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

Cataldo, Giuseppe and Qian, Elizabeth and Auclair, Jeremy (2022) Multifidelity uncertainty quantification and model validation of large-scale multidisciplinary systems. Journal of Astronomical Telescopes, Instruments, and Systems, 8 (3). Art. No. 038001. ISSN 2329-4124. doi:10.1117/1.jatis.8.3.038001.

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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.

Item Type:Article
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URLURL TypeDescription ItemRSB MFGSA approach ItemMATLAB code that implements the MFUQ method
Qian, Elizabeth0000-0001-6713-3746
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, whereas the one implementing the MFGSA strategy of Ref. 47 and the RSB MFGSA approach described in this work can be found at
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Issue or Number:3
Record Number:CaltechAUTHORS:20220726-996912000
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Official Citation:Giuseppe Cataldo, Elizabeth Qian, and Jeremy Auclair "Multifidelity uncertainty quantification and model validation of large-scale multidisciplinary systems," Journal of Astronomical Telescopes, Instruments, and Systems 8(3), 038001 (22 July 2022).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115848
Deposited By: George Porter
Deposited On:27 Jul 2022 21:31
Last Modified:27 Jul 2022 21:31

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