. The analyses of the wear paths revealed the same type of damage in all the tested alloy states (Fig. 7) , with the wear being abrasive. As shown in the images obtained at higher magnifications: grooves and scratches, microcracks, and plastic deformation can be easily observed on the surface of the wear tracks (Figs. 8 to 13) . The resulting surface irregularities ranged from 4 m to 6 m, regardless of the heat treatment condition (Figs. 9, 1 1 and 1 3) . The main wear mechanisms are therefore controlled by wedge formation and micro-ploughing (Figs. 14 and 15) . However, this causes a large amount of ploughed material to embed into the matrix at the edge of the wear mark, which makes a significant contribution to material fatigue. Moreover, the abrasive material cuts the surface of the matrix. The grooves and scratches that are formed are not always parallel to the direction of friction, which indicates the displacement of the friction particles in the wear area (Fig. 7) . The precipitations can increase hardness, but at the same time enhance the wear rate by causing disruption of plastic flow during particle impact. The larger ones can also act as an abrasive and, in turn, increase the wear rate during abrasion. 2.4 Subsurface Wear Morphology of the Samples and Microhardness Measurements O bservations of the wear surface carried out on the cross-section confirm the presented thesis (Figs. 16 to 20). I n the case of the DA state, more even wear was observed but, at the same time, it was often accompanied by delamination, which in turn contributed to the removal of larger fragments of the wear material (Figs. 18 and 19) . I t is unlikely that the fragments observed in the microscopic image came from surface micro-cutting, as this mechanism was not observed on the surface in the SEM investigations. This undoubtedly contributed to the greater wear observed during the tribological tests. As indicated earlier, the key factor was the microstructure. O bservations on the perpendicular cross-section of the samples showed that decohesion developed mainly in the area of the grain boundaries and interfacial boundaries (Figs. 16b, 18b and 20c). The loss of continuity with the matrix is much easier in the case of non-coherent particles than in the presence of coherent precipitations. The tendency for intergranular crack growth is an effect of planar slip band development results from the repeated shearing of precipitates by dislocation motion [28]. a) b) c) d) a) and b) perpendicular, and c) and d) and parallel to the sliding direction; Light microscopy, etched with 10 % HF I n the T6 state, which is formed mainly by coherent precipitations [4] and [29], changes typical for surface scratching and micro-ploughing were observed (Figs. 16 and 17) . Although changes in the direction of the features that formed on the surface of the samples were observed, the greatest changes in the cross-section occurred in the direction perpendicular to the sliding (Figs. 16a and b). The nature of the subsurface wear morphology observed in the R R A state was similar to those in the T6 state (Fig. 20). R egardless of the heat treatment states, microstructure evolution caused by plastic deformation was not observed. Small effects of plastic deformation were observed in the places where the abrasive was pressed into the surface of the samples, which led to the formation of characteristic tear-shaped cavities (Figs. 16d and 19b) . I n all the samples, it was also observed that the presence of the -AlFeMnSi particles in the subsurface area leads to a) parallel to the sliding direction, and b) perpendicular to the sliding direction, SEM, etched with 10 % HF a) and b) perpendicular, and c) and d) parallel to the sliding direction; Light microscopy, etched with 10 % HF Lachowicz, M.M. - Lesniewski, T. - Lachowicz, M.B. a) and b) perpendicular, and c) and d) parallel to the sliding direction; light microscopy, etched with 10 % HF its defragmentation and crushing. This also promotes plastic deformation; and the fact that increasing the its penetration into the friction area (Figs. 16b and c, temperature during friction may result in a partial 17, 18a , and 20). disappearance and growth of the precipitation The microhardness measurements are strengthening phases. The performed studies indicate consistent with the macrohardness measurements. that none of these effects occurred. The hardness The microhardness can be ranked in the following fluctuated due to the microstructural heterogeneity. increasing order: DA < T6 < R R A. Two effects can However, no tendency to increase or decrease the be expected as a result of the friction: an increase in hardness in the near-surface area, which would hardness directly at the surface was observed. The indicate the occurrence of hardening caused by results are shown in Fig. 21. The dashed lines are responsible for the actual hardness distributions, while the solid line is an approximation. 3 CONCLUSIONS The results of the hardness measurement and microscopic examinations, and the underlying reasons for the observed behaviour, can be summariz ed as follows: 1. The hardness of the AW7075 alloy is not the only determinant of abrasive wear. The conducted research shows that the microstructure of the tested alloy and the related heat treatment state also play an important role in this respect. The factor that favours the high value of the K b coefficient is its high hardness, which is caused by the presence of phases that are coherent with the matrix. This parameter increases in the following order: DA < R R A < T6. 2. The analyses of the wear paths showed the same type of damage in all the tested alloy states. The scratches, grooves, microcracks, and slight features of plastic deformation can be observed on the wear surface. The main wear mechanisms are therefore controlled by wedge formation and micro-ploughing. The delamination tendency may also have contributed to the increased wear of the DA condition, as delamination was observed in this condition. This is most likely related to the fact that this state has the lowest hardness. 3. The incoherent precipitation can increase hardness, as well as the wear rate, by disturbing the plastic flow during particle impact. Larger particles can also act as an abrasive and increase the wear rate during abrasion. O bservations on the perpendicular cross-section of the samples showed that decohesion developed mainly around the grain boundaries and interfacial boundaries. The loss of continuity with the matrix is much easier in their case than in the presence of coherent particles. 4. The presence of large precipitates of the primary phases, which do not dissolve at the stage of heat treatment, favours their crushing and defragmentation during abrasive wear. This promotes their penetration into the friction area. 5. N o tendency of an increase or decrease of the hardness directly at the surface was observed. An increase in hardness in the near-surface area could be expected, which would indicate the occurrence of hardening due to plastic deformation. However, an increase in temperature during wear could cause a partial disappearance and growth of the precipitation strengthening phases, which would result in a decrease in surface hardness. 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Licensee: SV-JME Received revised form: 2022-07-08 DOI:10.5545/sv-jme.2022.30 Original Scientific Paper Accepted for publication: 2022-07-11 Nitriding H S6-5-2 Steel in Inductively C oupled Plasma Marek Binienda1 – R obert Pietrasik2, – Sylester Pata2 – K rz ysz tof Matcz ak1 – Witold Krotewicz 1 Z emat Technology G roup, Poland 2 Lodz University of Technology, I nstitute of Materials Science and Engineering, Poland This article presents research on the possibility of obtaining a hardened surface layer via nitriding in coupled plasma (ICP) for HS6-5-2 steel. The subject of the investigation was the influence of the process parameters on the properties of the obtained layers. The surface layers were characterized using an optical microscope, SEM (Scanning Electron Microscope), EDS (Energy Dispersive Spectroscopy), XRD (X-Ray Diffraction), and a microhardness tester. The generator power was changed gradually from 500 W to 2 kW and the tests were carried out for various process durations, from 15 to 45 minutes at a set pressure. The obtained results show the possibility of obtaining nitrided surface layers with a thickness of up to 0.1 mm and a significant increase in hardness in a very short time. Keywords: plasma, nitriding, surface layer, hardness Highlights • The maximum hardness of about 1100 HV was obtained: an increase in hardness by 350 % in relation to the starting material. • Nitrided layers with a thickness of 100 ”m were obtained following a very short process: 45 minutes. • The influence of process parameters on the properties of the nitrided layers is shown. • The nucleation and growth mechanism of the nitrided layers obtained by this method is described. 