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dc.contributor.author | Calatayud, J. | es_ES |
dc.contributor.author | Cortés, J.-C. | es_ES |
dc.contributor.author | Dorini, F. A. | es_ES |
dc.contributor.author | Jornet, M. | es_ES |
dc.date.accessioned | 2021-03-31T03:30:40Z | |
dc.date.available | 2021-03-31T03:30:40Z | |
dc.date.issued | 2020-06 | es_ES |
dc.identifier.issn | 0378-4754 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/164755 | |
dc.description.abstract | [EN] In this paper we extend the study on the linear advection equation with independent stochastic velocity and initial condition performed in Dorini and Cunha (2011). By using both existing and novel results on the stochastic chain rule, we solve the random linear advection equation in the mean square sense. We provide a new expression for the probability density function of the solution stochastic process, which can be computed as accurately as wanted via Monte Carlo simulations, and which does not require the specific probability distribution of the integral of the velocity. This allows us to solve the non-Gaussian velocity case, which was not treated in the aforementioned contribution. Several numerical results illustrate the computations of the probability density function by using our approach. On the other hand, we derive a theoretical partial differential equation for the probability density function of the solution stochastic process. Finally, a shorter and easier derivation of the joint probability density function of the response process at two spatial points is obtained by applying conditional expectations appropriately. (C) 2019 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. | es_ES |
dc.description.sponsorship | This work has been supported by the Spanish Ministerio de Economia y Competitividad grant MTM201789664-P. The co-author Marc Jornet acknowledges the doctorate scholarship granted by Programa de Ayudas de Investigacion y Desarrollo (PAID), Universitat Politecnica de Valencia. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Mathematics and Computers in Simulation | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Random linear advection equation | es_ES |
dc.subject | Random partial differential equation | es_ES |
dc.subject | Mean square calculus | es_ES |
dc.subject | Random chain rule | es_ES |
dc.subject | Probability density function | es_ES |
dc.subject | Monte Carlo simulation | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Extending the study on the linear advection equation subject to stochastic velocity field and initial condition | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.matcom.2019.12.014 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/ | es_ES |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Calatayud, J.; Cortés, J.; Dorini, FA.; Jornet, M. (2020). Extending the study on the linear advection equation subject to stochastic velocity field and initial condition. Mathematics and Computers in Simulation. 172:159-174. https://doi.org/10.1016/j.matcom.2019.12.014 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.matcom.2019.12.014 | es_ES |
dc.description.upvformatpinicio | 159 | es_ES |
dc.description.upvformatpfin | 174 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 172 | es_ES |
dc.relation.pasarela | S\399353 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
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