SIAM/ASA Journal on Uncertainty Quantification, Volume 9, Issue 2, Page 483-506, January 2021.
Computer simulations of physical systems are commonly used to improve system performance via optimizing the system design. We study the case when, in addition to the simulation, a limited amount of experimental data is collected from the real physical system. This article describes a method for selecting a conservative system design that is robust to uncertainty from the simulation parameters and simulation bias. The concept is that each potential system design is assigned a worst-case scenario in a data-driven feasible region. The conservative system design is then chosen as the best of the worst-cases. The method is shown to have good statistical properties. A case study is performed where a vehicle safety belt design is chosen to minimize the impact of vehicle crashes on a driver.

中文翻译：

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具有有限实验数据和不精确仿真模型的鲁棒系统设计

SIAM / ASA不确定性量化期刊，第9卷，第2期，第483-506页，2021年1月。
物理系统的计算机仿真通常用于通过优化系统设计来提高系统性能。我们研究的情况是，除了模拟之外，还从真实的物理系统中收集了有限的实验数据。本文介绍了一种选择保守系统设计的方法，该系统设计对来自仿真参数和仿真偏差的不确定性具有鲁棒性。其概念是，在数据驱动的可行区域中，为每个潜在的系统设计分配最坏的情况。然后选择保守的系统设计作为最坏情况下的最佳选择。该方法显示具有良好的统计特性。在进行案例研究的情况下，选择了车辆安全带设计以最大程度地减少撞车事故对驾驶员的影响。