基于有限元的大型系统模型在屈曲约束下的结构优化
Finite Element-Based Structural Optimization of Large System Models Under Buckling Constraints
AI总结：
本文提出基于有限元的结构优化方法，用于优化大型系统各组件，在考虑应力和屈曲约束下最小化质量。
摘要：
优化大型多组件结构对于许多行业至关重要，以最小化质量，特别是在航天器设计中。单独优化一个主要载荷成员而忽略其他主要结构是不完整的，因为内部载荷会重新分布，当刚度分布变化时。也就是说，优化一个组件会改变接合载荷，从而需要新的优化——改变内部载荷会改变最优解。这在屈曲（稳定性）约束下尤为明显。目标是开发一种基于有限元的优化方法，用于优化大型主结构装配的每个组件。优化目标函数将为系统最小化质量，约束将包括应力约束以及屈曲约束。研究旨在提高这些模型的解决方案和实际可用性。感兴趣的系统是航天器机翼舱，其成员组件在整个结构中都是面板。我们分析了几种主要的优化方法，并定义了一种新的算法来解决这个问题，称为eigenOpt。
英文摘要：
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.
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