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dc.contributor.authorKang, Peter K.-
dc.contributor.authorDentz, Marco-
dc.contributor.authorLe Borgne, Tanguy-
dc.contributor.authorLee, Seunghak-
dc.contributor.authorJuanes, Ruben-
dc.date.accessioned2024-01-20T01:01:12Z-
dc.date.available2024-01-20T01:01:12Z-
dc.date.created2022-01-10-
dc.date.issued2017-08-
dc.identifier.issn0309-1708-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/122445-
dc.description.abstractWe investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that even if the Eulerian fluid velocity is steady the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes. (C) 2017 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCI LTD-
dc.subjectHETEROGENEOUS POROUS-MEDIA-
dc.subjectNON-FICKIAN TRANSPORT-
dc.subjectTIME RANDOM-WALKS-
dc.subjectSOLUTE TRANSPORT-
dc.subjectMASS-TRANSFER-
dc.subjectBOUNDARY-CONDITIONS-
dc.subjectTRACER TRANSPORT-
dc.subjectROUGH FRACTURES-
dc.subjectSINGLE FRACTURE-
dc.subjectPLUME EVOLUTION-
dc.titleAnomalous transport in disordered fracture networks: Spatial Markov model for dispersion with variable injection modes-
dc.typeArticle-
dc.identifier.doi10.1016/j.advwatres.2017.03.024-
dc.description.journalClass1-
dc.identifier.bibliographicCitationADVANCES IN WATER RESOURCES, v.106, pp.80 - 94-
dc.citation.titleADVANCES IN WATER RESOURCES-
dc.citation.volume106-
dc.citation.startPage80-
dc.citation.endPage94-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000407660800009-
dc.identifier.scopusid2-s2.0-85018688611-
dc.relation.journalWebOfScienceCategoryWater Resources-
dc.relation.journalResearchAreaWater Resources-
dc.type.docTypeArticle-
dc.subject.keywordPlusHETEROGENEOUS POROUS-MEDIA-
dc.subject.keywordPlusNON-FICKIAN TRANSPORT-
dc.subject.keywordPlusTIME RANDOM-WALKS-
dc.subject.keywordPlusSOLUTE TRANSPORT-
dc.subject.keywordPlusMASS-TRANSFER-
dc.subject.keywordPlusBOUNDARY-CONDITIONS-
dc.subject.keywordPlusTRACER TRANSPORT-
dc.subject.keywordPlusROUGH FRACTURES-
dc.subject.keywordPlusSINGLE FRACTURE-
dc.subject.keywordPlusPLUME EVOLUTION-
dc.subject.keywordAuthorDiscrete fracture networks-
dc.subject.keywordAuthorInjection modes-
dc.subject.keywordAuthorAnomalous transport-
dc.subject.keywordAuthorStochastic modeling-
dc.subject.keywordAuthorLagrangian velocity-
dc.subject.keywordAuthorTime domain random walks-
dc.subject.keywordAuthorContinuous time random walks-
dc.subject.keywordAuthorSpatial Markov model-
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