Abstract

The archetypical topology optimization problem concerns designing the layout of material within a given region of space so that some performance measure is extremized. To improve manufacturability and reduce manufacturing costs, restrictions on the possible layouts may be imposed. Among such restrictions, constraining the minimum length scales of different regions of the design has a significant place. Within the density filter based topology optimization framework the most commonly used definition is that a region has a minimum length scale not less than D if any point within that region lies within a sphere with diameterD > 0 that is completely contained in the region. In this paper, we propose a variant of this minimum length scale definition for subsets of a convex (possibly bounded) domain. We show that sets with positive minimum length scale are characterized as being morphologically open. As a corollary, we find that sets where both the interior and the exterior have positive minimum length scales are characterized as being simultaneously morphologically open and (essentially) morphologically closed. For binary designs in the discretized setting, the latter translates to that the opening of the design should equal the closing of the design. To demonstrate the capability of the developed theory, we devise a method that heuristically promotes designs that are binary and have positive minimum length scales (possibly measured in different norms) on both phases for minimum compliance problems. The obtained designs are almost binary and possess minimum length scales on both phases.

Highlights

  • Given a region of space ⊂ Rd, topology optimization aims at determining the layout of material that extremizes a given performance measure

  • We propose definition (31) of the NEighborhood based minimum Length scale (NEL) that is similar to definition (1) of Zhang et al (2014); the main difference lies in the treatment of regions that are close to the boundary of the design domain

  • We show that subsets with positive NEL are characterized as being morphologically open

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Summary

Introduction

Given a region of space ⊂ Rd , topology optimization aims at determining the layout of material that extremizes a given performance measure. In a typical topology optimization problem there are two phases of material, for convenience referred to as material and void, to be distributed within the design domain. The objective is to find a region M ⊂ such that M is occupied by material and V = \ M is occupied by void. Responsible Editor: Hae Chang Gea. In density based topology optimization, M ⊂ is represented by its characteristic function 1M : → {0, 1}—often referred to as the material indicator function. To utilize gradient based optimization algorithms, which are suitable for handling the large-scale problem obtained after discretization, the range of the material indicator function is relaxed to [0, 1]. The relaxed material indicator function ρ : → [0, 1] is referred to as the density.

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