EAGER: Accurate and Efficient Surrogate Modeling Applied to Computational Mechanics

这个早期概念探索性研究基金（EAGER）项目的目标是应用高维模型表示（HDMR）技术来构建高精度和高效的替代计算力学模型。高级计算力学模拟通常处理非常耗时的大尺度模型。HDMR技术使用系统采样程序，将原始物理模型的输出与其输入相关联，以产生高度精确且计算成本低廉的等效模型。这些低阶替代模型有望在保持原始模型精度的同时显著降低大规模模拟的成本。该方法可推广到计算力学以外的其他工程领域。这项研究有可能改变计算力学建模哲学和仿真能力的现状，并以合理的成本实现非常大规模的仿真。该方法可以有效地进行以往由于计算量大而难以进行的模拟。此外，它将为开发准确而高效的仿真方法提供新的途径。教育目标将集中在(1)培养代理建模领域的研究生和本科生，以及(2)为现有的计算力学课程开发新的课程材料。该研究融合了力学、统计学和计算方法等不同的科学和工程领域，将为本科生和研究生在最先进的计算建模和仿真方面提供丰富的教育和研究经验。

The objective of this EArly-concept Grant for Exploratory Research (EAGER) project is to apply High Dimensional Model Representation (HDMR) technique to construct highly accurate and efficient surrogate computational mechanics models. Advanced computational mechanics simulations typically deal with very large scale models that are extremely time consuming. HDMR technique uses systemic sampling procedure relating outputs of the original physical model to its inputs to produce highly accurate and computationally cheap equivalent models. These low order surrogate models are expected to dramatically reduce the cost of very large scale simulations while maintaining the accuracy of the original models. The proposed methodology is extendable to other fields of engineering besides computational mechanics.This research has the potential to transform current state of modeling philosophy and simulation capability in computational mechanics, and enable very large scale simulations at a reasonable cost. Simulations hitherto intractable due to very high computational burden can be performed efficiently with the proposed methodology. Additionally, it will provide new avenues in the development of accurate yet efficient simulation methods. Educational objectives will focus on (1) training graduate as well as undergraduate students in the area of surrogate modeling, and (2) developing new course materials for the existing courses on computational mechanics. The research being at the confluence of diverse areas of science and engineering such as mechanics, statistics and computational methods, will provide rich educational and research experiences for undergraduate and graduate students in state-of-the-art computational modeling and simulation.