Configurational-force-driven adaptive refinement and coarsening in topology optimization
Gabriel Stankiewicz, Chaitanya Dev, Paul Steinmann

TL;DR
This paper introduces a multi-level adaptive mesh refinement and coarsening strategy driven by configurational forces, based on Eshelby stress, to improve efficiency and accuracy in topology optimization, especially near design boundaries and stress-critical regions.
Contribution
It presents a novel adaptive refinement and coarsening method using configurational forces for efficient and precise topology optimization, reducing computational costs while maintaining high resolution.
Findings
Refinement along design boundaries and stress-critical regions improves structure accuracy.
Multilevel coarsening significantly reduces computational effort.
Configurational forces effectively guide adaptive mesh modifications.
Abstract
The iterative nature of topology optimization, especially in combination with nonlinear state problems, often requires the solution of thousands of linear equation systems. Furthermore, due to the pixelated design representation, the use of a fine mesh is essential to obtain geometrically well-defined structures and to accurately compute response quantities such as the von Mises stress. Therefore, the computational cost of solving a fine-mesh topology optimization problem quickly adds up. To address this challenge, we consider a multi-level adaptive refinement and coarsening strategy based on configurational forces. Configurational forces based on the Eshelby stress predict configurational changes such as crack propagation or dislocation motion. Due to a relaxation in the calculation of (Eshelby) stresses with respect to the design variables, discrete configurational forces increase not…
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