{"id":"https://openalex.org/W2892258454","doi":"https://doi.org/10.3390/s18093057","title":"Bayesian Finite Element Model Updating and Assessment of Cable-Stayed Bridges Using Wireless Sensor Data","display_name":"Bayesian Finite Element Model Updating and Assessment of Cable-Stayed Bridges Using Wireless Sensor Data","publication_year":2018,"publication_date":"2018-09-12","ids":{"openalex":"https://openalex.org/W2892258454","doi":"https://doi.org/10.3390/s18093057","mag":"2892258454","pmid":"https://pubmed.ncbi.nlm.nih.gov/30213096"},"language":"en","primary_location":{"id":"doi:10.3390/s18093057","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18093057","pdf_url":"https://www.mdpi.com/1424-8220/18/9/3057/pdf?version=1536747500","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/18/9/3057/pdf?version=1536747500","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060742909","display_name":"Parisa Asadollahi","orcid":"https://orcid.org/0000-0002-0805-3962"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Parisa Asadollahi","raw_affiliation_strings":["Department of Civil, Environmental, and Architectural Engineering, The University of Kansas, Lawrence, KS 66049, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil, Environmental, and Architectural Engineering, The University of Kansas, Lawrence, KS 66049, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006384169","display_name":"Yong Huang","orcid":"https://orcid.org/0000-0002-7963-0720"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Huang","raw_affiliation_strings":["Key Lab of Smart Prevention and Mitigation for Civil Engineering Disasters of the Ministry of Industry and Information, Harbin Institute of Technology, Harbin 150090, China","Key Lab of Structural Dynamic Behavior and Control of the Ministry of Education, School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Lab of Smart Prevention and Mitigation for Civil Engineering Disasters of the Ministry of Industry and Information, Harbin Institute of Technology, Harbin 150090, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Key Lab of Structural Dynamic Behavior and Control of the Ministry of Education, School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100402609","display_name":"Jian Li","orcid":"https://orcid.org/0000-0003-3439-7539"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jian Li","raw_affiliation_strings":["Department of Civil, Environmental, and Architectural Engineering, The University of Kansas, Lawrence, KS 66049, USA"],"raw_orcid":"https://orcid.org/0000-0003-3439-7539","affiliations":[{"raw_affiliation_string":"Department of Civil, Environmental, and Architectural Engineering, The University of Kansas, Lawrence, KS 66049, USA","institution_ids":["https://openalex.org/I146416000"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006384169","https://openalex.org/A5100402609"],"corresponding_institution_ids":["https://openalex.org/I146416000","https://openalex.org/I204983213"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.1572,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.90754047,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"18","issue":"9","first_page":"3057","last_page":"3057"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10534","display_name":"Structural Health Monitoring Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11850","display_name":"Concrete Corrosion and Durability","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/bayesian-inference","display_name":"Bayesian inference","score":0.6101908087730408},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5596733689308167},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5092848539352417},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5023226737976074},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.49826550483703613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49258309602737427},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.47907668352127075},{"id":"https://openalex.org/keywords/structural-health-monitoring","display_name":"Structural health monitoring","score":0.45496803522109985},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4380181133747101},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.4346136152744293},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40450677275657654},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.259854257106781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23587897419929504},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.11594641208648682}],"concepts":[{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.6101908087730408},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5596733689308167},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5092848539352417},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5023226737976074},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.49826550483703613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49258309602737427},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.47907668352127075},{"id":"https://openalex.org/C2776247918","wikidata":"https://www.wikidata.org/wiki/Q1423713","display_name":"Structural health monitoring","level":2,"score":0.45496803522109985},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4380181133747101},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4346136152744293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40450677275657654},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.259854257106781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23587897419929504},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.11594641208648682}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3390/s18093057","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18093057","pdf_url":"https://www.mdpi.com/1424-8220/18/9/3057/pdf?version=1536747500","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:30213096","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30213096","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:91e7c3e9e5eb4020a3f9dd4f0a5e0e64","is_oa":true,"landing_page_url":"https://doaj.org/article/91e7c3e9e5eb4020a3f9dd4f0a5e0e64","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":"Sensors, Vol 18, Iss 9, p 3057 (2018)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5126350","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC6164055","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:kuscholarworks.ku.edu:1808/29820","is_oa":true,"landing_page_url":"http://hdl.handle.net/1808/29820","pdf_url":null,"source":{"id":"https://openalex.org/S4377196285","display_name":"KU ScholarWorks (University of Kansas)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I146416000","host_organization_name":"University of Kansas","host_organization_lineage":["https://openalex.org/I146416000"],"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":"Article"},{"id":"pmh:oai:mdpi.com:/1424-8220/18/9/3057/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s18093057","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Sensors","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6164055","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6164055","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s18093057","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18093057","pdf_url":"https://www.mdpi.com/1424-8220/18/9/3057/pdf?version=1536747500","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G3537752892","display_name":null,"funder_award_id":"51778192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7320035931","display_name":null,"funder_award_id":"2017YFF0108702","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2892258454.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W77275778","https://openalex.org/W1551016509","https://openalex.org/W1604465848","https://openalex.org/W1641920144","https://openalex.org/W1854666258","https://openalex.org/W1964665495","https://openalex.org/W1972023825","https://openalex.org/W1993163577","https://openalex.org/W2020068214","https://openalex.org/W2023965427","https://openalex.org/W2038817616","https://openalex.org/W2044745682","https://openalex.org/W2054934530","https://openalex.org/W2062258832","https://openalex.org/W2062469328","https://openalex.org/W2087642098","https://openalex.org/W2087752560","https://openalex.org/W2093004055","https://openalex.org/W2097311910","https://openalex.org/W2097912000","https://openalex.org/W2116689067","https://openalex.org/W2120536720","https://openalex.org/W2130782750","https://openalex.org/W2166670624","https://openalex.org/W2168090960","https://openalex.org/W2182806504","https://openalex.org/W2335295811","https://openalex.org/W2341732730","https://openalex.org/W2464995617","https://openalex.org/W2479531384","https://openalex.org/W2577761826","https://openalex.org/W2588361551","https://openalex.org/W2607203254","https://openalex.org/W2748305738","https://openalex.org/W2783201580","https://openalex.org/W2791210712","https://openalex.org/W2802162642","https://openalex.org/W2806905348","https://openalex.org/W2888180323","https://openalex.org/W3099791665","https://openalex.org/W4250157793","https://openalex.org/W4299551239","https://openalex.org/W6636712753"],"related_works":["https://openalex.org/W2109606780","https://openalex.org/W1480082381","https://openalex.org/W4299976848","https://openalex.org/W308423894","https://openalex.org/W1436597729","https://openalex.org/W3122206612","https://openalex.org/W71678127","https://openalex.org/W2157655363","https://openalex.org/W4205763938","https://openalex.org/W2292189132"],"abstract_inverted_index":{"We":[0],"focus":[1],"on":[2,80,160,174,270],"a":[3,14,24,81,153,179,230],"Bayesian":[4,31,117,233,242],"inference":[5,32,118],"framework":[6],"for":[7,232],"finite":[8],"element":[9],"(FE)":[10],"model":[11,101,130,167,188,203,211,227,234,251,255,265,283],"updating":[12,70,266],"of":[13,61,98,200,208,220,263,289],"long-span":[15],"cable-stayed":[16],"bridge":[17,82],"using":[18,169,274],"long-term":[19],"monitoring":[20],"data":[21,150,273],"collected":[22,151],"from":[23,91,148,156,178],"wireless":[25],"sensor":[26],"network":[27],"(WSN).":[28],"A":[29],"robust":[30,138],"method":[33,119,277],"is":[34,55,86,112],"proposed":[35,51,116,276],"which":[36,253],"marginalizes":[37],"the":[38,65,92,99,104,115,144,157,161,175,187,193,197,201,206,209,216,221,225,238,259,271,275,280,290],"prediction-error":[39,62,106,121],"precisions":[40,68,72,122],"and":[41,69,76,103,137,182,205,250,267],"applies":[42],"Transitional":[43],"Markov":[44],"Chain":[45],"Monte":[46],"Carlo":[47],"(TMCMC)":[48],"algorithm.":[49],"The":[50,261],"marginalizing":[52],"error":[53,67,71],"precision":[54,107],"compared":[56],"with":[57,120,131,293],"other":[58],"two":[59,165,210],"treatments":[60],"precisions,":[63],"including":[64],"constant":[66],"through":[73],"theoretical":[74],"analysis":[75,181],"numerical":[77],"investigation":[78],"based":[79,173,269],"FE":[83,129,264,282],"model.":[84],"TMCMC":[85,194],"employed":[87],"to":[88],"draw":[89],"samples":[90],"posterior":[93,134,198,222],"probability":[94],"density":[95],"function":[96],"(PDF)":[97],"structural":[100,202,291],"parameters":[102,108,126,147,204],"uncertain":[105],"if":[109],"required.":[110],"It":[111],"found":[113],"that":[114,245,257,279],"marginalized":[123],"as":[124],"\"nuisance\"":[125],"produces":[127],"an":[128],"more":[132],"accurate":[133],"uncertainty":[135],"quantification":[136],"modal":[139,146,287],"property":[140],"prediction.":[141],"When":[142],"applying":[143],"identified":[145],"acceleration":[149],"during":[152],"one-year":[154],"period":[155],"large-scale":[158],"WSN":[159],"bridge,":[162],"we":[163],"choose":[164],"candidate":[166,226],"classes":[168,212,228,256],"different":[170],"parameter":[171],"grouping":[172],"clustering":[176],"results":[177,262],"sensitivity":[180],"apply":[183],"Bayes'":[184],"Theorem":[185],"at":[186],"class":[189,235],"level.":[190],"By":[191],"implementing":[192],"sampler,":[195],"both":[196],"distributions":[199],"plausibility":[207],"are":[213],"characterized":[214],"given":[215],"real":[217,272],"data.":[218,260],"Computation":[219],"probabilities":[223],"over":[224],"provides":[229],"procedure":[231],"assessment,":[236],"where":[237],"computation":[239],"automatically":[240],"implements":[241],"Ockham":[243],"razor":[244],"trades":[246],"off":[247],"between":[248],"data-fitting":[249],"complexity,":[252],"penalizes":[254],"\"over-fit\"":[258],"assessment":[268],"show":[278],"updated":[281],"can":[284],"successfully":[285],"predict":[286],"properties":[288],"system":[292],"high":[294],"accuracy.":[295]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}