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Uncertainty quantification of dynamic earthquake rupture simulations

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 em...

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Detalles Bibliográficos
Autores principales: Daub, Eric G., Arabnejad, Hamid, Mahmood, Imran, Groen, Derek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059650/
https://www.ncbi.nlm.nih.gov/pubmed/33775142
http://dx.doi.org/10.1098/rsta.2020.0076
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author Daub, Eric G.
Arabnejad, Hamid
Mahmood, Imran
Groen, Derek
author_facet Daub, Eric G.
Arabnejad, Hamid
Mahmood, Imran
Groen, Derek
author_sort Daub, Eric G.
collection PubMed
description 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’.
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spelling pubmed-80596502022-02-02 Uncertainty quantification of dynamic earthquake rupture simulations Daub, Eric G. Arabnejad, Hamid Mahmood, Imran Groen, Derek Philos Trans A Math Phys Eng Sci Articles 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’. The Royal Society Publishing 2021-05-17 2021-03-29 /pmc/articles/PMC8059650/ /pubmed/33775142 http://dx.doi.org/10.1098/rsta.2020.0076 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Daub, Eric G.
Arabnejad, Hamid
Mahmood, Imran
Groen, Derek
Uncertainty quantification of dynamic earthquake rupture simulations
title Uncertainty quantification of dynamic earthquake rupture simulations
title_full Uncertainty quantification of dynamic earthquake rupture simulations
title_fullStr Uncertainty quantification of dynamic earthquake rupture simulations
title_full_unstemmed Uncertainty quantification of dynamic earthquake rupture simulations
title_short Uncertainty quantification of dynamic earthquake rupture simulations
title_sort uncertainty quantification of dynamic earthquake rupture simulations
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059650/
https://www.ncbi.nlm.nih.gov/pubmed/33775142
http://dx.doi.org/10.1098/rsta.2020.0076
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