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Published July 2022 | Published
Journal Article Open

Multifidelity uncertainty quantification and model validation of large-scale multidisciplinary systems


A simulation-based framework for multifidelity uncertainty quantification is presented, which informs and guides the design process of complex, large-scale, multidisciplinary systems throughout their life cycle. In this framework, uncertainty in system models is identified, characterized, and propagated in an integrated manner through the analysis cycles needed to quantify the effects of uncertainty on the quantities of interest. This is part of the process to design systems and verify their compliance to performance requirements. Uncertainty quantification is performed through mean and variance estimators as well as global sensitivity analyses. These computational analyses are made tractable by the use of multifidelity methods, which leverage a variety of low-fidelity models to obtain speed-ups, while keeping the main high-fidelity model in the loop to guarantee convergence to the correct result. This framework was applied to the James Webb Space Telescope observatory integrated model used to calculate the wavefront error caused by thermal distortions. The framework proved to reduce the time required to perform global sensitivity analyses from more than 2 months to less than 2 days, while reducing the error in the final estimates of the quantities of interest, including model uncertainty factors. These technical performance improvements are crucial to the optimization of project resources such as schedule and budget and ultimately mission success.

Additional Information

© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE). Received: 15 December 2021; Accepted: 30 June 2022; Published: 22 July 2022. The material was based upon work supported by the National Aeronautics and Space Administration (NASA) under Award No. 80GSFC21M0002. The authors gratefully acknowledge the support provided by Enzo Kim in the development of the rank statistics-based GSA code, Christopher P. May in running the required TSS simulations, and Gary E. Mosier, Malcolm B. Nieder, and S. Harvey Moseley for their technical expertise and advice. GC also thanks the University of Maryland, Baltimore County for administering his appointment at the NASA Goddard Space Flight Center. The authors have no relevant financial interests in the manuscript and no other potential conflicts of interest to disclose. Code, Data, and Materials Availability. MATLAB code that implements the MFUQ method of Ref. 36 is available in a Github repository at https://github.com/pehersto/mfmc, whereas the one implementing the MFGSA strategy of Ref. 47 and the RSB MFGSA approach described in this work can be found at https://github.com/elizqian/mfgsa.

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August 22, 2023
October 23, 2023