{"id":"https://openalex.org/W7150876581","doi":"https://doi.org/10.48550/arxiv.2604.02483","title":"A Multimodal Vision Transformer-based Modeling Framework for Prediction of Fluid Flows in Energy Systems","display_name":"A Multimodal Vision Transformer-based Modeling Framework for Prediction of Fluid Flows in Energy Systems","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7150876581","doi":"https://doi.org/10.48550/arxiv.2604.02483"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02483","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02483","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.02483","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059658342","display_name":"Kiran K. Yalamanchi","orcid":"https://orcid.org/0000-0002-9990-0046"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yalamanchi, Kiran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071906834","display_name":"Shivam Barwey","orcid":"https://orcid.org/0000-0002-1717-1805"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barwey, Shivam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034477822","display_name":"Ibrahim Jarrah","orcid":"https://orcid.org/0000-0001-9525-2574"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jarrah, Ibrahim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5053076543","display_name":"Pinaki Pal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pal, Pinaki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.34119999408721924,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.34119999408721924,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10553","display_name":"Combustion and flame dynamics","score":0.2434999942779541,"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":0.06289999932050705,"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/computational-fluid-dynamics","display_name":"Computational fluid dynamics","score":0.6025999784469604},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.47909998893737793},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.46810001134872437},{"id":"https://openalex.org/keywords/fluid-dynamics","display_name":"Fluid dynamics","score":0.42320001125335693},{"id":"https://openalex.org/keywords/energy-flow","display_name":"Energy flow","score":0.3677999973297119},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.36469998955726624},{"id":"https://openalex.org/keywords/turbulence","display_name":"Turbulence","score":0.34709998965263367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6830999851226807},{"id":"https://openalex.org/C1633027","wikidata":"https://www.wikidata.org/wiki/Q815820","display_name":"Computational fluid dynamics","level":2,"score":0.6025999784469604},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.47909998893737793},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46059998869895935},{"id":"https://openalex.org/C90278072","wikidata":"https://www.wikidata.org/wiki/Q216320","display_name":"Fluid dynamics","level":2,"score":0.42320001125335693},{"id":"https://openalex.org/C206815995","wikidata":"https://www.wikidata.org/wiki/Q1341307","display_name":"Energy flow","level":3,"score":0.3677999973297119},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C196558001","wikidata":"https://www.wikidata.org/wiki/Q190132","display_name":"Turbulence","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.31439998745918274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31189998984336853},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2718000113964081},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02483","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02483","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.02483","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02483","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.755073606967926,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Computational":[0],"fluid":[1,7,34,187],"dynamics":[2],"(CFD)":[3],"simulations":[4,127],"of":[5,33,128,144,185],"complex":[6,186],"flows":[8],"in":[9],"energy":[10],"systems":[11],"are":[12],"prohibitively":[13],"expensive":[14],"due":[15],"to":[16,45,151,181],"strong":[17],"nonlinearities":[18],"and":[19,36,78,103,142,155,162],"multiscale-multiphysics":[20],"interactions.":[21],"In":[22],"this":[23],"work,":[24],"we":[25],"present":[26],"a":[27,51,133],"transformer-based":[28,176],"modeling":[29,184],"framework":[30],"for":[31,39],"prediction":[32],"flows,":[35],"demonstrate":[37],"it":[38],"high-pressure":[40],"gas":[41],"injection":[42,131],"phenomena":[43],"relevant":[44],"reciprocating":[46],"engines.":[47],"The":[48,65,146],"approach":[49],"employs":[50],"hierarchical":[52],"Vision":[53],"Transformer":[54],"(SwinV2-UNet)":[55],"architecture":[56,67],"that":[57],"processes":[58],"multimodal":[59,121],"flow":[60,98,160,188],"datasets":[61,122],"from":[62,113,124,167],"multi-fidelity":[63],"simulations.":[64],"model":[66,94,109],"is":[68,83],"conditioned":[69],"on":[70,85,120],"auxiliary":[71],"tokens":[72],"explicitly":[73],"encoding":[74],"the":[75,93,97,108,159],"data":[76],"modality":[77],"time":[79],"increment.":[80],"Model":[81],"performance":[82],"assessed":[84],"two":[86],"different":[87],"tasks:":[88],"(1)":[89],"spatiotemporal":[90],"rollouts,":[91],"where":[92,107],"autoregressively":[95],"predicts":[96],"state":[99],"at":[100],"future":[101],"times;":[102],"(2)":[104],"feature":[105],"transformation,":[106],"infers":[110],"unobserved":[111],"fields/views":[112],"observed":[114],"fields/views.":[115],"We":[116],"train":[117],"separate":[118],"models":[119,149,177],"generated":[123],"in-house":[125],"CFD":[126],"argon":[129],"jet":[130],"into":[132],"nitrogen":[134],"environment,":[135],"encompassing":[136],"multiple":[137],"grid":[138],"resolutions,":[139],"turbulence":[140],"models,":[141],"equations":[143],"state.":[145],"resulting":[147],"data-driven":[148],"learn":[150],"generalize":[152],"across":[153],"resolutions":[154],"modalities,":[156],"accurately":[157],"forecasting":[158],"evolution":[161],"reconstructing":[163],"missing":[164],"flow-field":[165],"information":[166],"limited":[168],"views.":[169],"This":[170],"work":[171],"demonstrates":[172],"how":[173],"large":[174],"vision":[175],"can":[178],"be":[179],"adapted":[180],"advance":[182],"predictive":[183],"systems.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-07T00:00:00"}