{"id":"https://openalex.org/W4389428543","doi":"https://doi.org/10.1109/access.2023.3340627","title":"Real-Time Hybrid Modeling of Francis Hydroturbine Dynamics via a Neural Controlled Differential Equation Approach","display_name":"Real-Time Hybrid Modeling of Francis Hydroturbine Dynamics via a Neural Controlled Differential Equation Approach","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4389428543","doi":"https://doi.org/10.1109/access.2023.3340627"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3340627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3340627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10347184.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10347184.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100369619","display_name":"Hong Wang","orcid":"https://orcid.org/0000-0002-9876-0176"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]},{"id":"https://openalex.org/I1309980932","display_name":"National Transportation Research Center","ror":"https://ror.org/011fc0n53","country_code":"US","type":"government","lineage":["https://openalex.org/I1309980932"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Wang","raw_affiliation_strings":["Energy and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-9876-0176","affiliations":[{"raw_affiliation_string":"Energy and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA","institution_ids":["https://openalex.org/I1289243028","https://openalex.org/I1309980932"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074154054","display_name":"Zhun Yin","orcid":"https://orcid.org/0000-0002-3159-7319"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhun Yin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New York University, Brooklyn, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-3159-7319","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067046312","display_name":"Zhong\u2010Ping Jiang","orcid":"https://orcid.org/0000-0002-4868-9359"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhong-Ping Jiang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New York University, Brooklyn, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-4868-9359","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0333,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74186525,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"11","issue":null,"first_page":"139133","last_page":"139146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T11372","display_name":"Hydraulic and Pneumatic Systems","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T11202","display_name":"Cavitation Phenomena in Pumps","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7053600549697876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6812903881072998},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6652228236198425},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.636981189250946},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6095568537712097},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6075624227523804},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5672248005867004},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.48354148864746094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4315928518772125},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41780099272727966},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.32774919271469116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16932028532028198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053600549697876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6812903881072998},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6652228236198425},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.636981189250946},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6095568537712097},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6075624227523804},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5672248005867004},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.48354148864746094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4315928518772125},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41780099272727966},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.32774919271469116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16932028532028198},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/access.2023.3340627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3340627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10347184.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f1f977a810934cafbba07880db4b8c71","is_oa":true,"landing_page_url":"https://doaj.org/article/f1f977a810934cafbba07880db4b8c71","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 139133-139146 (2023)","raw_type":"article"},{"id":"pmh:oai:osti.gov:2228975","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2228975","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"pmh:oai:osti.gov:2234314","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2234314","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"pmh:oai:osti.gov:2251618","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2251618","pdf_url":null,"source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"doi:10.1109/access.2023.3340627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3340627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10347184.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320337675","display_name":"Water Power Technologies Office","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389428543.pdf","grobid_xml":"https://content.openalex.org/works/W4389428543.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1587799944","https://openalex.org/W1778575788","https://openalex.org/W2026009629","https://openalex.org/W2110485445","https://openalex.org/W2146292423","https://openalex.org/W2194775991","https://openalex.org/W2766489112","https://openalex.org/W2903448084","https://openalex.org/W2904861519","https://openalex.org/W3003257820","https://openalex.org/W3005071597","https://openalex.org/W3011872312","https://openalex.org/W3150635270","https://openalex.org/W3158279880","https://openalex.org/W3163993681","https://openalex.org/W3199233901","https://openalex.org/W4210678178","https://openalex.org/W4224030084","https://openalex.org/W4239758949","https://openalex.org/W4253662955","https://openalex.org/W4288039037","https://openalex.org/W4306703266","https://openalex.org/W4367846823","https://openalex.org/W4385740522","https://openalex.org/W6736057607","https://openalex.org/W6752307458","https://openalex.org/W6757223306","https://openalex.org/W6760842081","https://openalex.org/W6778353478","https://openalex.org/W6785446266","https://openalex.org/W6846620194"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3099765033","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2150029999","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3,25,58],"learning":[4,10,26,59,101,123,134,157],"has":[5,66,141,230],"been":[6,67,142,231],"widely":[7],"applied":[8],"to":[9,42,69,146,195,209,214],"nonlinear":[11,46,73,149,162,187],"dynamic":[12],"models":[13],"for":[14,92,219],"the":[15,71,87,93,96,109,113,129,132,148,152,156,160,165,173,179,197,203,223,234,237,242],"development":[16,88],"of":[17,75,83,89,112,131,138,151,159,222,236],"a":[18,56,99,116,118,136,211,216],"digital":[19],"twin":[20],"system.":[21],"However,":[22],"most":[23],"traditional":[24],"frameworks,":[27],"such":[28],"as":[29],"recurrent":[30],"neural":[31,34,62,225],"networks,":[32,35],"convolutional":[33],"and":[36,45,144,168],"multilayer":[37],"perceptrons,":[38],"find":[39],"it":[40],"difficult":[41],"learn":[43,184],"continuous-time":[44,77],"system":[47,94],"models.":[48],"To":[49,127],"address":[50,196],"this":[51,54],"challenge,":[52],"in":[53,80,189],"paper,":[55],"novel":[57],"method":[60,181],"called":[61],"controlled":[63,76,226],"differential":[64,227],"equation":[65],"proposed":[68,133,180,224],"model":[70,111],"unknown":[72,186],"dynamics":[74,150,188],"systems":[78],"seen":[79],"Francis":[81,153],"hydroturbines":[82],"hydropower":[84],"systems.":[85],"Following":[86],"discretized-model":[90],"structures":[91],"using":[95,172],"first":[97],"principles,":[98],"detailed":[100],"algorithm":[102],"is":[103,106,125],"formulated":[104],"that":[105,178,200,233],"integrated":[107],"with":[108,121],"physical":[110],"hydroturbine.":[114],"As":[115],"result,":[117],"hybrid":[119],"modeling":[120],"effective":[122],"capability":[124],"obtained.":[126],"test":[128],"effectiveness":[130],"algorithm,":[135],"set":[137],"operational":[139],"data":[140,175],"collected":[143],"used":[145],"train":[147],"hydroturbine,":[154],"where":[155],"results":[158],"two":[161],"dynamics,":[163,171],"namely":[164],"mechanical":[166],"torque":[167],"water":[169],"flow":[170],"real":[174],"have":[176],"indicated":[177],"can":[182,240],"accurately":[183],"these":[185],"an":[190],"online,":[191],"adaptive":[192],"way.":[193],"Moreover,":[194],"overfitting":[198],"problem":[199],"appears":[201],"during":[202],"online":[204],"training":[205],"phase,":[206],"we":[207],"propose":[208],"apply":[210],"meta-learning":[212,238],"technique":[213,239],"pre-train":[215],"meta-initial":[217],"value":[218],"each":[220],"parameter":[221],"equations.":[228],"It":[229],"shown":[232],"use":[235],"reduce":[241],"prediction":[243],"mean":[244],"square":[245],"error":[246],"significantly":[247],"by":[248],"more":[249],"than":[250],"60%.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
