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Large-scale stochastic topology optimization using adaptive mesh refinement and coarsening through a two-level parallelization scheme

Autor
Baiges, J.; Martínez, J.; Herrero, D.; Otero, F.; Ferrer, A.
Tipus d'activitat
Article en revista
Revista
Computer methods in applied mechanics and engineering
Data de publicació
2019-01
Volum
343
Pàgina inicial
186
Pàgina final
206
DOI
https://doi.org/10.1016/j.cma.2018.08.028 Obrir en finestra nova
Projecte finançador
Elastic Flow. Aumento de la eficiencia en procesos de mezcla y transmisión de calor utilizando fluidos viscoelásticos en regimen laminar y turbulento
Repositori
http://hdl.handle.net/2117/124683 Obrir en finestra nova
URL
https://www.sciencedirect.com/science/article/pii/S0045782518304237 Obrir en finestra nova
Resum
Abstract Topology optimization under uncertainty of large-scale continuum structures is a computational challenge due to the combination of large finite element models and uncertainty propagation methods. The former aims to address the ever-increasing complexity of more and more realistic models, whereas the latter is required to estimate the statistical metrics of the formulation. In this work, the computational burden of the problem is addressed using a sparse grid stochastic collocation meth...
Paraules clau
Adaptive mesh refinement, Large scale, Parallel computing, Robust topology optimization, Sparse grid, Topological derivative
Grup de recerca
(MC)2 - UPC Mecànica de Medis Continus i Computacional
ANiComp - Anàlisi numèrica i computació científica

Participants

  • Baiges Aznar, Joan  (autor)
  • Martínez Frutos, Jesús  (autor)
  • Herrero Pérez, David  (autor)
  • Otero, Fermín  (autor)
  • Ferrer, Alex  (autor)