Cargando…

Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization

The present work presents an algorithmic approach to determine the optimal starting point for any complex geometry draping processes. The time-efficient Kinematic Draping Simulation (KDS) is used to assess the drapability of a geometry depending on many different starting points. The optimization pr...

Descripción completa

Detalles Bibliográficos
Autores principales: Fitas, Ricardo, Hesseler, Stefan, Wist, Santino, Greb, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668529/
https://www.ncbi.nlm.nih.gov/pubmed/36406739
http://dx.doi.org/10.1016/j.heliyon.2022.e11525
_version_ 1784831933369286656
author Fitas, Ricardo
Hesseler, Stefan
Wist, Santino
Greb, Christoph
author_facet Fitas, Ricardo
Hesseler, Stefan
Wist, Santino
Greb, Christoph
author_sort Fitas, Ricardo
collection PubMed
description The present work presents an algorithmic approach to determine the optimal starting point for any complex geometry draping processes. The time-efficient Kinematic Draping Simulation (KDS) is used to assess the drapability of a geometry depending on many different starting points. The optimization problem is then solved by applying Particle Swarm Optimization (PSO). The proposed methodology is applied to and validated with complex geometry and a common part of the automobile industry: the B-Pillar geometry. The results show that the PSO algorithm may improve random search up to 78 times. After several experiments, PSO particles have discrete coordinates and are located at optimum global and local regions most of the time, leading to solutions for complex objective functions. The global solution is such that the starting point is located near the geometrical centre of the B-Pillar. The novelty of the work is evident: it uses optimization for a real engineering application, and it draws pattern-related conclusions for other geometries. Experimental results are shown to be consistent with simulation results.
format Online
Article
Text
id pubmed-9668529
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-96685292022-11-17 Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization Fitas, Ricardo Hesseler, Stefan Wist, Santino Greb, Christoph Heliyon Research Article The present work presents an algorithmic approach to determine the optimal starting point for any complex geometry draping processes. The time-efficient Kinematic Draping Simulation (KDS) is used to assess the drapability of a geometry depending on many different starting points. The optimization problem is then solved by applying Particle Swarm Optimization (PSO). The proposed methodology is applied to and validated with complex geometry and a common part of the automobile industry: the B-Pillar geometry. The results show that the PSO algorithm may improve random search up to 78 times. After several experiments, PSO particles have discrete coordinates and are located at optimum global and local regions most of the time, leading to solutions for complex objective functions. The global solution is such that the starting point is located near the geometrical centre of the B-Pillar. The novelty of the work is evident: it uses optimization for a real engineering application, and it draws pattern-related conclusions for other geometries. Experimental results are shown to be consistent with simulation results. Elsevier 2022-11-12 /pmc/articles/PMC9668529/ /pubmed/36406739 http://dx.doi.org/10.1016/j.heliyon.2022.e11525 Text en © 2022 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Fitas, Ricardo
Hesseler, Stefan
Wist, Santino
Greb, Christoph
Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization
title Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization
title_full Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization
title_fullStr Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization
title_full_unstemmed Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization
title_short Kinematic draping simulation optimization of a composite B-pillar geometry using particle swarm optimization
title_sort kinematic draping simulation optimization of a composite b-pillar geometry using particle swarm optimization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668529/
https://www.ncbi.nlm.nih.gov/pubmed/36406739
http://dx.doi.org/10.1016/j.heliyon.2022.e11525
work_keys_str_mv AT fitasricardo kinematicdrapingsimulationoptimizationofacompositebpillargeometryusingparticleswarmoptimization
AT hesselerstefan kinematicdrapingsimulationoptimizationofacompositebpillargeometryusingparticleswarmoptimization
AT wistsantino kinematicdrapingsimulationoptimizationofacompositebpillargeometryusingparticleswarmoptimization
AT grebchristoph kinematicdrapingsimulationoptimizationofacompositebpillargeometryusingparticleswarmoptimization