Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Topology optimization of continuum structures under hybrid uncertainties

Topology optimization of continuum structures under hybrid uncertainties The aim of this paper is to study the topology optimization for mechanical systems with hybrid material and geometric uncertainties. The random variations are modeled by a memory-less transformation of random fields which ensures their physical admissibility. The stochastic collocation method combined with the proposed material and geometry uncertainty models provides robust designs by utilizing already developed deterministic solvers. The computational cost is decreased by using of sparse grids and discretization refinement that are proposed and demonstrated as well. The method is utilized in the design of minimum compliance structure. The proposed algorithm provides a computationally cheap alternative to previously introduced stochastic optimization methods based on Monte Carlo sampling by using adaptive sparse grids method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Structural and Multidisciplinary Optimization Springer Journals

Topology optimization of continuum structures under hybrid uncertainties

Download PDF
11 pages

Loading next page...
 
/lp/springer_journal/topology-optimization-of-continuum-structures-under-hybrid-35LXrRkSDq
Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Engineering; Theoretical and Applied Mechanics; Computational Mathematics and Numerical Analysis; Engineering Design
ISSN
1615-147X
eISSN
1615-1488
DOI
10.1007/s00158-017-1868-0
Publisher site
See Article on Publisher Site

Abstract

The aim of this paper is to study the topology optimization for mechanical systems with hybrid material and geometric uncertainties. The random variations are modeled by a memory-less transformation of random fields which ensures their physical admissibility. The stochastic collocation method combined with the proposed material and geometry uncertainty models provides robust designs by utilizing already developed deterministic solvers. The computational cost is decreased by using of sparse grids and discretization refinement that are proposed and demonstrated as well. The method is utilized in the design of minimum compliance structure. The proposed algorithm provides a computationally cheap alternative to previously introduced stochastic optimization methods based on Monte Carlo sampling by using adaptive sparse grids method.

Journal

Structural and Multidisciplinary Optimization – Springer Journals

Published: Dec 4, 2017

References

  • A linearized approach to worst-case design in parametric and geometric shape optimization
    Allaire, G; Dapogny, C
  • Robust truss topology design via semidefinite programming
    Ben-Tal, A; Nemirovski, A
  • Topology optimization of non-linear elastic structures and compliant mechanisms
    Bruns, TE; Tortorelli, DA
  • A new level-set based approach to shape and topology optimization under geometric uncertainty
    Chen, S; Chen, W
  • Level set based robust shape and topology optimization under random field uncertainties
    Chen, SK; Chen, W; Lee, SH
  • Minimax optimization problem of structural design
    Cherkaev, E; Cherkaev, A
  • Introducing loading uncertainty in topology optimization
    Dunning, PD; Kim, HA; Mullineux, G
  • Structural optimization under uncertain loads and nodal locations
    Guest, J; Igusa, T
  • Structural topology optimization based on non-local Shepard interpolation of density field
    Kang, Z; Wang, YQ
  • Topology optimization under uncertainty via non-intrusive polynomial chaos expansion
    Keshavarzzadeha, V; Fernandeza, F; Tortorelli, DA
  • Robust topology optimization for compliant mechanisms considering uncertainty of applied loads
    Kogiso, N; Ahn, W; Nishiwaki, S; Izui, K; Yoshimura, M
  • Topology optimization considering material and geometric uncertainties using stochastic collocation methods
    Lazarov, BS; Schevenels, M; Sigmund, O
  • Topology optimization with geometric uncertainties by perturbation techniques
    Lazarov, BS; Schevenels, M; Sigmund, O
  • New type of optimality criteria method in case of probabilistic loading conditions
    Logo, J
  • Optimal topologies in case of probabilistic loading: the influence of load correlation
    Logo, J; Ghaemi, M; Rad, MM
  • Continuous approximation of material distribution for topology optimization
    Matsui, K; Terada, K
  • Robust topology optimization accounting for spatially varying manufacturing errors
    Schevenels, M; Lazarov, BS; Sigmund, O
  • Manufacturing tolerant topology optimization
    Sigmund, O
  • Topology optimization of continuum structures under uncertainty – a polynomial chaos approach
    Tootkaboni, M; Asadpoure, A; Guest, JK
  • Robust topology optimization of structures under loading uncertainty
    Zhao, J; Wang, C
  • Topology optimization for optical projection lithography with manufacturing uncertainties
    Zhou, M; Lazarov, BS; Sigmund, O