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

Ander  Gray; Alexander Wimbush; Marco de Angelis; Peter O. Hristov; Dominic Calleja; Enrique Miralles-Dolz; Roberto Rocchetta

doi:10.1016/j.ymssp.2021.108210

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

Ander Gray, Alexander Wimbush, Marco de Angelis (Corresponding author), Peter O. Hristov (Corresponding author), Dominic Calleja, Enrique Miralles-Dolz, Roberto Rocchetta (Corresponding author)

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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.

Originele taal-2	Engels
Artikelnummer	108210
Aantal pagina's	39
Tijdschrift	Mechanical Systems and Signal Processing
Volume	165
DOI's	https://doi.org/10.1016/j.ymssp.2021.108210
Status	Gepubliceerd - 15 feb. 2022

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The authors would like to thank Professor Scott Ferson, Chair of Risk and Uncertainty at the Institute for Risk and Uncertainty, University of Liverpool, in particular for his guidance, support, mentorship and seemingly bottomless knowledge of uncertainty analysis. This research was funded in part by EPSRC and ESRC CDT in Risk and Uncertainty, EP/L015927/1, EPSRC “Digital twins for improved dynamic design” EP/R006768/1, the Digital Lifecycle Twins for predictive maintenance “ITEA3-2018-17030-DayTiMe” grant, and EUROfusion Consortium and Euratom research and training programme under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the funding organisations that have supported this work.

Financiers	Financiernummer
University of Liverpool

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10.1016/j.ymssp.2021.108210Licentie: CC BY

published versionDefinitieve gepubliceerde versie, 13,6 MBLicentie: CC BY

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From inference to design: A comprehensive framework for uncertainty quantification in engineering with limited information. / Gray, Ander ; Wimbush, Alexander; de Angelis, Marco (Corresponding author) et al.
In: Mechanical Systems and Signal Processing, Vol. 165, 108210, 15.02.2022.

Onderzoeksoutput: Bijdrage aan tijdschrift › Tijdschriftartikel › Academic › peer review

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AU - Miralles-Dolz, Enrique

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

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