A multi-material topology optimization algorithm based on the topological derivative

TL;DR

This paper introduces a level-set based topology optimization algorithm capable of handling multiple materials, extending previous two-material methods to arbitrary material counts, and demonstrating its effectiveness through numerical examples.

Contribution

The paper extends a two-material topology optimization algorithm to multiple materials using a vector-valued level set function and generalized topological derivatives.

Findings

Successfully applied to academic and elasticity problems.

Supports nucleation without initial perforation.

Achieves local optimality conditions in multi-material design.

Abstract

We present a level-set based topology optimization algorithm for design optimization problems involving an arbitrary number of different materials, where the evolution of a design is solely guided by topological derivatives. Our method can be seen as an extension of the algorithm that was introduced in (Amstutz, Andrae 2006) for two materials to the case of an arbitrary number $M$ of materials. We represent a design that consists of multiple materials by means of a vector-valued level set function which maps into $\mathbb R^{M-1}$. We divide the space $\mathbb R^{M-1}$ into $M$ sectors, each corresponding to one material, and establish conditions for local optimality of a design based on certain generalized topological derivatives. The optimization algorithm consists in a fixed point iteration striving to reach this optimality condition. Like the two-material version of the algorithm, also our method possesses a nucleation mechanism such that it is not necessary to start with a perforated initial design. We show numerical results obtained by applying the algorithm to an academic example as well as to the compliance minimization in linearized elasticity.