{"id":"https://openalex.org/W4403534919","doi":"https://doi.org/10.1109/codit62066.2024.10708600","title":"A Machine Learning Approach of MHD Stokes Flow in a Lid-Driven Cavity<sup>*</sup>","display_name":"A Machine Learning Approach of MHD Stokes Flow in a Lid-Driven Cavity<sup>*</sup>","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4403534919","doi":"https://doi.org/10.1109/codit62066.2024.10708600"},"language":"en","primary_location":{"id":"doi:10.1109/codit62066.2024.10708600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit62066.2024.10708600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042568878","display_name":"Merve G\u00fcrb\u00fcz","orcid":"https://orcid.org/0000-0002-7746-9005"},"institutions":[{"id":"https://openalex.org/I4210115299","display_name":"TED University","ror":"https://ror.org/0285rh439","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210115299"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Merve Gurbuz-Caldag","raw_affiliation_strings":["TED University,Department of Mathematics,Ankara,Turkey,06420"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TED University,Department of Mathematics,Ankara,Turkey,06420","institution_ids":["https://openalex.org/I4210115299"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052097232","display_name":"Bengisen Pekmen","orcid":"https://orcid.org/0000-0002-3073-6284"},"institutions":[{"id":"https://openalex.org/I4210115299","display_name":"TED University","ror":"https://ror.org/0285rh439","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210115299"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Bengisen Pekmen","raw_affiliation_strings":["TED University,Department of Mathematics,Ankara,Turkey,06420"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TED University,Department of Mathematics,Ankara,Turkey,06420","institution_ids":["https://openalex.org/I4210115299"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210115299"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"140","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11751","display_name":"Lattice Boltzmann Simulation Studies","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11751","display_name":"Lattice Boltzmann Simulation Studies","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9143999814987183,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/magnetohydrodynamics","display_name":"Magnetohydrodynamics","score":0.7569544315338135},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5542360544204712},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49463364481925964},{"id":"https://openalex.org/keywords/mechanics","display_name":"Mechanics","score":0.4120576083660126},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.4095505475997925},{"id":"https://openalex.org/keywords/plasma","display_name":"Plasma","score":0.1459067463874817},{"id":"https://openalex.org/keywords/nuclear-physics","display_name":"Nuclear physics","score":0.0967542827129364}],"concepts":[{"id":"https://openalex.org/C31532427","wikidata":"https://www.wikidata.org/wiki/Q2549249","display_name":"Magnetohydrodynamics","level":3,"score":0.7569544315338135},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5542360544204712},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49463364481925964},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.4120576083660126},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.4095505475997925},{"id":"https://openalex.org/C82706917","wikidata":"https://www.wikidata.org/wiki/Q10251","display_name":"Plasma","level":2,"score":0.1459067463874817},{"id":"https://openalex.org/C185544564","wikidata":"https://www.wikidata.org/wiki/Q81197","display_name":"Nuclear physics","level":1,"score":0.0967542827129364}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/codit62066.2024.10708600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit62066.2024.10708600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1979530751","https://openalex.org/W1987040419","https://openalex.org/W1997218405","https://openalex.org/W2010071402","https://openalex.org/W2032998436","https://openalex.org/W2052845102","https://openalex.org/W2077044530","https://openalex.org/W2513891077","https://openalex.org/W2517752774","https://openalex.org/W2963056712","https://openalex.org/W3080730553","https://openalex.org/W4205706796","https://openalex.org/W4224022852","https://openalex.org/W4316813550","https://openalex.org/W4381162086","https://openalex.org/W4388582099"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2935759653","https://openalex.org/W3105167352","https://openalex.org/W54078636","https://openalex.org/W2954470139","https://openalex.org/W1501425562","https://openalex.org/W2902782467","https://openalex.org/W3084825885"],"abstract_inverted_index":{"In":[0,104],"this":[1],"study,":[2],"the":[3,11,27,36,54,67,75,82,99,107,120,124,133,140,151],"trilayer":[4],"neural":[5],"network":[6],"(TNN)":[7],"is":[8,51,64,145],"generated":[9],"for":[10,35,90],"prediction":[12],"of":[13,18,46,59,74,93,116,126,136,142,154,157],"some":[14],"chosen":[15],"problem":[16],"variables":[17,109,122],"Stokes":[19,49,158],"flow":[20,50],"in":[21,96,102],"a":[22],"lid-driven":[23],"cavity":[24],"subjected":[25],"to":[26,42,66],"uniform":[28],"magnetic":[29,117],"field":[30],"with":[31],"an":[32],"inclination":[33,100,114],"angle":[34,101,115],"first":[37],"time.":[38],"The":[39,57,85],"data":[40],"set":[41],"develop":[43],"TNN":[44,105,148],"model":[45,149],"magnetohydrodynamics":[47],"(MHD)":[48],"gathered":[52],"from":[53],"numerical":[55,86],"results.":[56],"method":[58],"approximate":[60],"particular":[61],"solution":[62],"(MAPS)":[63],"employed":[65],"nondimensional":[68],"governing":[69],"equations":[70,77,80],"which":[71],"are":[72,88,110,123],"comprised":[73],"Navier-Stokes":[76],"and":[78,98,113,119,129,139],"Maxwell":[79],"neglecting":[81],"convective":[83],"terms.":[84],"outcomes":[87],"obtained":[89],"several":[91],"values":[92],"Hartmann":[94,111],"number":[95,112],"[0,100]":[97],"[0,\u03c0].":[103],"model,":[106],"input":[108],"field,":[118],"output":[121],"norm":[125,141],"stream":[127],"function":[128],"v":[130],"velocity":[131,138,155],"component,":[132],"minimum":[134],"value":[135],"u":[137],"vorticity.":[143],"It":[144],"shown":[146],"that":[147],"gives":[150],"efficient":[152],"predictions":[153],"indicators":[156],"flow.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}