1835 KB0 KB199920252021Dávalos Ramírez, José OmarGómez Roa, AntonioMolina Salazar, JavierRosel Solis, Nanuel JavierRuiz Ochoa, Juan Antonioštevilka:3letnik:67str. 88-100ISSN:0039-2480COBISSID_HOST:67976707URN:URN:NBN:SI:doc-418QLJGXenZveza strojnih inženirjev in tehnikov Slovenije etc.Strojniški vestnikartificial neural networkscrow search algorithmfinite element methodkriterij Tsai-Wumetoda končnih elementovoptimizacijaoptimizationrunning blade prostheticstekaške listnate protezeTsai-Wu criterionumetne nevronske mreževranin iskalni algoritemOptimization of running blade prosthetics utilizing crow search algorithm assisted by artificial neural networks|A crow search algorithm (CSA) was applied to perform the optimization of a running blade prosthetics (RBP) made of composite materials like carbon fibre layers and cores of acrylonitrile butadiene styrene (ABS). Optimization aims to increase the RBP displacement limited by the Tsai-Wu failure criterion. Both displacement and the Tsai-Wu criterion are predicted using artificial neural networks (ANN) trained with a database constructed from finite element method (FEM) simulations. Three different cases are optimized varying the carbon fibre layers orientations: -45°/45°, 0°/90°, and a case with the two-fibre layer orientations intercalated. Five geometric parameters and a number of carbon fibre layers are selected as design parameters. A sensitivity analysis is performed using the Garzon equation. The best balance between displacement and failure criterion was found with fibre layers oriented at 0°/90°. The optimal candidate with -45°/45° orientation presents higher displacement; however, the Tsai-Wu criterion was less than 0.5 and not suitable for RBP design. The case with intercalated fibres presented a minimal displacement being the stiffer RBP design. The damage concentrates mostly in the zone that contacts the ground. The sensitivity study found that the number of layers and width were the most important design parametersTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaUniverza v Ljubljani, Fakulteta za strojništvo