Multi-constrained 3D topology optimization via augmented topological level-set

TL;DR

This paper presents a robust 3D topology optimization method combining topological level-set, augmented Lagrangian, and assembly-free deflated FEA to efficiently handle multiple constraints in complex designs.

Contribution

It introduces a novel integrated approach that effectively manages multiple constraints in 3D topology optimization using advanced sensitivity analysis and computational techniques.

Findings

Successfully applied to several 3D numerical examples

Demonstrates improved computational efficiency

Effectively handles multiple constraints in topology optimization

Abstract

The objective of this paper is to introduce and demonstrate a robust methodology for solving multi-constrained 3D topology optimization problems. The proposed methodology is a combination of the topological level-set formulation, augmented Lagrangian algorithm, and assembly-free deflated finite element analysis (FEA). The salient features of the proposed method include: (1) it exploits the topological sensitivity fields that can be derived for a variety of constraints, (2) it rests on well-established augmented Lagrangian formulation to solve constrained problems, and (3) it overcomes the computational challenges by employing assembly-free deflated FEA. The proposed method is illustrated through several 3D numerical experiments.