0 INTRODUCTION The constant development of technology means that there is a need to optimiz e the functional properties of materials used in the production of tools and machine parts. O n one hand, this process can be achieved by producing tool materials with better properties, which requires the use of expensive alloying additives in a multi-stage technological process [1] and [2]. O n the other hand, research to modify the surface layer to obtain new, more favourable functional features of ready-made tools is being carried out. Despite significant progress in the development of surface engineering, methods for increasing the durability and reliability of tools and structural elements, especially those of small dimensions, still cause problems [3] and [4]. O ne of the most frequently used technologies, especially for small dimension elements, is nitriding [5] to [7]. N itriding done by the classical thermo- chemical treatment method leads to (Fe2-3 N) and ¶ (Fe4N ) [8] to [10] brittle layer formation. I n the case of gaseous-controlled processes, it is possible to control the phase composition of the layers, but the processes take a relatively long time, even for thin layers [11]. Plasma-assisted nitriding is presented in the literature on the subject primarily concerning ionic discharge, which is the phenomenon of accelerating particles in an electric field. The high kinetic energy of ions is created as a result of the potential difference between the electrodes, both in the glow discharge of direct current and in the high-frequency electric field. I n the first case, the existence of strong field strength is obvious and directly dependent on the potential difference applied to the electrodes. I n high-frequency plasma discharge, the discharge is obtained between opposite electrodes as a result of applying a high-energy and high-frequency signal from a generator to them. Such plasma is called “ capacitively coupled plasma” (CCP). The generator can be connected by means of electrodes directly to the discharge area or by galvanic isolation of one of the electrodes using a capacitor or an insulator. The disadvantage of the direct variant of connecting the linings with the discharge is the possibility of contamination of the treatment atmosphere with matter from the electrodes due to their contact with the plasma. I n the case of isolating one of the electrodes, due to the different masses and the related mobility of ions and electrons, the high frequency of electrode polariz ation changes means that heavy ions cannot keep up with the changes in the electric field. As a result, a constant, non-discharged charge accumulates on one of the electrodes, causing the electrode to be polariz ed with a constant voltage. This phenomenon is called “ autopolariz ation” , and its consequence is the creation of a strong, directed electric field, which accelerates the ions, by giving them high kinetic energy, causing the spraying of the processed samples. This is the main reason that this method of plasma production cannot be used to nitride objects while keeping their surface and edges intact. *Corr. Author’s Address: Lodz University of Technology, Institute of Materials Science and Engineering, 1/15 Stefanowski Street,90-924 Lodz, Poland, robert.pietrasik@p.lodz.pl Another disadvantageous effect of the directed electric field is the shadow phenomenon, which makes it necessary to change the position of the workpieces during the process [12]. I t should be emphasiz ed, however, that CCP plasma is used in numerous industrial applications in which high ion energy is useful, e.g., ion etching, surface cleaning, or expanding. The use of inductively coupled plasma obtained in a strong magnetic field due to the flow of Foucault currents eliminates the occurrence of an accelerating electric field. The magnetic field of the solenoid causes the flow of eddy currents both in the gas region and in the workpiece, which simultaneously fulfil two tasks: they resistively heat both the gas (nitrogen) creating a plasma ring discharge and the workpieces to the penetration depth, where the value depends on the resistivity of both the ioniz ed gas and the sample and frequency. Multiple ioniz ation of particles in a low-temperature non-isothermal plasma [13] makes it an effective source of the nitriding agent and can be used for diffusive saturation of metals. However, the use of such an induced plasma for steel nitriding is practically unknown, as single works on a laboratory scale [14] have only been recogniz ed. I n contrast, inductively coupled plasma is widely used for the physical deposition of various types of coatings [15]. A proprietary stand for nitriding in high-frequency plasma was designed and built to perform the tests (Fig. 1) . The device consists of a high-frequency generator set with an inductor, which contains a reactor inside. The set of vacuum pumps allows the appropriate vacuum to be obtained. N itrogen with a purity of 99.999 % is taken from a cylinder via the mass flow controller. Fig. 1. Block diagram of the device for Inductively Coupled Plasma As part of this work, the HS6-5-2 steel was subjected to tests. Cutting tools made of this steel, including the drills, taps, and reamers most commonly used in industry and households, constitute a specific group: they are exposed to work in very difficult conditions. Practice shows that small-siz e tools are not sharpened but replaced with new ones [16]. Therefore, the modification of the surface by nitriding in inductively coupled plasma, leading to a numerous increase in their durability while maintaining high core impact strength, is economically justified. 1 EXPERIMENTAL PROCEDURE The samples used for the tests were HS6-5-2 steel bars with a diameter of 4 mm, a length of 50 mm with the composition in accordance with the standard shown in Table 1. The samples were in the raw steel state (without heat treatment). Table 1. Standardized chemical composition [wt. %] of HS6-5-2 steel C 0.80 to 0.88 Cr 3.80 to 4.50 Mo 4.70 to 5.20 V 1.70 to 2.10 W 5.90 to 6.70 Si Max 0.45 The samples were nitrided in a stand built for nitriding in inductively coupled plasma discharge with a frequency from a band intended for industrial, scientific, and medical (I SM) applications, in a continuous operation mode. The device was made of a reactor in the form of a quartz tube, 750 mm long and 100 mm in diameter, and was connected to a set of vacuum pumps, which included a turbomolecular pump and a scroll pump. The operating pressure of the process under a nitrogen atmosphere of 99.9999 % purity was 100 Pa, and its flow was controlled by a mass flow controller (MFC). The plasma discharge took place within a coil made of a copper pipe with a diameter of 8 mm and was powered by a generator with a frequency of 27.12 MHz . The power was changed in steps ranging between 500 W, 1 kW, 1.5 kW, and 2 kW. The samples placed in quartz glass process tables were nitrided at constant pressure and changed the duration of the process (15 min, 30 min, 45 m in) for the set generator power. The cross-section microstructures of specimens were observed using a N ikon MA200 optical microscope (N ikon I nstech Co., Ltd., Tokyo Japan). The microstructure and chemical composition of the surface layers were also investigated by using a scanning electron