Uncertainty quantification of dynamic earthquake rupture simulations

Author:

Daub Eric G.1ORCID,Arabnejad Hamid2ORCID,Mahmood Imran2,Groen Derek2

Affiliation:

1. Research Engineering Group, Alan Turing Institute, London, UK

2. Department of Computer Science, Brunel University London, London, UK

Abstract

We present a tutorial demonstration using a surrogate-model based uncertainty quantification (UQ) approach to study dynamic earthquake rupture on a rough fault surface. The UQ approach performs model calibration where we choose simulation points, fit and validate an approximate surrogate model or emulator, and then examine the input space to see which inputs can be ruled out from the data. Our approach relies on the mogp_emulator package to perform model calibration, and the FabSim3 component from the VECMA toolkit to streamline the workflow, enabling users to manage the workflow using the command line to curate reproducible simulations on local and remote resources. The tools in this tutorial provide an example template that allows domain researchers that are not necessarily experts in the underlying methods to apply them to complex problems. We illustrate the use of the package by applying the methods to dynamic earthquake rupture, which solves the elastic wave equation for the size of an earthquake and the resulting ground shaking based on the stress tensor in the Earth. We show through the tutorial results that the method is able to rule out large portions of the input parameter space, which could lead to new ways to constrain the stress tensor in the Earth based on earthquake observations. This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico ’.

Funder

Engineering and Physical Sciences Research Council

Horizon 2020 Framework Programme

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Reliability and reproducibility in computational science: implementing validation, verification and uncertainty quantification in silico;Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences;2021-03-29

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