Efficient distributed approach for density-based topology optimization using coarsening and h-refinement
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Arquitectura y Tecnología de Computadoras; Lenguajes y Sistemas InformáticosSponsors
This work has been supported by the AEI/FEDER and UE under the contract DPI2016-77538-R.Realizado en/con
Universidad Politécnica de Cartagena; Universidad de MurciaPublication date
2022-03-03Publisher
ELSEVIERBibliographic Citation
David Herrero-Pérez, Sebastián Ginés Picó-Vicente, Humberto Martínez-Barberá, Efficient distributed approach for density-based topology optimization using coarsening and h-refinement, Computers & Structures, Volume 265, 2022, 106770, ISSN 0045-7949, https://doi.org/10.1016/j.compstruc.2022.106770.Peer review
SIKeywords
Topology optimizationDistributed computing
Multigrid methods
Adaptive mesh refinement
Abstract
This work presents an efficient parallel implementation of density-based topology optimization using Adaptive Mesh Refinement (AMR) schemes to reduce the computational burden of the bottleneck of the process, the evaluation of the objective function using Finite Element Analysis (FEA). The objective is to obtain an equivalent design to the one generated on a uniformly fine mesh using distributed memory computing but at a much cheaper computational cost. We propose using a fine mesh for the optimization and a coarse mesh for the analysis using coarsening and refinement criteria based on the thresholding of design variables. We evaluate the functional on the coarse mesh using a distributed conjugate gradient solver preconditioned by an algebraic multigrid (AMG) method showing its computational advantages in some cases by comparing with geometric multigrid (GMG) and AMG methods in two- and three-dimensional problems. We use different computational resources with small regularization distances ...
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