microscope (SEM) JEO L JSM­6610 LV (JEO L Ltd., Tokyo Japan) equipped with an energy dispersion spectroscope (EDS) X -MAX 80 O xford I nstruments (O xford I nstruments G roup, Abingdon, United Kingdom). The X -ray diffraction (X R D) was done on a device from PAN alytical Empyrean (Malvern Panalytical Ltd, Malvern, United Kingdom). The source was an x-ray tube with cobalt anode-emitting characteristic radiation (CoK 1.74 ). Primary beam optic consisted of Goebel mirror for Co radiation, fixed divergence slit 0.5 deg, Soller slit 0.04 rad, and mask 10 mm. Diffracted beam optic consisted of parallel plate collimator 0.18 deg, Soller slits 0.04 rad and proportional X e detector. The hardness distribution of the nitrided layers was measured using a Vickers microhardness tester N EX US 4305 (I N N O VATEST Ltd., Maastricht, N etherlands). The surface hardness on the sample prepared for metallographic tests was measured at a distance of 10 m from the edge of the sample and successively further inside the sample every 5 m. Measurements were made with 0.98 N load. The surface roughness profile parameters were tested with the T8000 R C profilometer by Hommel-Etamic. Parameter Ra arithmetic mean of the profile ordinates, was determined in accordance with the PN -EN I SO 4287: 1999 s tandard. Time SEM image EDS nitrogen distribution 15 min 30 min 45 min. Fig. 2. Images of the SEM structures and the corresponding EDS nitrogen distributions obtained at a generator power of 500 W for different process times. 2 RESULTS AND DISCUSSION As a result of the processes carried out at a generator power of 500 W, z ones of nitride compounds on the surface were only obtained without an internal nitriding z one, regardless of time. I mages of the SEM structures and the corresponding EDS nitrogen distribution distributions are shown in Fig. 2. With a generator power of 500 W (Fig. 2), only the rudiments of the layer can be observed in the form of a white z one of nitride compounds: initially composed of ¶ nitrides, and after longer dosing of nitrogen, transforming into nitrides. In this case, the internal nitriding z one was not obtained probably because of the low temperature of the samples, which was not sufficient to dissolve the nitrides and diffuse nitrogen into the samples. I n the case of the shortest a) time (15 min), the nitrogen content in the nitride z one was about 6 % by weight, which proves that it is mainly .’ nitride (Fe4 N ). I f the process is prolonged to 30 min, the nitrogen content increases, on average, to a level of about 10 % by weight. This value and the fact that the content exceeds 8 % prove that we are dealing ith nitride (Fe2-3 N ). Analogically, for a time of 45 min, the average nitrogen content is about 12 % by weight, so we are dealing with slightly more saturated nitrogen, specifically the nitride e (Fe2-3 N ). These observations are consistent with the X -ray diffraction test (Fig. 3) , where the spectra for the samples after 15 min and 45 min nitriding processes are presented. In the first case, the ¶ (Fe4 N ) nitrides are visible only. I n the case of the longer process (45 b) Fig 3. XRD spectra for nitrided samples at 500 W generator power, during a) 15 min and b) 45 min min), the stress of nitrides e (Fe3 N) and residuals of (Fe4 N ) are visible, respectively. This may prove that the process of constituting nitrided layers takes place through the nucleation of ¶ nitrides, hich (together ith a longer nitrogen supply) transform into nitride. Hoever, ith the indicated generator power, the obtained substrate temperature is too low and does not allow nitrogen diffusion deeper into the samples, as evidenced by the absence of an internal nitriding z one, and is confirmed by the lack of increase in the hardness of the sample directly under the nitride layer (the hardness at a depth of 10 m is about 300 HV). I n contrast, surface hardness ranges from 60 HV, in the case of nitride on the surface, to 700 HV for . The processes carried out using higher generator powers allowed diffusion layers of various uniformity and thickness, as well as structural formation, to be obtained. The summary of the obtained structures is shown in Fig. 4. The analysis of the photos shows that there is a clear correlation between the parameters of the process and the thickness and structure of the obtained layers. I ncreasing the generator power to 1 kW results in the appearance of the beginnings of the diffusion z one with a very irregular depth. A longer process time results in an increase in nitrogen saturation, but the layers are highly heterogeneous. At 1.5 kW, the diffusion layer is clearly visible but is not uniform and has an island structure, especially for shorter process times. I t is clearly visible at shorter process times (e.g., for 15 min, the depth of the diffusion z one ranges from 26 m to 42 m, but a white z one of nitride compounds appears on the surface above the areas of the thicker z one of internal nitriding). I ncreasing the time to 45 min makes the thickness uniform; however, the nitride compounds were not diffused. The use of a 2 kW generator results in even layers with a constant thickness after a 15 min process. However, an undiffused z one of nitride compounds is visible. O nly Generator Process time power 15 min 30 min 45 min Fig. 4. Summary of metallographic structures obtained for different generator powers and process times Binienda, M. – Pietrasik, R. – Paweta, S. – Matczak, K. – Krotewicz, W. extending the duration of the process clearly results in increasing the depth of nitrogen diffusion into the steel structure and in obtaining layers with only the internal nitriding z one, without a z one of nitride compounds on the surface (white z one). The results of X R D studies are the confirmation of the above-described phenomenon and the model of nucleation and growth of nitrided layers in inductively coupled plasma. Fig. 5 shows X R D spectrum, which was made for sample processed in the parameters considered optimal: 2 kW generator power, for 45 min. I t shows reflections from the Fe phase: ferrite, and nitrides, Fe4 N and CrN . O f course, there are also visible carbide phases, e.g., of the Fe3 W3 C type, which are typical for this type of steel. The reflex at 52 deg is slightly shifted to the left (compressive stresses) and slightly widened, which indicates the existence of a solid nitrogen solution gradient in Fe and, therefore, the presence of the diffusion z one in the structure. Fig. 6 presents a list of optical images of the surface appearance of the initial samples, after the process in which the nitride compounds z one was obtained (P 500 , t 45 min.), and after the diffusion of the nitride compounds z one (P 2 k, t 45 min.). For the initial samples, the surface roughness parameter Ra was 0.58 m. I n the case of nitrided samples with a z one of nitride compounds, the sample changes to dull grey (Fig. 6) , which is related to the presence of e nitride on the surface and is consistent with the Ra 0.87 m roughness measurement results. However, in the case of surfaces from which the nitride layers have been diffused and in the structure, we only observe a diffusion z one, the colour changes to a darker one, and the appearance is less dull (Fig. 6) . The reduction of roughness after the diffusion of the nitrides is also visible in the results of measurements of the Ra 0.6 m parameter. a) b) c) Fig. 6. Summary of the surface appearance of samples in different technological conditions; a) the surface appearance of the initial sample before the nitriding process, b) the appearance of the sample surface after nitriding with the zone of nitride compounds, and c) the appearance of the sample surface after nitriding and after the zone of nitride compounds diffused To determine the effective thickness of the obtained surface layers, hardness distributions were made as a function of the distance from the edge of the sample. Due to the unevenness of the layers, especially for lower generator power, five hardness distributions were made. The average results, compiled separately for each of the generator powers for the tested process time lengths, are shown in