From inference to design: A comprehensive framework for uncertainty quantification in engineering with limited information

作者：Ander Gray, Alexander Wimbush, M. D. Angelis, P. O. Hristov, Dominic Calleja, Enrique Miralles-Dolz, Roberto Rocchetta · 年份：2022 · DOI：10.1016/j.ymssp.2021.108210 · 被引用次数：43 · 研究领域：Computer Science

Abstract In this paper we present a framework for addressing a variety of engineering design challenges with limited empirical data and partial information. This framework includes guidance on the characterisation of a mixture of uncertainties, efficient methodologies to integrate data into design decisions, and to conduct reliability analysis, and risk/reliability based design optimisation. To demonstrate its efficacy, the framework has been applied to the NASA 2020 uncertainty quantification challenge. The results and discussion in the paper are with respect to this application.