一种基于高保真流固耦合仿真的设计方法
A Principled Approach to Design Using High Fidelity Fluid-Structure Interaction Simulations
摘要：
高保真度流体-结构相互作用模拟可能需要在数百个岩心上运行许多天。当可能需要重复这种模拟时（例如，出于设计优化的目的），这在时间和经济考虑方面造成了严重的负担。在本文中，我们提出了基于（约束）贝叶斯优化（BO）的战略，以减轻这种负担。BO是一种基于高斯过程（GP）的数值优化技术，能够有效地（对昂贵的FSI模型的调用最少）收敛到一些全局最优设计，如使用黑箱目标函数所衡量的。在这项研究中，我们提出了一个原则性的设计演变，从FSI模型验证，通过一系列的桥梁模拟（使验证情况逐步接近应用程序），以便我们可以识别水下，无人驾驶，自主车辆（UUAV）帆飞机的材料属性。我们能够实现快速收敛到最佳设计，使用少量的FSI模拟（最多十几个），即使在选择多个设计参数，同时尊重优化约束。
英文摘要：
A high fidelity fluid-structure interaction simulation may require many days to run, on hundreds of cores. This poses a serious burden, both in terms of time and economic considerations, when repetitions of such simulations may be required (e.g. for the purpose of design optimization). In this paper we present strategies based on (constrained) Bayesian optimization (BO) to alleviate this burden. BO is a numerical optimization technique based on Gaussian processes (GP) that is able to efficiently (with minimal calls to the expensive FSI models) converge towards some globally optimal design, as gauged using a black box objective function. In this study we present a principled design evolution that moves from FSI model verification, through a series of Bridge Simulations (bringing the verification case incrementally closer to the application), in order that we may identify material properties for an underwater, unmanned, autonomous vehicle (UUAV) sail plane. We are able to achieve fast convergence towards an optimal design, using a small number of FSI simulations (a dozen at most), even when selecting over several design parameters, and while respecting optimization constraints.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