Figs. 7 to 9. I t should be emphasiz ed that high hardness values were obtained despite the core not being hardened. The maximum hardness of the samples exceeds 1 100 HV, with an initial (core) hardness of about 300 HV, which translates into a 360 % increase in hardness. There is also a general tendency of increasing maximum hardness with increasing generator power and process time. Fig 5. XRD spectrum for nitrided sample at 2 kW generator power, 45 min Fig. 9. Comparison of microhardness distribution of surface layers obtained with a 2 kW generator power, for different process times Based on the hardness distributions made for a power of 1 kW, 1.5 kW, and 2 kW, the effective thicknesses of individual layers were determined in accordance with DI N 50190-3 (criterion 5 0 HV above the core hardness), while for the generator power of 500 W, the layer thickness was determined metallographically. Table 2 shows the thickness of the obtained layers as a function of generator power and process duration. When analysing the obtained layer thicknesses, it can be observed that, in line with theoretical predictions, the layer thicknesses increase along with generator power and with the extension of the process time. However, due to the thickness of the layers, their uniformity and phase structure, only the layers obtained with a generator power of 2 kW and process times of 30 min and 45 min are of practical importance for the application. I n these cases, uniform layers were obtained without the white z one and the precipitation of nitrides at the grain boundaries of the former austenite, thus the most desirable for potential applications for small cutting tools. I t should be emphasiz ed that the layers of usable thickness are obtained after a very short process (45 min). I f counting a complete pump-down cycle, this time is approximately 1.5 hours. Compared to gas nitriding methods, for which the full cycle of such thickness is about 9 hours, this is a very good result. Comparison of the ionic or plasma methods with other methods of induction provides the following conclusions: the time is similar, but the inductively coupled plasma allows to eliminate the edge dissolution phenomenon and avoid the shadow effect. Table 2. Summary of the thicknesses of the obtained layers as a function of generator power and process duration Generator Process time power 15 min 30 min 45 min 500 W 2.4 ”m 4.0 ”m 4.7 ”m 1 kW 13 ”m 47 ”m 59 ”m 1.5 kW 26 ”m 53 ”m 65 ”m 2 kW 68 ”m 87 ”m 107 ”m 3 CONCLUSIONS 1. I t is possible to obtain nitrided layers with the correct structure in inductively coupled plasma. I t is very important from a technological and economic point of view, i.e., a significant reduction of the process time with the possibility of full regulation of the structure of the layers, also without the z one of nitride compounds. 2. The possibility of nitriding in inductively coupled plasma on an industrial scale is also very important from an ecological point of view. The process uses inert nitrogen instead of toxic ammonia. I n the new technology, there are also no emissions that require the utiliz ation of post-process gases. Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, 506-513 3. For samples made of HS6-5-2 steel with a diameter of 4 mm, it is best to conduct the process with a generator power of 2 kW. 4. The maximum hardness obtained on the raw material is about 1 10 0 HV; hardness increases by 350 % in relation to the starting material. 5. Layers with functional properties of 100 m thickness are obtained in a very short process lasting 45 m in. 4 ACKNOWLEDGMENTS The work has been done under Measure 1.2— Sectoral R esearch & Development programs of “ Program O peracyjny I nteligentny R oz w ” 2014–2020 (Smart G rowth O perational Program 2014–2020) co-funded by the European R egional Development Fund. The project: “ Development of nitriding technology for machine parts and tools in inductively coupled plasma together with a device for its implementation.” Contract N umber: PO I R .01.01.01-00-0088/ 17. 5 REFERENCES [1] Pye, D. (2003). Practical Nitriding and Ferritic Nitrocarburizing. ASM International, Russell Township, DOI:10.31399/asm. tb.pnfn.9781627083508. [2] Bilger, P., Dulcy J., Gantois M., Torchane L. (1996). Control of iron nitride layers growth kinetics in the binary Fe-N system. Metallurgical and Materials Transactions: A, vol. 27A, p. 1823­1835, DOI:10.1007/BF02651932. [3] Sawicki, J., Siedlaczek P., Staszczyk A. (2018). Fatigue life predicting for nitrided steel - finite element analysis. Archives of Metallurgy and Materials, vol. 63 no. 2, p. 921-927, DOI:10.24425/122423. [4] Sawicki, J., Siedlaczek P., Staszczyk A. (2018). Finite-element analysis of residual stresses generated under nitriding process: a three-dimensional model. Metal Science and Heat Treatment, vol. 59, no. 11-12, p. 799-804, DOI:10.1007/ s11041-018-0229-y. [5] Pokorny, Z., Dobrocky, D., Kadlec, J., Studeny, Z. (2018). Influence of alloying elements on gas nitriding process of high-stressed machine parts of weapons. 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Nitriding HS6-5-2 Steel in Inductively Coupled Plasma Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8 Vsebina Vsebina Strojniški vestnik - Journal of Mechanical Engineering letnik 68, (2022), številka 7-8 L jubljana, julij-avgust 2022 ISSN 0039-2480 aa eeo R az širjeni povz etki (extended abstracts) Oguz Dogan: Kratkotrajno lezenje razlicnih polimerov za dodajalno izdelavo v razlicnih temperaturnih in obremenitvenih raz merah SI 61 Ragul Kumar Kittusamy, Velavan Rajagopal, Paul Gregory Felix: Priprava in termicna karakterizacija trdnih/kapljevitih organskih kompozitnih fazno spremenljivih snovi (PCM) na osnovi mašcobnih kislin, iz boljšanih z nanografenom, z a shranjevanje toplote SI 62 Prabhakaran Jayasankar, Jayabal Subbaian: Optimizacija ravni ogljikovega dioksida v petsedežnem voz ilu SI 63 Davood Afshari, Ali Ghaffari, uheir Barsum: Optimizacija postopka uporovnega tockovnega varjenja magnez ijeve z litine AZ 61 SI 64 Marzena M. Lachoicz, Tadeusz Lenieski, Maciej B. Lachoicz: Vpliv dvostopenjskega staranja in obdelave R R A na abraz ivno obrabo med tremi telesi pri z litini AW7075 SI 65 Marek Binienda, Robert Pietrasik, Sylester Pata, Krzysztof Matczak, itold Kroteicz: Nitridiranje jekla HS6-5-2 v induktivno sklopljeni plaz mi SI 66 Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, SI 61 Prejeto v recenzijo: 2022-05-08 © 2022 Avtorji. Prejeto popravljeno: 2022-06-22 Odobreno za objavo: 2022-08-05 ratotrao leee ralii oliero a dodaalo idelao ralii teeratri i oreeitei raeraK * O guz Dogan Univerza Kahramanmaras Sutcu Imam, Oddelek za strojništvo, Turcija Polimerni materiali za dodajalnoizdelavo so v pogojih stalnih obremenitev podvrženi signifikantnim spremembam dimenz ij. To lahko vpliva na varnost delovanja polimernih konstrukcij, iz delanih po dodajalnih postopkih in z ato obstaja potreba po opredelitvi lez enja polimerov, ki se uporabljajo pri dodajalni iz delavi. Temperatura je eden glavnih parametrov, ki vplivajo na lez enje polimerov. V dostopni literaturi pa je le malo študij, ki bi obravnavale vpliv temperature na lez enje preiz kušancev, iz delanih po postopku FDM. Pomanjkanje obstojecih raziskav je bilo tudi glavna motivacija za izvedbo pricujoce študije. Lez enje preiz kušancev, pripravljenih po postopku dodajalne iz delave (iz materialov PLA, ABS, TPLA, CPE, najlon, PC), je bilo eksperimentalno preizkušeno pri treh razlicnih temperaturah (25 C, 40 C in 60 C) in dveh stopnjah obremenitve (10 MPa in 20 MPa). Preiz kušanci so bili iz delani na 3D -tiskalniku Ultimaker 2+ Extended 3D printer in na CNC rezkalnem stroju, s cimer je bila zagotovljena homogena struktura. Eksperimenti so bili opravljeni na standardni napravi z a preiz kušanje lez enja. Merilnika na napravi merita temperaturo in raz tez ek preiz kušanca. Preiz kusi lez enja so bili opravljeni v skladu s standardom ASTM D2990-17 in so potekali v klimatiz irani sobi na miz i, ki je iz olirana proti vibracijam. Vsak preiz kus lez enja je trajal 3 ure (10.800 s), v tem casu pa je potekalo merjenje in beleženje raztezka zaradi lezenja z