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Global optimization for data assimilation in landslide tsunami models
dc.contributor.author | Ferreiro Ferreiro, Ana María | |
dc.contributor.author | García Rodríguez, José Antonio | |
dc.contributor.author | López Salas, José Germán | |
dc.contributor.author | Escalante Sánchez, Cipriano | |
dc.contributor.author | Castro Díaz, Manuel Jesús | |
dc.date.accessioned | 2024-07-19T13:02:02Z | |
dc.date.available | 2024-07-19T13:02:02Z | |
dc.date.issued | 2020-02-15 | |
dc.identifier.issn | 1090-2716 | |
dc.identifier.issn | 0021-9991 | |
dc.identifier.uri | http://hdl.handle.net/2183/38174 | |
dc.description | © 2020. This manuscript version is made available under the CC-BY-NCND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. This version of the article has been accepted for publication in Journal of Computational Physics (1090-2716). The Version of Record is available online at 10.1016/j.jcp.2019.109069. | es_ES |
dc.description.abstract | [Abstract]: The goal of this article is to make automatic data assimilation for a landslide tsunami model, given by the coupling between a non-hydrostatic multi-layer shallow-water and a Savage-Hutter granular landslide model for submarine avalanches. The coupled model is discretized using a positivity preserving second-order path-conservative finite volume scheme. Then, the data assimilation problem is posed in a global optimization framework. Later, multi-path parallel metaheuristic stochastic global optimization algorithms are developed. More precisely, a multi-path Simulated Annealing algorithm is compared with a multi-path hybrid global optimization algorithm based on coupling Simulated Annealing with gradient local searchers. | es_ES |
dc.description.sponsorship | The authors want to acknowledge the designers of the experiment [83] , for making the data publicly available. The authors also wish to thank the anonymous reviewers for their through review of the article and their constructive advises. This research has been financially supported by Spanish Government Ministerio de Economía y Competitividad through the research projects MTM2016-76497-R and MTM2015-70490-C2-1-R . | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2016-76497-R/ES/METODOS MATEMATICOS Y SIMULACION NUMERICA PARA RETOS EN FINANZAS CUANTITATIVAS, MEDIOAMBIENTE, BIOTECNOLOGIA Y EFICIENCIA INDUSTRIAL | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2013-47800-C2-1-P/ES/DESARROLLO DE SIMULADORES HIDRODINAMICOS Y MORFODINAMICOS EFICIENTES PARA LA EVALUACION Y PREVISION DE RIESGOS II | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.jcp.2019.109069 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Tsunamis | es_ES |
dc.subject | Submarine avalanches | es_ES |
dc.subject | Finite volume methods | es_ES |
dc.subject | Data assimilation | es_ES |
dc.subject | Global optimization | es_ES |
dc.subject | Parallel computing | es_ES |
dc.title | Global optimization for data assimilation in landslide tsunami models | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Journal of Computational Physics | es_ES |
UDC.volume | 403 | es_ES |
UDC.startPage | 109069 | es_ES |
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