{"id":"https://openalex.org/W4285274851","doi":"https://doi.org/10.1109/tim.2022.3184363","title":"Flooding Prognostic in Packed Columns Based on Electrical Capacitance Tomography and Convolution Neural Network","display_name":"Flooding Prognostic in Packed Columns Based on Electrical Capacitance Tomography and Convolution Neural Network","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285274851","doi":"https://doi.org/10.1109/tim.2022.3184363"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3184363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3184363","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.research.ed.ac.uk/en/publications/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031439277","display_name":"Yuan Chen","orcid":"https://orcid.org/0000-0001-8117-3859"},"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":"Yuan Chen","raw_affiliation_strings":["School of Engineering, The University of Edinburgh, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0001-8117-3859","affiliations":[{"raw_affiliation_string":"School of Engineering, The University of Edinburgh, Edinburgh, U.K","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353162","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0001-7257-8563"},"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":"Chang Liu","raw_affiliation_strings":["School of Engineering, The University of Edinburgh, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0001-7257-8563","affiliations":[{"raw_affiliation_string":"School of Engineering, The University of Edinburgh, Edinburgh, U.K","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":["School of Engineering, The University of Edinburgh, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0002-5797-9753","affiliations":[{"raw_affiliation_string":"School of Engineering, The University of Edinburgh, Edinburgh, U.K","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084791510","display_name":"Mathieu Lucquiaud","orcid":"https://orcid.org/0000-0003-2211-7157"},"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":"Mathieu Lucquiaud","raw_affiliation_strings":["School of Engineering, The University of Edinburgh, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2211-7157","affiliations":[{"raw_affiliation_string":"School of Engineering, The University of Edinburgh, Edinburgh, U.K","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058004272","display_name":"Jiabin Jia","orcid":"https://orcid.org/0000-0001-5073-5126"},"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":"Jiabin Jia","raw_affiliation_strings":["School of Engineering, The University of Edinburgh, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5073-5126","affiliations":[{"raw_affiliation_string":"School of Engineering, The University of Edinburgh, Edinburgh, U.K","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":0.4417,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.58750569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9998999834060669,"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/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.9857000112533569,"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/electrical-capacitance-tomography","display_name":"Electrical capacitance tomography","score":0.8464312553405762},{"id":"https://openalex.org/keywords/capacitance","display_name":"Capacitance","score":0.7613160610198975},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5741159319877625},{"id":"https://openalex.org/keywords/flooding","display_name":"Flooding (psychology)","score":0.5410832166671753},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.4962952733039856},{"id":"https://openalex.org/keywords/mechanics","display_name":"Mechanics","score":0.4602438807487488},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42041438817977905},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.41522276401519775},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.3965381979942322},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.30342352390289307},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2676905691623688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1741906702518463},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.16467419266700745},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.15808740258216858}],"concepts":[{"id":"https://openalex.org/C2777418626","wikidata":"https://www.wikidata.org/wiki/Q2584887","display_name":"Electrical capacitance tomography","level":4,"score":0.8464312553405762},{"id":"https://openalex.org/C30066665","wikidata":"https://www.wikidata.org/wiki/Q164399","display_name":"Capacitance","level":3,"score":0.7613160610198975},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5741159319877625},{"id":"https://openalex.org/C186594467","wikidata":"https://www.wikidata.org/wiki/Q1429176","display_name":"Flooding (psychology)","level":2,"score":0.5410832166671753},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.4962952733039856},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.4602438807487488},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42041438817977905},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.41522276401519775},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3965381979942322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30342352390289307},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2676905691623688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1741906702518463},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.16467419266700745},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.15808740258216858},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C17525397","wikidata":"https://www.wikidata.org/wiki/Q176140","display_name":"Electrode","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tim.2022.3184363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3184363","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Chen, Y, Liu, C, Jia, J, Yang, Y & Lucquiaud, M 2022, 'Flooding Prognostic in Packed Columns based on Electrical Capacitance Tomography and Convolution Neural Network', IEEE Transactions on Instrumentation and Measurement, vol. 71. https://doi.org/10.1109/TIM.2022.3184363","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:195181","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-8117-3859>,","pdf_url":"https://eprints.whiterose.ac.uk/id/eprint/195181/3/Final%20Revised%20Draft%20Paper%20TIM.