mikrometrom. Hitrost lez enja je pri vseh materialih rasla s temperaturo okolice in ravnjo napetosti. R ez ultati so pokaz ali, da ima obremenitev vecji vpliv na lezenje kot temperatura. PC je bil v vseh eksperimentalnih scenarijih najbolj obstojen proti lez enju. N ajslabšo obstojnost proti lez enju ima material PLA, ki se najpogosteje uporablja v 3D-tiskalnikih. a dele, natisnjene iz materiala PLA na 3D-tiskalnikih, je zato priporocljiva uporaba pri sobni temperaturi ter v odsotnosti obremenitev oz. pod zelo majhnimi staticnimi obremenitvami. Izdelava vsakega preizkušanca na 3D-tiskalniku in CNC-stroju traja približno 1,5 ure, preizkus lezenja pa nato traja še dodatne 3 ure. Pridobitev ene same krivulje lezenja torej traja v povprecju 4,5 ure. Izvedljivo število eksperimentov je zato omejeno in tudi ni bilo mogoce preiskati lezenja materialov, ki so manj razširjeni v dodajalni proiz vodnji. Poleg tega so nekateri materiali zelo elasticni in zanje ni bilo mogoce dolociti krivulj lezenja s to napravo (npr. TPU in PP). Pregled literature je pokazal pomanjkanje študij lezenja raznih natisnjenih polimernih izdelkov pri razlicnih temperaturah in obremenitvah. lanek bo zato zanimiv za bralce, ki se ukvarjajo z dodajalno izdelavo, 3D-tiskalniki ali karakteriz acijo polimerov. le eede dodaala idelaa reii leea olieri ateriali li tolote Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, SI 62 Prejeto v recenzijo: 2022-04-06 © 2022 Avtorji. Prejeto popravljeno: 2022-06-13 Odobreno za objavo: 2022-06-16 riraa i teria arateriacia trdialeiti organskih kompoz itnih faz no spremenljivih snovi (PCM) a ooi aoi ili iolai aoraeo z a shranjevanje toplote * R agul Kumar Kittusamy – Velavan R ajagopal – P aul G regory Felix Tehniški kolidž PSG, Oddelek za strojništvo, Indija Glavni cilj pricujocega raziskovalnega dela je premostitev vrzeli med ponudbo in potrebami po energiji na podrocju gospodinjskih solarnih grelnikov vode (SGV). Shranjevanje toplote (ST) v SGV s pomocjo fazno spremenljivih snovi je do okolja prijazen pristop k pripravi dodatne vroce vode. Delovna temperatura gospodinjskih SGV je približno 65 C. Konvencionalni PCM na osnovi parafina, ki se uporabljajo za ST v SGV, imajo tališce med 50 C in 60 C ter niso primerni za zagotavljanje vroce vode z najvišjo želeno temperaturo. Vpredstavljenem delu je bila uporabljena evtekticna kombinacija PCM na osnovi mašcobnih kislin s tališcem blizu 65 C kot alternativa parafinskim PCM za pripravo vroce vode z najvišjo temperaturo. Toplotna prevodnost najbolj raz širjenih sodobnih PCM je raz meroma niz ka (od 0,5 do 1 W/mK), kar lahko resno vpliva na celotno z mogljivost sistema z a ST. Z a naslavljanje omenjenega problema so bili predlagani faz no spremenljivi snovi dodani nanoaditivi na osnovi ogljika. N anodelci grafena so bili dodani po postopku dvostopenjske mehanske disperzije v utežnih razmerjih 1, 2 in 3 . a pravilno uporabo pripravljenih kompozitov N PCM v kateri koli aplikaciji je potrebno osnovno poz navanje materialnih lastnosti, v objavljeni literaturi pa ni bilo mogoce najti raziskav termicnih lastnosti PCM na osnovi mašcobnih kislin z razlicno vsebnostjo nanodelcev grafena. Glavni cilj raziskovalnega dela je bila priprava in preucitev toplotnih lastnosti ter kemijske in toplotne stabilnosti novih kompoz itov. O bstoj in enakomerna poraz delitev grafena v PCM sta bila potrjena z ramanskim spektrometrom in analizo z vrsticnim elektronskim mikroskopom. Rezultati FTIR in RD so pokazali, da so vsi trije kompoziti NPCM kemijsko stabilni, njihova kristalinicnost pa je podobna kot pri osnovnem PCM. Pri vzorcu s 3 grafena se je toplotna prevodnost v trdnem stanju povecala za 21,8 , toplotna prevodnost v kapljevitem stanju pa za 161,65 . Analiza DSC je razkrila tudi 3,52-odstotno zmanjšanje specificne latentne toplote. Vsi kompoziti NPCM imajo zacetno in vršno temperaturo tališca blizu osnovnega PCM. Rezultati TGS so pokazali, da so kompoz iti N PCM raz meroma toplotno stabilnejši kot osnovni PCM. aradi povišane toplotne prevodnosti kompozitov NPCM je mogoce pospešiti tudi hitrost taljenja in strjevanja med cikli polnjenja in praznjenja. a najboljši izkoristek razpoložljive soncne energije bi zato bilo mogoce povecati volumsko kapaciteto sistema za STna osnovi NPCM oz. zagotoviti prostor za hrambo vecjih kolicin NPCM. Tako bi se dalo maksimalno izkoristiti potencialno specificno latentno toploto NPCM za shranjevanje dodatne toplote in SGV bi lahko zagotavljali dodatno vroco vodo pri želeni temperaturi. Predlagani kompoziti NPCM so tako lahko najboljša alternativa konvencionalnim parafinskim PCM za gospodinjske SGVz integrirano možnostjo ST. Potencialna uporaba predlaganih kompoz itov N PCM pa ni omejena le na ST v SG V, saj so primerni tudi z a ST v sistemih z a rekuperacijo niz kotemperaturne odpadne toplote in z a toplotno upravljanje elektronike. Z a potrditev toplotnih lastnosti NPCM v daljšem casovnem obdobju bodo potrebni še preizkusi s pospešenimi toplotnimi cikli, za preucitev realnega vedenja NPCM v SGV pa podrobnejše študije s toploto sonca. le eede aodelci raea ooit oa eeria raeae tolote olari grelnik vode Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, SI 63 Prejeto v recenzijo: 2022-02-22 © 2022 Avtorji. Prejeto popravljeno: 2022-04-29 Odobreno za objavo: 2022-05-12 Otiiacia rai olioea dioida etedee oilX * Prabhakaran Jayasankar – J ayabal Subbaian Vladni tehniški kolidž, Oddelek za strojništvo, Indija Kakovost z raka v potniškem prostoru voz il je lahko petkrat slabša kot v stanovanjskih in nestanovanjskih stavbah, zaradi cesar se pojavljajo zdravstvene težave, kot so glavobol, draženje grla in slabost, ki so simptomi onesnaženega zraka. Nadzor ogljikovega dioksida kot enega glavnih onesnaževal v kabinah vozil je pogoj za regulacijo ravni ogljikovega dioksida. Pricujoca raziskava obravnava beleženje ravni ogljikovega dioksida pri razlicnem številu potnikov, hitrosti z raka in temperaturi. Potniki v klimatiz iranih voz ilih bodo tako lahko uporabljali svoje klimatske naprave na optimalen nacin za zdravo uporabniško izkušnjo. Raziskovalni problem je dolocitev minimalne vrednosti onesnaževal zraka v potniškem prostoru, kot je ogljikov dioksid, pri razlicnem številu potnikov, hitrosti zraka in temperaturi. a dolocitev minimalne ravni ogljikovega dioksida pri razlicnih obremenitvah ter ustrezne hitrosti zraka in temperature v vozilu tipa kombilimuz ina je bila uporabljena z asnova, analiz a in optimiz acija po metodi odz ivnih površin. Poleg tega so bili za dolocanje minimalne ravni ogljikovega dioksida uporabljeni metoda odzivnih površin, posplošena metoda reduciranega gradienta in genetski algoritem. Vecina raziskovalcev pri iskanju optimalnih vrednosti odgovorov uporablja statisticne, gradientne in metahevristicne algoritme. Z a meritve koncentracije ogljikovega dioksida v voz ilu je bil uporabljen prenosljivi merilnik I AQ CO 2 proizvajalca Extech (model CO250). Merilna naprava deluje po nacelu nedisperzivne infrardece spektroskopije (NDIR) ter lahko meri koncentracije do 5000 ppm z locljivostjo 1 ppm. Merilnik je bil nastavljen za snemanje podatkov v enominutnih intervalih. R ez ultati meritev CO 2 so bili nato s proizvajalcevo programsko opremo preneseni v prenosni racunalnik. Izbran je bil petsedežni avtomobil tipa kombilimuzina s klimatsko napravo, ki omogoca nastavitev temperature v obmocju od 18 C do 25 C ter vklop in izklop kroženja zraka. Opravljeni so bili po trije preizkusi za primere, ko v avtu sedi 1 do 5 potnikov. Pri koncni optimizaciji parametrov so bile uporabljene povprecne vrednosti rezultatov vseh treh preizkusov. Po opravljenih eksperimentih so bile uporabljene optimizacijske tehnike z metahevristicnimi algoritmi. Opravljeni so bili eksperimenti v optimalnih pogojih, dolocenih po metodah RSM, GRG in GA, vrednosti ravni ogljikovega dioksida pa so bile nato razvršcene in primerjane z optimalnimi vrednostmi. Napovedane ravni ogljikovega dioksida po metodi R SM ob prisotnosti 1 do 5 ljudi v kabini so z našale 471,876 ppm, 508,865 ppm, 580,7 ppm, 65,05 ppm in 76,362 ppm. Eksperimentalno dolocene vrednosti so znašale 47,83 ppm, 503,832 ppm, 586,231 ppm, 671,376 ppm in 752,263 ppm. Absolutne odstotne vrednosti napake metode G R G ob prisotnosti 1 do 5 ljudi v kabini so z našale 1,8, 0,9, 0,9, 1,7 oz . 