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History Matching with Subset Simulation

Gong, Z; DiazDelaO, FA; Hristov, P; Beer, M; (2021) History Matching with Subset Simulation. International Journal for Uncertainty Quantification , 11 (5) pp. 19-38. 10.1615/Int.J.UncertaintyQuantification.2021033543. Green open access

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Abstract

Computational cost often hinders the calibration of complex computer models. In this context, history matching (HM) is becoming a widespread calibration strategy, with applications in many disciplines. HM uses a statistical approximation, also known as an emulator, to the model output, in order to mitigate computational cost. The process starts with an observation of a physical system. It then produces progressively more accurate emulators to determine a non-implausible domain: a subset of the input space that provides a good agreement between the model output and the data, conditional on the model structure, the sources of uncertainty, and an implausibility measure. In HM, it is essential to generate samples from the nonimplausible domain, in order to run the model and train the emulator until a stopping condition is met. However, this sampling can be very challenging, since the nonimplausible domain can become orders of magnitude smaller than the original input space very quickly. This paper proposes a solution to this problem using subset simulation, a rare event sampling technique that works efficiently in high dimensions. The proposed approach is demonstrated via calibration and robust design examples from the field of aerospace engineering.

Type: Article
Title: History Matching with Subset Simulation
Open access status: An open access version is available from UCL Discovery
DOI: 10.1615/Int.J.UncertaintyQuantification.2021033543
Publisher version: https://doi.org/10.1615/Int.J.UncertaintyQuantific...
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: history matching, subset simulation, Gaussian process emulation, robust design
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics > Clinical Operational Research Unit
URI: https://discovery.ucl.ac.uk/id/eprint/10126802
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