Finite Element-Based Structural Optimization of Large System Models Under Buckling Constraints

TL;DR

This paper develops a finite element-based optimization method for large structural systems, focusing on minimizing mass under stress and buckling constraints, with a new algorithm called eigenOpt for spacecraft fuselage design.

Contribution

Introduces a novel finite element-based optimization approach with the eigenOpt algorithm for large structures under buckling constraints.

Findings

EigenOpt effectively minimizes mass while satisfying buckling constraints.

The method improves solution accuracy and practical usability for large system models.

Analysis of existing optimization methods highlights the advantages of the new algorithm.

Abstract

Optimization of large structures of multiple components is essential to many industries for minimizing mass, especially the design of aerospace vehicles. Optimizing a single primary load member independently of all other primary structures is an incomplete process, due to the redistribution of internal loads, as the stiffness distribution changes. That is, optimizing a component changes joint loads, which then calls for a new optimization - changing internal loads changes the optimum. This is particularly evident under buckling (stability) constraints. The goal is to develop a finite element-based optimization approach which can be used to optimize each component of a large, primary structure assembly. The optimization objective function will be to minimize mass for the system, and the constraints will be both stress constraints as well as buckling constraints. The research aims to improve both the solution and practical usability of these models. The system of interest is a spacecraft fuselage, of which the member components are panels throughout the structure. We present analyses of several main optimization methods, and define a new algorithm to solve this problem, eigenOpt.