An efficient framework for robust topology optimization of fully coupled exterior vibro-acoustic systems with hybrid uncertainties

This study proposes a novel efficient framework for robust topology optimization of fully coupled exterior vibro-acoustic systems with hybrid random-interval uncertainties, utilizing the finite element method-boundary element method. For hybrid uncertainty quantification, the polynomial chaos-Chebyshev interval (PCCI) method has been widely adopted. However, the application of conventional PCCI method is severely limited by the prohibitive computational cost caused by a large number of sampling points. To overcome this bottleneck, Bayesian compressive sensing is introduced to establish a sparse PCCI method, thereby reducing the heavy computational burden associated with hybrid uncertainty quantification. Furthermore, a multi-resolution strategy is adopted to decouple the design mesh from the analysis mesh. Within this strategy, a fine design mesh ensures high-quality material distributions, while a coarse analysis mesh provides further acceleration in the overall evaluation. The combination of these two approaches enables high computational efficiency of the proposed framework under hybrid uncertainty conditions, thereby yielding robust optimized designs with high resolution. The efficacy of the framework is comprehensively validated through a series of numerical examples, demonstrating its strong ability to guide the robust optimized design of fully coupled exterior vibro-acoustic systems operating in complex uncertain environments.