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"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":"Article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.11820/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:publications/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/e1c64f2e-2225-40e3-bf1b-8e722c343cd0","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Chen, Y, Liu, C, Jia, J, Yang, Y & Lucquiaud, M 2022, 'Flooding Prognostic in Packed Columns based on Electrical Capacitance Tomography and Convolution Neural Network', IEEE Transactions on Instrumentation and Measurement, vol. 71. https://doi.org/10.1109/TIM.2022.3184363","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G745719754","display_name":null,"funder_award_id":"EP/P001661/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W36715365","https://openalex.org/W1122984720","https://openalex.org/W1155350164","https://openalex.org/W1503398984","https://openalex.org/W1569279109","https://openalex.org/W1920661243","https://openalex.org/W1964230934","https://openalex.org/W1976878756","https://openalex.org/W1998188913","https://openalex.org/W2003499941","https://openalex.org/W2007333510","https://openalex.org/W2009497115","https://openalex.org/W2011399473","https://openalex.org/W2020837036","https://openalex.org/W2040220980","https://openalex.org/W2044188673","https://openalex.org/W2049772201","https://openalex.org/W2051343358","https://openalex.org/W2060217809","https://openalex.org/W2065384876","https://openalex.org/W2073569779","https://openalex.org/W2087913253","https://openalex.org/W2088078575","https://openalex.org/W2088860026","https://openalex.org/W2089674817","https://openalex.org/W2090247722","https://openalex.org/W2093618290","https://openalex.org/W2108863971","https://openalex.org/W2110674208","https://openalex.org/W2136939531","https://openalex.org/W2310126244","https://openalex.org/W2345639549","https://openalex.org/W2583662161","https://openalex.org/W2619378372","https://openalex.org/W2810470058","https://openalex.org/W2811441645","https://openalex.org/W2899186693","https://openalex.org/W2919115771","https://openalex.org/W2921278323","https://openalex.org/W2948861672","https://openalex.org/W2989707712","https://openalex.org/W3009250710","https://openalex.org/W3010268473","https://openalex.org/W3010889593","https://openalex.org/W3097223218","https://openalex.org/W3127352836","https://openalex.org/W3133725013","https://openalex.org/W3152640484","https://openalex.org/W3165290021","https://openalex.org/W3172901920","https://openalex.org/W3209499826","https://openalex.org/W4220961705","https://openalex.org/W4221025902","https://openalex.org/W4232398143"],"related_works":["https://openalex.org/W2065013354","https://openalex.org/W1974831921","https://openalex.org/W2362942457","https://openalex.org/W2056641994","https://openalex.org/W2364971604","https://openalex.org/W2009640073","https://openalex.org/W1971900134","https://openalex.org/W1973400749","https://openalex.org/W1969121263","https://openalex.org/W2393881606"],"abstract_inverted_index":{"The":[0,142],"flooding":[1,53,66,224],"of":[2,39,65,163,189,210,220],"packed":[3,227],"columns":[4],"is":[5,107,172],"accompanied":[6],"by":[7,200],"a":[8,104,118],"steep":[9],"increase":[10],"in":[11,18,61,71,75,226],"liquid":[12,92,110,135,143,194,212],"hold-up":[13,93,111,136,144],"and":[14,23,43,95,117,223],"pressure":[15],"drop,":[16],"resulting":[17],"lower":[19],"mass":[20],"transfer":[21],"efficiency":[22],"potential":[24],"damage":[25],"to":[26,31,51,68,147,165,175],"equipment.":[27],"This":[28],"study":[29],"aims":[30],"investigate,":[32],"for":[33,207,215],"the":[34,37,62,83,134,153,176,192],"first":[35],"time,":[36],"feasibility":[38],"Electrical":[40,56,84,121,196],"Capacitance":[41,57,85,122,197],"Tomography":[42,58,86,123,198],"Convolutional":[44,80,114,169,201],"Neural":[45,81,115,170,202],"Networks":[46,116,171,203],"as":[47],"an":[48],"intensified":[49],"alternative":[50],"conventional":[52,120],"prediction":[54,219],"methods.":[55],"allows":[59],"variations":[60],"predominant":[63],"characteristics":[64],"events":[67],"be":[69],"investigated":[70],"greater":[72],"detail":[73],"than":[74,191],"previous":[76],"research.":[77],"Combined":[78],"with":[79],"Networks,":[82],"sensor":[87],"enables":[88],"high":[89,157,181],"accuracy":[90],"on":[91,126],"calculation":[94],"strong":[96],"robustness":[97],"against":[98],"noise-contaminated":[99],"measurements.":[100],"In":[101,167],"this":[102],"work,":[103],"detailed":[105],"comparison":[106],"made":[108],"between":[109],"results":[112],"using":[113],"more":[119,216],"method":[124,179],"based":[125],"Maxwell":[127,148,177],"equation.":[128],"Both":[129],"methods":[130],"can":[131],"accurately":[132],"calculate":[133],"at":[137,156,180],"low":[138],"gas":[139,158,182],"flow":[140,159,183],"rates.":[141],"predicted":[145],"according":[146],"equation":[149,178],"did":[150],"not":[151],"match":[152],"measured":[154],"values":[155],"rates,":[160,184],"showing":[161],"discrepancies":[162],"up":[164],"68%.":[166],"contrast,":[168],"much":[173],"superior":[174],"giving":[185],"only":[186],"1%":[187],"mean":[188],"difference":[190],"reference":[193],"hold-up.":[195],"supported":[199],"shows":[204],"great":[205],"fidelity":[206],"non-invasive":[208],"monitoring":[209],"local":[211],"hold-up,":[213],"allowing":[214],"accurate,":[217],"localized":[218],"loading":[221],"point":[222,225],"columns.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
