De-homogenization of optimal multi-scale 3D topologies

TL;DR

This paper introduces an efficient de-homogenization method for creating high-resolution 3D topologies optimized for minimum compliance, significantly reducing computational costs and enabling giga-scale designs on standard PCs.

Contribution

It presents a novel de-homogenization approach that combines homogenization-based optimization with implicit geometry for detailed 3D topologies at low computational cost.

Findings

Achieves near-optimal 3D topologies with high resolution.

Reduces computational cost by three orders of magnitude.

Produces designs with objective values comparable to homogenization-based methods.

Abstract

This paper presents a highly efficient method to obtain high-resolution, near-optimal 3D topologies optimized for minimum compliance on a standard PC. Using an implicit geometry description we derive a single-scale interpretation of optimal multi-scale designs on a very fine mesh (de-homogenization). By performing homogenization-based topology optimization, optimal multi-scale designs are obtained on a relatively coarse mesh resulting in a low computational cost. As microstructure parameterization we use orthogonal rank-3 microstructures, which are known to be optimal for a single loading case. Furthermore, a method to get explicit control of the minimum feature size and complexity of the final shapes will be discussed. Numerical examples show excellent performance of these fine-scale designs resulting in objective values similar to the homogenization-based designs. Comparisons with well-established density-based topology optimization methods show a reduction in computational cost of 3 orders of magnitude, paving the way for giga-scale designs on a standard PC.