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

Gray, A. and Wimbush, A. and de Angelis, M. and Hristov, P.O. and Calleja, D. and Miralles-Dolz, E. and Rocchetta, R. (2022) From inference to design : a comprehensive framework for uncertainty quantification in engineering with limited information. Mechanical Systems and Signal Processing, 165. 108210. ISSN 0888-3270 (https://doi.org/10.1016/j.ymssp.2021.108210)

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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.

ORCID iDs

Gray, A., Wimbush, A., de Angelis, M. ORCID logoORCID: https://orcid.org/0000-0001-8851-023X, Hristov, P.O., Calleja, D., Miralles-Dolz, E. and Rocchetta, R.;
CORE (COnnecting REpositories)