Abstract The need to quantify the uncertainty associated with the main design features and properties of composite laminates has been recognized by the scientific and industrial communities. Recently, robustness and reliability assessment have been combined in a structural design framework called Reliability-based Robust Design Optimization (RBRDO). However, reliability assessment is known to aggravate significantly the efficiency of evolutionary algorithms, in structural design optimization. The problem becomes particularly difficult in the design optimization of composite laminate structures. In this paper, it is proposed the application of an analytical dimensional reduction technique of the uncertainty space associated with reliability assessment, based on the approximate local solution of Sobol’ indices. This approach has a negligible computational cost. It is demonstrated that several random mechanical properties of the optimal design solutions are not important for reliability assessment and can be frozen. The proposed methodology allows the RBRDO problem to be solved much more efficiently.

中文翻译：

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降维应用于基于可靠性的复合结构鲁棒设计优化

摘要 科学界和工业界已经认识到需要量化与复合材料层压板的主要设计特征和性能相关的不确定性。最近，稳健性和可靠性评估已结合在称为基于可靠性的稳健设计优化 (RBRDO) 的结构设计框架中。然而，众所周知，在结构设计优化中，可靠性评估会显着提高进化算法的效率。该问题在复合层压结构的设计优化中变得尤为困难。在本文中，基于 Sobol 指数的近似局部解，提出了与可靠性评估相关的不确定空间的解析降维技术的应用。这种方法的计算成本可以忽略不计。结果表明，优化设计解决方案的几个随机机械特性对于可靠性评估并不重要，可以冻结。所提出的方法允许更有效地解决 RBRDO 问题。