Mathematical and computational modeling of membrane distillation technology: a data-driven review

Membrane distillation (MD) technology is increasingly gaining attention as an environmentally sustainable water treatment method of emerging interest. During last three decades there has been wide efforts to model and improve the performance of this technology. In this study we examine both the math...

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Detalles Bibliográficos
Autores: Aytaç, Ersin, Contreras Martínez, Jorge, Khayet Souhaimi, Mohamed
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/129633
Acceso en línea:https://hdl.handle.net/20.500.14352/129633
Access Level:acceso abierto
Palabra clave:536
628.165
66.049
Membrane distillation
Bibliometric analysis
Data-driven approach
Data mining
Data analysis
Computational modeling
Mathematical modeling
Ciencias
2213 Termodinámica
33 Ciencias Tecnológicas
2210.19 Fenómenos de Membrana
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oai_identifier_str oai:docta.ucm.es:20.500.14352/129633
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repository_id_str
spelling Mathematical and computational modeling of membrane distillation technology: a data-driven reviewAytaç, ErsinContreras Martínez, JorgeKhayet Souhaimi, Mohamed536628.16566.049Membrane distillationBibliometric analysisData-driven approachData miningData analysisComputational modelingMathematical modelingCiencias2213 Termodinámica33 Ciencias Tecnológicas2210.19 Fenómenos de MembranaMembrane distillation (MD) technology is increasingly gaining attention as an environmentally sustainable water treatment method of emerging interest. During last three decades there has been wide efforts to model and improve the performance of this technology. In this study we examine both the mathematical and computational modeling methods used in MD with a data-driven method. To gather the dataset, a broad range of terms related with theoretical modeling of MD were searched in the Scopus database. The collection consists of 526 documents including 116 journals, 14,291 references used by authors, 1252 involved authors and 29.47 % international co-authorship rate. The overall pattern of publications is found to increase over time indicating the enhancing interest on theoretical modeling of MD process. Journal of Membrane Science and Desalination are the top two journals publishing theoretical modeling of MD, with 105 and 100 articles, respectively. Dr. Ghaffour N. contributed with the highest number of articles, 24; and Dr. Khayet M. has the highest articles fractionalized value with 7.08. The dataset was categorized first into mathematical and computational modeling, then into the used mass transport approaches through membrane hydrophobic pores. Recently, in MD field computational modeling has been considered more than mathematical modeling. The combined Knudsen diffusion/ordinary molecular diffusion model is the dominant mass transport approach considered in MD mathematical modeling with 117 articles. On the other hand, computational fluid dynamics is the most used computational method with 114 articles.ElsevierUniversidad Complutense de Madrid20242024-02-0120242024-02-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/129633reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/1296332026-06-02T12:44:21Z
dc.title.none.fl_str_mv Mathematical and computational modeling of membrane distillation technology: a data-driven review
title Mathematical and computational modeling of membrane distillation technology: a data-driven review
spellingShingle Mathematical and computational modeling of membrane distillation technology: a data-driven review
Aytaç, Ersin
536
628.165
66.049
Membrane distillation
Bibliometric analysis
Data-driven approach
Data mining
Data analysis
Computational modeling
Mathematical modeling
Ciencias
2213 Termodinámica
33 Ciencias Tecnológicas
2210.19 Fenómenos de Membrana
title_short Mathematical and computational modeling of membrane distillation technology: a data-driven review
title_full Mathematical and computational modeling of membrane distillation technology: a data-driven review
title_fullStr Mathematical and computational modeling of membrane distillation technology: a data-driven review
title_full_unstemmed Mathematical and computational modeling of membrane distillation technology: a data-driven review
title_sort Mathematical and computational modeling of membrane distillation technology: a data-driven review
dc.creator.none.fl_str_mv Aytaç, Ersin
Contreras Martínez, Jorge
Khayet Souhaimi, Mohamed
author Aytaç, Ersin
author_facet Aytaç, Ersin
Contreras Martínez, Jorge
Khayet Souhaimi, Mohamed
author_role author
author2 Contreras Martínez, Jorge
Khayet Souhaimi, Mohamed
author2_role author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 536
628.165
66.049
Membrane distillation
Bibliometric analysis
Data-driven approach
Data mining
Data analysis
Computational modeling
Mathematical modeling
Ciencias
2213 Termodinámica
33 Ciencias Tecnológicas
2210.19 Fenómenos de Membrana
topic 536
628.165
66.049
Membrane distillation
Bibliometric analysis
Data-driven approach
Data mining
Data analysis
Computational modeling
Mathematical modeling
Ciencias
2213 Termodinámica
33 Ciencias Tecnológicas
2210.19 Fenómenos de Membrana
description Membrane distillation (MD) technology is increasingly gaining attention as an environmentally sustainable water treatment method of emerging interest. During last three decades there has been wide efforts to model and improve the performance of this technology. In this study we examine both the mathematical and computational modeling methods used in MD with a data-driven method. To gather the dataset, a broad range of terms related with theoretical modeling of MD were searched in the Scopus database. The collection consists of 526 documents including 116 journals, 14,291 references used by authors, 1252 involved authors and 29.47 % international co-authorship rate. The overall pattern of publications is found to increase over time indicating the enhancing interest on theoretical modeling of MD process. Journal of Membrane Science and Desalination are the top two journals publishing theoretical modeling of MD, with 105 and 100 articles, respectively. Dr. Ghaffour N. contributed with the highest number of articles, 24; and Dr. Khayet M. has the highest articles fractionalized value with 7.08. The dataset was categorized first into mathematical and computational modeling, then into the used mass transport approaches through membrane hydrophobic pores. Recently, in MD field computational modeling has been considered more than mathematical modeling. The combined Knudsen diffusion/ordinary molecular diffusion model is the dominant mass transport approach considered in MD mathematical modeling with 117 articles. On the other hand, computational fluid dynamics is the most used computational method with 114 articles.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-02-01
2024
2024-02-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/129633
url https://hdl.handle.net/20.500.14352/129633
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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