Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models

TL;DR

This paper introduces a stress-constrained topology optimization method for lattice-like structures that employs component-wise reduced order models to significantly reduce computational costs while maintaining accuracy in stress prediction.

Contribution

It develops a novel ROM-based approach for efficient topology optimization of lattice structures, enabling large reductions in run time with accurate stress constraints.

Findings

Achieves approximately 150x speedup in forward solves.

Maintains less than 5% relative error in stress computation.

Successfully reduces mass while respecting stress constraints.

Abstract

Lattice-like structures can provide a combination of high stiffness with light weight that is useful in many applications, but a resolved finite element mesh of such structures results in a computationally expensive discretization. This computational expense may be particularly burdensome in many-query applications, such as optimization. We develop a stress-constrained topology optimization method for lattice-like structures that uses component-wise reduced order models as a cheap surrogate, providing accurate computation of stress fields while greatly reducing run time relative to a full order model. We demonstrate the ability of our method to produce large reductions in mass while respecting a constraint on the maximum stress in a pair of test problems. The ROM methodology provides a speedup of about 150x in forward solves compared to full order static condensation and provides a relative error of less than 5% in the relaxed stress.