Automatic underwater vehicle hull Design optimization is a complex engineering process for generating a UUV hull with optimized properties on a given requirement. First, it involves the integration of involved computationally complex engineering simulation tools. Second, it needs integration of a sample efficient optimization framework with the integrated toolchain. To this end, we integrated the CAD tool called FreeCAD with CFD tool openFoam for automatic design evaluation. For optimization, we chose Bayesian optimization (BO), which is a well-known technique developed for optimizing time-consuming expensive engineering simulations and has proven to be very sample efficient in a variety of problems, including hyper-parameter tuning and experimental design. During the optimization process, we can handle infeasible design as constraints integrated into the optimization process. By integrating domain-specific toolchain with AI-based optimization, we executed the automatic design optimization of underwater vehicle hull design. For empirical evaluation, we took two different use cases of real-world underwater vehicle design to validate the execution of our tool.

翻译：自主水下航行器（UUV）艇体设计的优化是一个复杂的工程过程，旨在根据给定需求生成具有优化性能的UUV艇体。该过程首先需要整合涉及计算复杂度高的工程仿真工具，其次需将样本高效的优化框架与集成工具链相结合。为此，我们集成了名为FreeCAD的计算机辅助设计工具与开源计算流体力学工具OpenFOAM，用于自动设计评估。在优化方面，我们选择贝叶斯优化（BO）——这是一种为优化耗时且昂贵的工程仿真而开发的成熟技术，已在超参数调优和实验设计等多种问题中展现出极高的样本效率。在优化过程中，通过将不可行的设计作为约束条件集成到优化框架中，可以对这些设计进行处理。通过将特定领域工具链与基于人工智能的优化相结合，我们实现了水下航行器艇体设计的自动化优化。为进行实证评估，我们选取了两种真实世界的水下航行器设计用例，以验证该工具的执行性能。