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Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model

Ji Li Orcid Logo, Zhixian Cao, Alistair G.L. Borthwick

Applied Mathematical Modelling, Volume: 99, Pages: 458 - 477

Swansea University Author: Ji Li Orcid Logo

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Abstract

All shallow water hydro-sediment-morphodynamic (SHSM) models are prone to uncertainty arising from inadequate representation of the underlying physics and error in input parameters. At the time of writing, most SHSM models solve deterministic problems, whilst studies of uncertainty quantification in...

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Published in: Applied Mathematical Modelling
ISSN: 0307-904X
Published: Elsevier BV 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa57284
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spelling 2021-08-03T17:29:25.2037477 v2 57284 2021-07-08 Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model 4123c4ddbcd6e77f580974c661461c7c 0000-0003-4328-3197 Ji Li Ji Li true false 2021-07-08 CIVL All shallow water hydro-sediment-morphodynamic (SHSM) models are prone to uncertainty arising from inadequate representation of the underlying physics and error in input parameters. At the time of writing, most SHSM models solve deterministic problems, whilst studies of uncertainty quantification in SHSM models remain rare. Here a new stochastic SHSM model is proposed, extended from a well-balanced, operator-splitting-based, generalized polynomial chaos stochastic Galerkin (gPC-SG) solver of the one-dimensional shallow water hydrodynamic equations. A series of probabilistic numerical tests are carried out, corresponding to idealized test of dam break flow over a fixed bed and laboratory experiments of flow-sediment-bed evolutions induced by a sudden dam break and by landslide dam failure. The proposed modelling framework shows promise for uncertainty quantification of shallow water-sediment flows over erodible beds. Journal Article Applied Mathematical Modelling 99 458 477 Elsevier BV 0307-904X uncertainty quantification, shallow water hydro-sediment-morphodynamic model, operator-splitting, generalized polynomial chaos, stochastic Galerkin method 1 11 2021 2021-11-01 10.1016/j.apm.2021.06.031 COLLEGE NANME Civil Engineering COLLEGE CODE CIVL Swansea University 2021-08-03T17:29:25.2037477 2021-07-08T11:51:15.8596826 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Ji Li 0000-0003-4328-3197 1 Zhixian Cao 2 Alistair G.L. Borthwick 3 57284__20362__1b02ea8a991b4142a8cce0de3714825c.pdf 57284.pdf 2021-07-08T11:53:49.3396951 Output 1368851 application/pdf Accepted Manuscript true 2022-07-07T00:00:00.0000000 Released under the terms of a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License true eng http://creativecommons.org/licenses/by-nc-nd/4.0/
title Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
spellingShingle Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
Ji Li
title_short Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
title_full Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
title_fullStr Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
title_full_unstemmed Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
title_sort Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model
author_id_str_mv 4123c4ddbcd6e77f580974c661461c7c
author_id_fullname_str_mv 4123c4ddbcd6e77f580974c661461c7c_***_Ji Li
author Ji Li
author2 Ji Li
Zhixian Cao
Alistair G.L. Borthwick
format Journal article
container_title Applied Mathematical Modelling
container_volume 99
container_start_page 458
publishDate 2021
institution Swansea University
issn 0307-904X
doi_str_mv 10.1016/j.apm.2021.06.031
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
document_store_str 1
active_str 0
description All shallow water hydro-sediment-morphodynamic (SHSM) models are prone to uncertainty arising from inadequate representation of the underlying physics and error in input parameters. At the time of writing, most SHSM models solve deterministic problems, whilst studies of uncertainty quantification in SHSM models remain rare. Here a new stochastic SHSM model is proposed, extended from a well-balanced, operator-splitting-based, generalized polynomial chaos stochastic Galerkin (gPC-SG) solver of the one-dimensional shallow water hydrodynamic equations. A series of probabilistic numerical tests are carried out, corresponding to idealized test of dam break flow over a fixed bed and laboratory experiments of flow-sediment-bed evolutions induced by a sudden dam break and by landslide dam failure. The proposed modelling framework shows promise for uncertainty quantification of shallow water-sediment flows over erodible beds.
published_date 2021-11-01T04:12:54Z
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score 11.017731