A multi-fidelity probabilistic optimisation method for the design of composite structures subjected to thermomechanical loading is introduced in this work for the first time. The proposed multi-fidelity approach offers considerable computation efficiency as well as sufficient accuracy, enabling probabilistic optimisation to include more design variables in the early design phase. This approach incorporates both nonlinear information fusion algorithms and multi-level optimisation to achieve increased accuracy and computation time savings. In this optimisation process, a High-Fidelity Model (HFM) covers only a part of the entire design space with information collected uniformly while providing high-fidelity information of other design spaces sparsely without causing extra computational cost. Simultaneously, a Low-Fidelity Model (LFM) explores the whole design space to compensate lack of high-fidelity information. In this manner, the number of high-fidelity information to construct a multi-fidelity model is dramatically reduced. The Reliability-Based Design Optimisation (RBDO) demonstrated the proposed multi-fidelity method of a mono-stringer stiffened composite panel under thermomechanical loading using Gaussian Processes (GPs).

在这项工作中首次引入了一种用于热机械载荷复合结构设计的多保真概率优化方法。所提出的多保真方法提供了相当大的计算效率和足够的精度，使概率优化能够在早期设计阶段包括更多的设计变量。这种方法结合了非线性信息融合算法和多级优化，以提高准确性并节省计算时间。在这个优化过程中，高保真模型（HFM）仅覆盖整个设计空间的一部分，信息收集均匀，同时稀疏地提供其他设计空间的高保真信息，而不会造成额外的计算成本。同时，低保真模型 (LFM) 探索整个设计空间以弥补高保真信息的缺乏。以这种方式，用于构建多保真模型的高保真信息的数量显着减少。基于可靠性的设计优化 (RBDO) 展示了使用高斯过程 (GP) 在热机械载荷下单纵梁加筋复合板的拟议多保真方法。