Topology optimization in quasi-static plasticity with hardening using a level-set method

We study topology optimization in quasi-static plasticity with linear kinematic and linear isotropic hardening using a level-set method. We consider the primal variational formulation for the plasticity problem. This formulation is subjected to penalization and regularization, resulting in an approx...

Full description

Saved in:
Bibliographic Details
Published in:Structural and multidisciplinary optimization 2021-11, Vol.64 (5), p.3163-3191
Main Authors: Desai, Jeet, Allaire, Grégoire, Jouve, François, Mang, Chetra
Format: Article
Language:English
Subjects:
Algorithms
Analysis of PDEs
Computation
Computational Mathematics and Numerical Analysis
Engineering
Engineering Design
Engineering Sciences
Hardening
Iterative methods
Mathematics
Mechanical engineering
Mechanics
Optimization
Plastic properties
Regularization
Research Paper
Theoretical and Applied Mechanics
Topology optimization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We study topology optimization in quasi-static plasticity with linear kinematic and linear isotropic hardening using a level-set method. We consider the primal variational formulation for the plasticity problem. This formulation is subjected to penalization and regularization, resulting in an approximate problem that is shape-differentiable. The shape derivative for the approximate problem is computed using the adjoint method. Thanks to the proposed penalization and regularization, the time discretization of the adjoint problem is proved to be well-posed. For comparison purposes, the shape derivative for the original problem is computed in a formal manner. Finally, shape and topology optimization is performed numerically using the level-set method, and 2D and 3D case studies are presented. Shapes are captured exactly using a body-fitted mesh at every iteration of the optimization algorithm.
ISSN:1615-147X
1615-1488
DOI:10.1007/s00158-021-03034-7