Structural topology optimization under uncertain loading

结构拓扑优化是一种灵活的工具，已被证明在概念和初步设计阶段特别有用。本计画将致力于发展不确定性负载条件下之强健结构拓扑最佳化新演算法。这是一个重要的话题，因为大多数现实世界的结构设计问题涉及的不确定性，由于在操作环境中的波动的负载条件。忽视这种不确定性可能会带来灾难性的后果，并导致不可预见的使用中故障。在这个项目中开发的算法将基于Nair教授小组开发的Anchored ANOVA Petrov-Galerkin投影方案。这项工作将扩展到处理线性弹性静力学和随机伴随灵敏度分析能力将被开发。一个水平集配方将用于发展的最佳拓扑结构和详细的数值研究将进行基准性能的算法开发的一系列问题。

Structural topology optimization is a flexible tool that has proven to be particularly useful in the conceptual and preliminary design stages. This project will be concerned with the development of new algorithms for robust structural topology optimization under uncertain loading conditions. This is an important topic since most real-world structural design problems involve uncertainty in the loading conditions due to fluctuations in the operating environment. Ignoring this uncertainty can be potentially disastrous and lead to unforeseen in-service failure. The algorithms to be developed in this project will be based on the anchored ANOVA Petrov-Galerkin projection scheme developed by Professor Nair's group. This work will be extended to deal with linear elastostatics and stochastic adjoint sensitivity analysis capabilities will be developed. A level-set formulation will used to evolve the optimal topology and detailed numerical studies will be conducted to benchmark the performance of the algorithms developed on a range of problems.