1,1. N apovedane ravni ogljikovega dioksida po metodi G A ob prisotnosti 1 do 5 ljudi v kabini so z našale 471,61 1 ppm, 508,785 ppm, 580,722 ppm, 659 ,839 ppm in 76,016 ppm. Eksperimentalno dolocene vrednosti so znašale 47,83 ppm, 503,832 ppm, 58,124 ppm, 671,376 ppm in 752,263 ppm . Lastnosti kakovosti zraka v notranjem prostoru, kot so relativna vlažnost zraka, vsebnost trdnih delcev, raven ogljikovega monoksida in raven kisika, je mogoce optimizirati z optimizacijskimi tehnikami ter dolociti optimalno vrednost za ugodno in zdravo življenje v notranjih prostorih. S temi metodami je mogoce dolociti optimalne vhodne parametre klimatizacije, kot so vhodna hitrost, pretok svežega zraka, nacin filtriranja in zahtevana temperatura zraka za razlicne obremenitve notranjega prostora. Lastnosti zraka v notranjih prostorih so odvisne od vsakokratnega prostora, vrednosti v razlicnih državah pa se lahko spreminjajo v odvisnosti od okoljskih razmer in nenadnih klimatskih sprememb na zadevnem geografskem podrocju. tudijo bo v prihodnje mogoce razširiti tudi na ostala vozila, kot so športni terenci in avtomobili s sedmimi sedeži, tovornjaki, avtobusi in celo vlaki, ob upoštevanju spremenljivega števila potnikov, nadmorske višine, nacina prezracevanja in zunanjih vremenskih pogojev. tudija je tako dobro izhodišce za raziskovalce kakovosti zraka v notranjih prostorih, ki uporabljajo racunalniške tehnike za ucinkovito analizo zdravja in ugodja v avtomobilskih kabinah. Podrocje optimizacije kakovosti z raka v voz ilih je sicer omenjano v literaturi, kar pa le v manjši meri velja z a optimiz acijo vhodnih parametrov s ciljem z manjševanje ravni CO 2 v kabinah kombilimuzin. Vpricujocem delu so bili zato uporabljeni trije algoritmi za optimizacijo onesnaževal zraka v kabini. le eede olio dioid etedeo oilo eeti alorite aoot raa oil etoda odz ivnih površin *Naslov avtorja za dopisovanje: Vladni tehniški kolidž, Oddelek za strojništvo, Indija, jpkn006@gmail.com SI 63 Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, SI 64 Prejeto v recenzijo: 2022-04-25 © 2022 Avtorji. Prejeto popravljeno: 2022-06-20 Odobreno za objavo: 2022-07-08 Otiiacia otoa oroea tooea area magnez ijeve z litine AZ 61 Davood Afshari1, * – Ali G haffari1 – Z uheir Barsum2 1 Univerz a v Z anjanu, I ran 2 Kraljevi inštitut za tehnologijo, vedska Vclankuje predstavljena integracija umetne nevronske mreže (ANN) in vecciljnega genetskega algoritma (GA) za optimizacijo uporovnega tockovnega varjenja magnezijeve zlitine A61. Magnezijeve (Mg) zlitine v zadnjem casu pridobivajo vse vec pozornosti in pomena v kategoriji kovin, ki so enostavne za obdelavo. Odlikuje jih izjemno raz merje med trdnostjo in maso, med drugim pa jih uporabljajo v avtomobilski, letalski in vesoljski industriji ter z a gradnjo konstrukcij. Kljub z natnemu z animanju pa ostaja industrijska uporaba magnez ijevih z litin v primerjavi z aluminijevimi in jeklenimi zlitinami omejena zaradi nekaterih tehnicnih težav. Uporovno tockovno varjenje (UTV) magnezijevih zlitin je bolj kompleksno kot UTVjeklenih in aluminijevih zlitin ter zahteva drugacne varilne parametre. Glavni cilj pricujoce študije je bila zato identifikacija optimalnih parametrov UTV za kakovostne zvarne spoje z visoko trdnostjo. Stabilnost in trdnost zvarnega spoja sta mocno odvisni od velikosti zvarne lece in preostalih napetosti po postopku varjenja, zato je glavni cilj optimizacije doseganje najvecje velikosti zvarne lece in minimalnih preostalih nateznih napetosti v obmocju zvara. Glavni varilni parametri, ki vplivajo na kakovost zvarov, so elektricni tok, cas varjenja in sila elektrod. Uporabljena je bila faktorska zasnova eksperimentov za preucitev vpliva varilnih parametrov na velikost zvarne lece in preostalih napetosti v uporovnem tockovnem zvarnem spoju materiala A61. Iz polne faktorske zasnove eksperimentov iz haja skupaj 8 kombinacij vhodnih parametrov z a varjenje preiz kušancev. Z varjeni preiz kušanci so bili prerezani po srednjici in nato je bila z opticnim mikroskopom izmerjena velikost zvarne lece. a meritve preostalih napetosti je bila izbrana metoda RD. Elektricni tok, cas varjenja in njune interakcije vplivajo na velikost zvarne lece, medtem ko sila elektrod in njene interakcije z ostalimi spremenljivkami prakticno nimajo nikakršnega vpliva. Elektricni tok ima najvecji vpliv na velikost zvarne lece. as varjenja in sila elektrod vplivata na preostale napetosti. as varjenja ima najvecji vpliv na preostale napetosti, medtem ko je vpliv elektricnega toka prakticno zanemarljiv. V študiji sta bili uporabljeni dve loceni vecslojni ANN s povezavami naprej in algoritmom vzvratnega razširjanja za napovedovanje velikosti zvarnih lec in najvecjih preostalih nateznih napetosti. Rezultati so pokazali, da lahko obe umetni nevronski mreži z visoko tocnostjo napovesta velikost zvarnih lec in preostalih napetosti na osnovi parametrov uporovnega tockovnega varjenja. Koncno je bil razvit še integriran vecciljni algoritem ANN-ANN-GA za optimizacijo parametrov uporovnega tockovnega varjenja. a oceno tocnosti predlaganega vecciljnega GA je bilo opravljeno UTV preizkušanca z optimalnimi parametri. Velikost zvarne lece in preostale napetosti so bile tudi eksperimentalno iz merjene in primerjane z napovedmi integriranega optimiz acijskega algoritma. Predstavljeni integrirani algoritem ANN-ANN-GAlahko z visoko tocnostjo napove velikost zvarnih lec in preostalih napetosti, optimalni parametri UTV pa z agotavljajo visoko trdnost in kakovost z varnega spoja. le eede oroo tooo aree reotale aetoti eta eroa rea eeti algoritem, magnez ijeva z litina AZ 61 Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, SI 65 © 2022 Avtorji. Prejeto v recenzijo: 2022-03-31 Prejeto popravljeno: 2022-05-30 Odobreno za objavo: 2022-06-01 Vpliv dvostopenjskega staranja in obdelave R R A na abraz ivno obrabo med tremi telesi pri z litini AW7075 * Marz ena M. Lachowicz Tadeusz Lenieski Maciej B. Lachoicz Z nanstveno-tehniška univerz a v Wroclawu, Fakulteta z a strojništvo, Poljska Pri nekaterih aplikacijah z aluminijevimi z litinami prihaja do relativnega gibanja med površinami komponent in obrabna obstojnost je v tem primeru pomembna lastnost materiala. Mnoge raz iskave so pokaz ale, da lahko toplotna obdelava signifikantno vpliva na tribološko obrabo. Z lasti fragmentacija sestavnih delov v mikrostrukturi lahko pomembno vpliva na tribološke parametre. V clanku je predstavljena analiza vpliva stanja po toplotni obdelavi na abrazivno obrabo aluminijeve zlitine A7075. a dolocitev obstojnosti proti abrazivni obrabi so bili opravljeni preizkusi z napravo T-07. Glede na rezultate preizkusov so stopnje abrazivne obrabe preizkušanih zlitin po razlicnih toplotnih obdelavah razvršcene takole: dvostopenjsko staranje < obdelava R R A < stanje T6. a dolocitev utrjevanja materiala je bila opravljena meritev trdote po Vickersu. Trdota zlitine A7075 narašca v tem vrstnem redu: dvostopenjsko staranje < stanje T6 < obdelava R R A. Z analiz o odvisnosti med trdoto in abraz ivno obrabo je bilo ugotovljeno, da trdota ni edini dejavnik vpliva na tovrstno obrabo, saj imata pomembno vlogo tudi mikrostruktura preiz kušene z litine in stanje po toplotni obdelavi. Material ima po dvostopenjskem staranju in po obdelavi RRA kljub razlicnim vrednostim trdote podobno obrabno obstojnost in zato je bil analiziran tudi vpliv mikrostrukture. Podana je domneva, da prevlada izlocenih delcev, ki so koherentni z osnovo v mikrostrukturi, spodbuja ohranjanje zveznosti osnove in izlocenih delcev. Vecji in nekoherentni izloceni delci v osnovi lahko nasprotno delujejo kot abraziv in povecajo stopnjo obrabe. Kontinuiteta izlockov in osnove se v tem primeru lažje prekine kot v prisotnosti koherentnih delcev. Dekohezija obicajno nastopi na mejah zrn oz. na mejnih površinah. Po triboloških preiskavah je bila opravljena še preiskava površin z vrsticnim elektronskim mikroskopom za dolocitev dominantnega mehanizma površinskih poškodb. Obrabne lastnosti kažejo podoben tip poškodb ne glede na stanje po toplotni obdelavi. Gre predvsem za praske, brazde, mikrorazpoke