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：自主水下航行器艇体设计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。首先，它涉及集成所涉及的计算复杂的工程仿真工具。其次，它需要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CAD工具与CFD工具OpenFOAM以实现自动设计评估。在优化方面，我们选择了贝叶斯优化（BO），这是一种为优化耗时且昂贵的工程仿真而开发的著名技术，已在包括超参数调优和实验设计在内的多种问题中证明具有极高的样本效率。在优化过程中，我们可以将不可行设计作为约束条件纳入优化过程。通过将领域特定工具链与基于AI的优化相结合，我们实现了水下航行器艇体设计的自动优化。为了进行实证评估，我们选取了两种不同的实际水下航行器设计案例来验证我们工具的执行效果。