Abstract

In this paper, we introduce geometry optimization into an existing topology optimization workflow for truss structures with global stability constraints, assuming a linear buckling analysis. The design variables are the cross-sectional areas of the bars and the coordinates of the joints. This makes the optimization problem formulations highly nonlinear and yields nonconvex semidefinite programming problems, for which there are limited available numerical solvers compared with other classes of optimization problems. We present problem instances of truss geometry and topology optimization with global stability constraints solved using a standard primal-dual interior point implementation. During the solution process, both the cross-sectional areas of the bars and the coordinates of the joints are concurrently optimized. Additionally, we apply adaptive optimization techniques to allow the joints to navigate larger move limits and to improve the quality of the optimal designs.

Highlights

  • Truss design problems are often formulated based on the so-called ground structure approach (Dorn et al 1964), in which a set of joints are distributed in the design space and are connected by potential bars

  • We address truss design problems with global stability constraints using a linear buckling model that is formulated as a nonlinear semidefinite programming problem

  • We have introduced geometry optimization to an existing truss topology optimization with global stability constraints formulation, posed as a nonlinear semidefinite programming problem

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Summary

Introduction

Truss design problems are often formulated based on the so-called ground structure approach (Dorn et al 1964), in which a set of joints are distributed in the design space and are connected by potential bars. We address truss design problems with global stability constraints using a linear buckling model that is formulated as a nonlinear semidefinite programming problem Such problems have been extensively studied by Ben-Tal et al (2000), Kanno et al (2001), Levy and Su (2004), Kocvara (2002), Stingl (2006), and Evgrafov (2005) and solved, for example by Fiala et al (2013) and Kocvara and Stingl (2003), but always for cases where the nodes or joints are assumed to be fixed.

Background
The problem formulation
The primal-dual interior point framework
Numerical results
Fixed versus moving joints
Adaptive geometry and topology optimization
General comments based on the numerical experiments
Findings
Conclusions
Full Text
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