Affiliation:
1. Institute of Artificial Intelligence, Beihang University, Beijing, China
2. Institute of Applied Physics and Computational Mathematics, Beijing, China
Abstract
Since 2000, the research of uncertainty quantification (UQ) has been successfully applied in many fields and has been highly valued and strongly supported by academia and industry. This review firstly discusses the sources and the types of uncertainties and gives an overall discussion on the goal, practical significance, and basic framework of the research of UQ. Then, the core ideas and typical methods of several important UQ processes are introduced, including sensitivity analysis, uncertainty propagation, model calibration, Bayesian inference, experimental design, surrogate model, and model uncertainty analysis.
Funder
National Numerical Wind Tunnel Project
Subject
General Engineering,General Mathematics
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