in rahlo plasticno deformacijo na obrabni površini. Prisotnost vecjih delcev primarnih faz, ki se ne raztopijo med toplotno obdelavo, vpliva na njihovo drobljenje in defragmentacijo med abrazivnim obrabljanjem. aradi trenja je mogoce pricakovati dva pojava v predelu blizu površine: povecanje trdote, ki je znamenje utrjanja zaradi plasticne deformacije, ter delno izginotje in rast faz izlocevalnega utrjanja zaradi povišanja temperature, ki je posledica trenja. Analiz a je bila z ato raz širjena z meritvami poraz delitve trdote po preseku. R ez ultati so pokaz ali, da ni prišlo do nobenega od omenjenih pojavov. Spremembe trdote, ki bi bile povez ane z deformacijskim utrujanjem, ali strukturne spremembe zaradi trenja niso bile opažene. le eede aliiee litie araia oraa tolota odelaa trdota irotrtra Strojniški vestnik - Journal of Mechanical Engineering 68(2022)7-8, SI 66 Prejeto v recenzijo: 2022-01-26 © 2022 Avtorji. Prejeto popravljeno: 2022-07-08 Odobreno za objavo022-07-11 Nitridiranje jekla H S6-5-2 v induktivno sklopljeni plaz mi Marek Binienda1 – R obert Pietrasik2, – Sylester Pata2 – K rz ysz tof Matcz ak1 – Witold Krotewicz 1 Tehnološka skupina Z emat, Poljska 2 Tehniška univerza v Lodžu, Inštitut za materiale in inženiring, Poljska V clanku je predstavljena raziskava o možnostih površinskega utrjevanja jekla HS6-5-2 z nitridiranjem v induktivno sklopljeni plaz mi (I CP). Z aradi nenehnega tehnološkega raz voja obstaja potreba po optimiz aciji funkcionalnih lastnosti materialov, ki se uporabljajo pri proiz vodnji orodij in strojnih delov. Problema se je po eni strani mogoce lotiti s proizvodnjo orodnih materialov z boljšimi lastnostmi, ki zahtevajo uporabo dragih zlitinskih dodatkov v vecstopenjskih tehnoloških procesih. Po drugi strani pa potekajo tudi raziskave na podrocju modifikacije površinskih slojev z a doseganje novih, primernejših funkcionalnih lastnostih pri orodjih, ki so takoj pripravljena za uporabo. Kljub znatnemu napredku na podrocju inženiringa površin pa še vedno povzrocajo težave metode z a iz boljševanje trajnosti in z anesljivosti orodij ter konstrukcijskih elementov, z lasti tistih z majhnimi dimenz ijami. Ena najbolj raz širjenih tehnologij, z lasti z a dele majhnih dimenz ij, je nitridiranje. N itridiranje po klasicni termokemicni metodi povzroci formiranje krhkih slojev (Fe2-3 N) in ¶ (Fe4 N ). Procesi v nadz orovani plinski atmosferi sicer omogocajo obvladovanje fazne sestave slojev, so pa razmeroma zamudni, tudi pri pripravi tankih slojev. Uporaba induktivno sklopljene plazme, ustvarjene v mocnem magnetnem polju s Foucaultovimi tokovi, odpravlja pospeševalno elektricno polje. Magnetno polje tuljave ustvarja vrtincne tokove v plinu in v obdelovancu, ti pa hkrati izpolnjujejo dve nalogi: uporovno segrevanje plina (dušika) do razelektritve in nastanka obroca plaz me ter segrevanje obdelovanca do globine penetracije. Vrednost je odvisna od upornosti ioniz iranega plina in obdelovanca ter od frekvence. Veckratna ionizacija delcev v nizkotemperaturni neizotermni plazmi zagotavlja ucinkovit vir medija za nitridiranje in je primerna za difuzno nasicenje kovin. Uporaba inducirane plazme za nitridiranje jekel je prakticno neznana, saj je objavljenih le nekaj raziskav na laboratorijski ravni. a preizkuse v okviru pricujoce raziskave je bilo izbrano jeklo HS6-5-2. Nitridiranje preizkušancev je bilo opravljeno v reaktorju s kvarcno cevjo v induktivno sklopljeni plazmi pri frekvenci 27,12 MHz. Delovni procesni tlak v dušikovi atmosferi s cistoco , je znašal 100 Pa. Plazemski reaktor je poganjal generator z naslednjimi stopnjami mocmi: 500 , 1 k, 1,5 k: in 2 k. Preizkušanci na delovnih mizicah iz kvarcnega stekla so bili nitridirani pri konstantnem tlaku in nastavljeni moci generatorja 15, 30 oz. 45 minut. Mikrostruktura preizkušancev v prerezu je bila preiskana pod opticnim mikroskopom Nikon MA200 (Nikon Instech Co., Ltd., Tokio, Japonska). Mikrostruktura in kemicna sestava površinskih slojev sta bili preiskani tudi pod vrsticnim elektronskim mikroskopom (SEM) JEOLJSM-6610 LV(JEOLLtd., Tokio, Japonska), opremljenim z energijsko disperz ijskim spektroskopom (EDS) X -MAX 80 O xford I nstruments (O xford I nstruments G roup, Abingdon, druženo kraljestvo). Rentgentska difrakcija (RD) je bila opravljena z napravo PANalytical Empyrean (Malvern Panalytical Ltd, Malvern, druženo kraljestvo). Porazdelitev trdote v nitridiranih slojih je bila izmerjena z merilnikom mikrotrdote po Vickersu N EX US 4305 (I N N O VATEST Ltd., Maastricht, N iz oz emska). Površinska trdota preiz kušanca, pripravljenega z a metalografske preiskave, je bila iz merjena na oddaljenosti 10 m od roba preiz kušanca in nato v korakih velikosti 5 m proti notranjosti z obremenitvijo 0,98 N . Na podlagi porazdelitve trdote po obdelavi z mocjo 1 k, 1,5 kin 2 kje bila dolocena efektivna debelina posamez nih slojev po standardu DI N 50190-3 ( merilo je trdota 50 H V nad trdoto jedra). Induktivno sklopljena plazma omogoca izdelavo nitridiranih slojev s primerno strukturo. Ta ugotovitev je pomembna s tehnološkega in ekonomskega vidika, saj postopek zagotavlja signifikantno skrajšanje casa obdelave ter popoln nadzor nad strukturo slojev, torej tudi nad obmocji brez nitridov. Možnost industrijskega nitridiranja v induktivno sklopljeni plazmi je zelo pomembna tudi z ekološkega stališca – v procesu je namrec namesto strupenega amoniaka uporabljen inertni plin dušik. Pri novi tehnologiji tudi ni emisij, ki bi z ahtevale uporabo plinov za naknadno obdelavo. Dosežena je bila najvecja trdota pribl. 1100 HV, kar predstavlja 350-odstotno povecanje trdote v primerjavi z neobdelanim materialom. as obdelave za ustvarjanje slojev debeline 100 m s funkcionalnimi lastnostmi je z elo kratek, komaj 45 m inut. le eede laa itridirae orii lo trdota Guide for Authors All manuscripts must be in English. Pages should be numbered sequentially. The manuscript should be composed in accordance with the Article Template given above. The suggested length of contributions is 10 to 20 pages. Longer contributions will only be accepted if authors provide justification in a cover letter. 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We kindly ask you to suggest at least two reviewers for your paper and give us their names, their full affiliation and contact information, and their scientific research inter­est. The suggested reviewers should have at least two relevant references (with an impact factor) to the scientific field concerned; they should not be from the same country as the authors and should have no close connection with the authors. FORMAT OF THE MANUSCRIPT: The manuscript should be composed in accordance with the Article Template. The manuscript should be written in the following format: - A Title that adequately describes the content of the manuscript. - A list of Authors and their affiliations. - An Abstract that should not exceed 250 words. The Abstract should state the principal objectives and the scope of the investigation, as well as the methodology employed. It should summarize the results and state the principal conclusions. - 4 to 6 significant key words should follow the abstract to aid indexing. - 4 to 6 highlights; a short collection of bullet points that convey the core findings and provide readers with a quick textual overview of the article. These four to six bullet points should describe the essence of the research (e.g. results or conclusions) and high­light what is distinctive about it. - An Introduction that should provide a review of recent literature and sufficient back­ground information to allow the results of the article to be understood and evaluated. - A Methods section detailing the theoretical or experimental methods used. - An Experimental section that should provide details of the experimental set-up and the methods used to obtain the results. - A Results section that should clearly and concisely present the data, using figures and tables where appropriate. - A Discussion section that should describe the relationships and generalizations shown by the results and discuss the significance of the results, making comparisons with pre­viously published work. (It may be appropriate