{"id":"https://openalex.org/W3177096904","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459959","title":"Multiphase flowrate measurement with time series sensing data and sequential model","display_name":"Multiphase flowrate measurement with time series sensing data and sequential model","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3177096904","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459959","mag":"3177096904"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc50364.2021.9459959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"},"type":"article","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/A5081712021","display_name":"Haokun Wang","orcid":"https://orcid.org/0000-0003-0757-7729"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Haokun Wang","raw_affiliation_strings":["Institute for Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087250419","display_name":"Delin Hu","orcid":"https://orcid.org/0000-0002-2441-6057"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Delin Hu","raw_affiliation_strings":["Institute for Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044092715","display_name":"Yunjie Yang","orcid":"https://orcid.org/0000-0002-5797-9753"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yunjie Yang","raw_affiliation_strings":["Institute for Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Institute for Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101951237","display_name":"Maomao Zhang","orcid":"https://orcid.org/0000-0002-1742-4665"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maomao Zhang","raw_affiliation_strings":["Shenzhen LeEngStar Co.,Ltd, Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen LeEngStar Co.,Ltd, Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081712021"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":0.7331,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64438187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10864","display_name":"Fluid Dynamics and Mixing","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/venturi-effect","display_name":"Venturi effect","score":0.9800530672073364},{"id":"https://openalex.org/keywords/multiphase-flow","display_name":"Multiphase flow","score":0.7787602543830872},{"id":"https://openalex.org/keywords/mass-flow-meter","display_name":"Mass flow meter","score":0.6955493092536926},{"id":"https://openalex.org/keywords/flow-measurement","display_name":"Flow measurement","score":0.646208643913269},{"id":"https://openalex.org/keywords/volumetric-flow-rate","display_name":"Volumetric flow rate","score":0.6090775728225708},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5402715802192688},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5389460325241089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5200607180595398},{"id":"https://openalex.org/keywords/mass-flow-rate","display_name":"Mass flow rate","score":0.5176203846931458},{"id":"https://openalex.org/keywords/two-phase-flow","display_name":"Two-phase flow","score":0.43718796968460083},{"id":"https://openalex.org/keywords/mass-flow","display_name":"Mass flow","score":0.42440012097358704},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4223478138446808},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.41498613357543945},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.21880972385406494},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21734872460365295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19756463170051575},{"id":"https://openalex.org/keywords/mechanics","display_name":"Mechanics","score":0.17997586727142334},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.1230948269367218}],"concepts":[{"id":"https://openalex.org/C21423434","wikidata":"https://www.wikidata.org/wiki/Q725699","display_name":"Venturi effect","level":3,"score":0.9800530672073364},{"id":"https://openalex.org/C2779379648","wikidata":"https://www.wikidata.org/wiki/Q1559665","display_name":"Multiphase flow","level":2,"score":0.7787602543830872},{"id":"https://openalex.org/C175580448","wikidata":"https://www.wikidata.org/wiki/Q114414","display_name":"Mass flow meter","level":3,"score":0.6955493092536926},{"id":"https://openalex.org/C16302685","wikidata":"https://www.wikidata.org/wiki/Q15091623","display_name":"Flow measurement","level":2,"score":0.646208643913269},{"id":"https://openalex.org/C172120300","wikidata":"https://www.wikidata.org/wiki/Q1134348","display_name":"Volumetric flow rate","level":2,"score":0.6090775728225708},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5402715802192688},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5389460325241089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5200607180595398},{"id":"https://openalex.org/C75892298","wikidata":"https://www.wikidata.org/wiki/Q1366187","display_name":"Mass flow rate","level":2,"score":0.5176203846931458},{"id":"https://openalex.org/C144308804","wikidata":"https://www.wikidata.org/wiki/Q232997","display_name":"Two-phase flow","level":3,"score":0.43718796968460083},{"id":"https://openalex.org/C33493971","wikidata":"https://www.wikidata.org/wiki/Q3295893","display_name":"Mass flow","level":2,"score":0.42440012097358704},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4223478138446808},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.41498613357543945},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.21880972385406494},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21734872460365295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19756463170051575},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.17997586727142334},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.1230948269367218},{"id":"https://openalex.org/C201289731","wikidata":"https://www.wikidata.org/wiki/Q1172599","display_name":"Inlet","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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":2,"locations":[{"id":"doi:10.1109/i2mtc50364.2021.9459959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/b9d40d45-e727-4b29-a797-912641065522","is_oa":false,"landing_page_url":"https://hdl.handle.net/20.500.11820/b9d40d45-e727-4b29-a797-912641065522","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"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":16,"referenced_works":["https://openalex.org/W1514655326","https://openalex.org/W2007090477","https://openalex.org/W2038716855","https://openalex.org/W2090217923","https://openalex.org/W2134225440","https://openalex.org/W2134986126","https://openalex.org/W2461556369","https://openalex.org/W2594988164","https://openalex.org/W2736767003","https://openalex.org/W2775103799","https://openalex.org/W2926004035","https://openalex.org/W2944620330","https://openalex.org/W2980215945","https://openalex.org/W3097128261","https://openalex.org/W4245066122","https://openalex.org/W6741720756"],"related_works":["https://openalex.org/W2116491277","https://openalex.org/W1994017856","https://openalex.org/W3177096904","https://openalex.org/W2396144173","https://openalex.org/W2272108857","https://openalex.org/W1561343599","https://openalex.org/W2164901466","https://openalex.org/W2052817049","https://openalex.org/W2029015768","https://openalex.org/W2074556842"],"abstract_inverted_index":{"Accurate":[0],"multiphase":[1,29,98],"flowrate":[2,30,58,74,137],"measurement":[3],"is":[4,119],"challenging":[5],"but":[6],"crucially":[7],"important":[8],"in":[9,95],"energy":[10],"industry":[11],"to":[12,26,53,82,105,121],"monitor":[13],"the":[14,28,55,65,71,76,115,125],"production":[15],"processes.":[16],"Machine":[17],"learning":[18],"has":[19],"recently":[20],"emerged":[21],"as":[22],"a":[23,41,96],"promising":[24],"method":[25],"estimate":[27,54],"based":[31,63],"on":[32,64],"different":[33,140],"flow":[34,62,99,141],"meters.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39],"propose":[40],"Convolutional":[42],"Neural":[43],"Network":[44],"(CNN)":[45],"combined":[46],"with":[47,124],"Long-Short":[48],"Term":[49],"Memory":[50],"(LSTM)":[51],"model":[52,118],"mass":[56,73],"liquid":[57,77,136],"of":[59,70,75],"oil/gas/water":[60],"three-phase":[61],"Venturi":[66,92,131],"tube.":[67],"The":[68,111],"range":[69],"estimated":[72],"phase":[78],"varies":[79],"from":[80,91,130],"92.1":[81],"10000":[83],"kg/h.":[84],"We":[85],"collect":[86],"time":[87,126],"series":[88,127],"sensing":[89,128],"data":[90,108,129],"tube":[93,132],"installed":[94],"pilot-scale":[97],"facility":[100],"and":[101,133],"utilize":[102],"single-phase":[103],"flowmeters":[104],"acquire":[106],"reference":[107],"before":[109],"mixing.":[110],"experimental":[112],"results":[113],"suggest":[114],"proposed":[116],"CNN-LSTM":[117],"able":[120],"effectively":[122],"deal":[123],"achieve":[134],"acceptable":[135],"estimation":[138],"under":[139],"conditions.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