to combine the Results and Discussion sections into a single section to improve clarity.) - A Conclusions section that should present one or more conclusions drawn from the results and subsequent discussion and should not duplicate the Abstract. - Acknowledgement (optional) of collaboration or preparation assistance may be includ­ed. Please note the source of funding for the research. - Nomenclature (optional). Papers with many symbols should have a nomenclature that defines all symbols with units, inserted above the references. If one is used, it must con­tain all the symbols used in the manuscript and the definitions should not be repeated in the text. In all cases, identify the symbols used if they are not widely recognized in the profession. Define acronyms in the text, not in the nomenclature. - References must be cited consecutively in the text using square brackets [1] and col­lected together in a reference list at the end of the manuscript. - Appendix(-icies) if any. v, T, n, etc.). Symbols for units that consist of letters should be in plain text (e.g. ms-1, K, min, mm, etc.). Please also see: http://physics.nist.gov/cuu/pdf/sp811.pdf . Abbreviations should be spelt out in full on first appearance followed by the abbreviation in parentheses, e.g. variable time geometry (VTG). The meaning of symbols and units belonging to symbols should be explained in each case or cited in a nomenclature section at the end of the manuscript before the References. Figures (figures, graphs, illustrations digital images, photographs) must be cited in consecutive numerical order in the text and referred to in both the text and the captions as Fig. 1, Fig. 2, etc. Figures should be prepared without borders and on white grounding and should be sent separately in their original formats. If a figure is composed of several parts, please mark each part with a), b), c), etc. and provide an explanation for each part in Figure caption. The caption should be self-explanatory. Letters and numbers should be readable (Arial or Times New Roman, min 6 pt with equal sizes and fonts in all figures). Graphics (submitted as supplementary files) may be exported in resolution good enough for printing (min. 300 dpi) in any common format, e.g. TIFF, BMP or JPG, PDF and should be named Fig1.jpg, Fig2.tif, etc. However, graphs and line drawings should be prepared as vector images, e.g. CDR, AI. Multi-curve graphs should have individual curves marked with a symbol or otherwise provide distinguishing differences using, for example, different thicknesses or dashing. Tables should carry separate titles and must be numbered in consecutive numerical order in the text and referred to in both the text and the captions as Table 1, Table 2, etc. In addition to the physical quantities, such as t (in italics), the units [s] (normal text) should be added in square brackets. Tables should not duplicate data found elsewhere in the manuscript. Tables should be prepared using a table editor and not inserted as a graphic. REFERENCES: A reference list must be included using the following information as a guide. Only cited text references are to be included. Each reference is to be referred to in the text by a number enclosed in a square bracket (i.e. [3] or [2] to [4] for more references; do not combine more than 3 references, explain each). No reference to the author is necessary. References must be numbered and ordered according to where they are first mentioned in the paper, not alphabetically. All references must be complete and accurate. Please add DOI code when available. Examples follow. Journal Papers: Surname 1, Initials, Surname 2, Initials (year). Title. Journal, volume, number, pages, DOI code. [1] Hackenschmidt, R., Alber-Laukant, B., Rieg, F. (2010). Simulating nonlinear materials under centrifugal forces by using intelligent cross-linked simulations. Strojniški vest-nik - Journal of Mechanical Engineering, vol. 57, no. 7-8, p. 531-538, DOI:10.5545/sv­jme.2011.013. Journal titles should not be abbreviated. Note that journal title is set in italics. Books: Surname 1, Initials, Surname 2, Initials (year). Title. Publisher, place of publication. [2] Groover, M.P. (2007). Fundamentals of Modern Manufacturing. John Wiley & Sons, Hoboken. Note that the title of the book is italicized. Chapters in Books: Surname 1, Initials, Surname 2, Initials (year). Chapter title. Editor(s) of book, book title. Publisher, place of publication, pages. [3] Carbone, G., Ceccarelli, M. (2005). Legged robotic systems. Kordi˜, V., Lazinica, A., Merdan, M. (Eds.), Cutting Edge Robotics. Pro literatur Verlag, Mammendorf, p. 553­576. Proceedings Papers: Surname 1, Initials, Surname 2, Initials (year). Paper title. Proceedings title, pages. [4] Štefani˜, N., Martin°evi˜-Miki˜, S., Tošanovi˜, N. (2009). Applied lean system in process industry. MOTSP Conference Proceedings, p. 422-427. Standards: Standard-Code (year). Title. Organisation. Place. [5] ISO/DIS 16000-6.2:2002. Indoor Air – Part 6: Determination of Volatile Organic Com­pounds in Indoor and Chamber Air by Active Sampling on TENAX TA Sorbent, Thermal Desorption and Gas Chromatography using MSD/FID. International Organization for Standardization. Geneva. WWW pages: Surname, Initials or Company name. Title, from http://address, date of access. [6] Rockwell Automation. Arena, from http://www.arenasimulation.com, accessed on 2009­09-07. EXTENDED ABSTRACT: When the paper is accepted for publishing, the authors will be requested to send an extended abstract (approx. one A4 page or 3500 to 4000 characters or approx. 600 words). The instruction for composing the extended abstract are published on-line: http://www.sv-jme.eu/information-for-authors/ . COPYRIGHT: Authors submitting a manuscript do so on the understanding that the work has not been published before, is not being considered for publication elsewhere and has been read and approved by all authors. The submission of the manuscript by the authors means that the authors automatically agree to publish the paper uder CC-BY 4.0 Int. or CC-BY-NC 4.0 Int. when the manuscript is accepted for publication. All accepted manuscripts must be accompanied by a Copyright Agreement, which should be sent to the editor. The work should be original work by the authors and not be published elsewhere in any language without the written consent of the publisher. The proof will be sent to the author showing the final layout of the article. Proof correction must be minimal and executed quickly. Thus it is essential that manuscripts are accurate when submitted. Authors can track the status of their accepted articles on https://en.sv-jme.eu/. PUBLICATION FEE: Authors will be asked to pay a publication fee for each article prior to the article appearing in the journal. However, this fee only needs to be paid after the article has been accepted for publishing. The fee is 380 EUR (for articles with maximum of 6 pages), 470 EUR (for articles with maximum of 10 pages), plus 50 EUR for each additional page. The additional cost for a color page is 90.00 EUR (only for a journal hard copy; optional upon author’s request). These fees do not include tax. SPECIAL NOTES Units: The SI system of units for nomenclature, symbols and abbreviations should be Strojniški vestnik -Journal of Mechanical Engineering followed closely. Symbols for physical quantities in the text should be written in italics (e.g. Ašker°eva 6, 1000 Ljubljana, Slovenia, e-mail: info@sv-jme.eu http://www.sv-jme.eu Contents Papers 451 Oguz Dogan: Short-term Creep Behaviour of Different Polymers Used in Additive Manufacturing under Different Thermal and Loading Conditions 461 Ragul Kumar Kittusamy, Velavan Rajagopal, Paul Gregory Felix: Preparation and Thermal Characterization of Nanographene-Enhanced Fatty Acid-Based Solid-Liquid Organic Phase Change Material Composites for Thermal Energy Storage 471 Prabhakaran Jayasankar, Jayabal Subbaian: Optimization of in-Vehicle Carbon Dioxide Level in a 5-Seat Car 485 Davood Afshari, Ali Ghaffari, Zuheir Barsum: Optimization in the Resistant Spot-Welding Process of AZ61 Magnesium Alloy 493 Marzena M. 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