{"id":"https://openalex.org/W7139976160","doi":"https://doi.org/10.1016/j.engappai.2026.114490","title":"Multi-Fidelity deep learning for predicting the nonlinear buckling behaviour of concrete thin-shells","display_name":"Multi-Fidelity deep learning for predicting the nonlinear buckling behaviour of concrete thin-shells","publication_year":2026,"publication_date":"2026-03-21","ids":{"openalex":"https://openalex.org/W7139976160","doi":"https://doi.org/10.1016/j.engappai.2026.114490"},"language":"en","primary_location":{"id":"doi:10.1016/j.engappai.2026.114490","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114490","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.engappai.2026.114490","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125393367","display_name":"Maxime Pollet","orcid":null},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Maxime Pollet","raw_affiliation_strings":["University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-1894-1998","affiliations":[{"raw_affiliation_string":"University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059763722","display_name":"Paul Shepherd","orcid":"https://orcid.org/0000-0001-7078-4232"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Paul Shepherd","raw_affiliation_strings":["University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0001-7078-4232","affiliations":[{"raw_affiliation_string":"University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130278572","display_name":"Will Hawkins","orcid":null},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Will Hawkins","raw_affiliation_strings":["University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-4918-7665","affiliations":[{"raw_affiliation_string":"University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom","institution_ids":["https://openalex.org/I51601045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5125393367"],"corresponding_institution_ids":["https://openalex.org/I51601045"],"apc_list":{"value":3170,"currency":"USD","value_usd":3170},"apc_paid":{"value":3170,"currency":"USD","value_usd":3170},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.62708997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"174","issue":null,"first_page":"114490","last_page":"114490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11115","display_name":"Topology Optimization in Engineering","score":0.6327999830245972,"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/T11115","display_name":"Topology Optimization in Engineering","score":0.6327999830245972,"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/T10221","display_name":"Composite Structure Analysis and Optimization","score":0.1225999966263771,"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/T11096","display_name":"Aeroelasticity and Vibration Control","score":0.04230000078678131,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/buckling","display_name":"Buckling","score":0.8025000095367432},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.7347000241279602},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6219000220298767},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6179999709129333},{"id":"https://openalex.org/keywords/finite-element-method","display_name":"Finite element method","score":0.43810001015663147},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43549999594688416},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.35569998621940613}],"concepts":[{"id":"https://openalex.org/C85476182","wikidata":"https://www.wikidata.org/wiki/Q693104","display_name":"Buckling","level":2,"score":0.8025000095367432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015000224113464},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.7347000241279602},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6219000220298767},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6179999709129333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5260999798774719},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43549999594688416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4050000011920929},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38749998807907104},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.35569998621940613},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C2781141662","wikidata":"https://www.wikidata.org/wiki/Q17118374","display_name":"Nonlinear modelling","level":3,"score":0.334199994802475},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.3269999921321869},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.engappai.2026.114490","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114490","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.engappai.2026.114490","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114490","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320322","display_name":"University of Bath","ror":"https://ror.org/002h8g185"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1966353228","https://openalex.org/W1977046327","https://openalex.org/W1977581329","https://openalex.org/W1986704270","https://openalex.org/W2009460742","https://openalex.org/W2025617453","https://openalex.org/W2025684896","https://openalex.org/W2028130116","https://openalex.org/W2050305668","https://openalex.org/W2050426625","https://openalex.org/W2060515798","https://openalex.org/W2139122853","https://openalex.org/W2147564067","https://openalex.org/W2789269361","https://openalex.org/W2919958648","https://openalex.org/W2947047078","https://openalex.org/W2948978827","https://openalex.org/W3029905808","https://openalex.org/W3036063661","https://openalex.org/W3134684220","https://openalex.org/W3152893301","https://openalex.org/W3176094907","https://openalex.org/W3216987970","https://openalex.org/W4200352996","https://openalex.org/W4205475448","https://openalex.org/W4252026969","https://openalex.org/W4285676788","https://openalex.org/W4318678065","https://openalex.org/W4320810855","https://openalex.org/W4379113503","https://openalex.org/W4385889052","https://openalex.org/W4389050903","https://openalex.org/W4391177810","https://openalex.org/W4391751949","https://openalex.org/W4397010553","https://openalex.org/W4416442154"],"related_works":[],"abstract_inverted_index":{"This":[0,66],"research":[1,67],"introduces":[2],"a":[3,82,94,98,135,188,229],"novel":[4],"approach":[5],"to":[6,30,74,80,163,187,199,239,256],"rapidly":[7],"estimate":[8],"the":[9,36,42,52,69,76,119,123,140,144,148,195,205,224,234,243,258],"nonlinear":[10,45,156,206,230,259,284],"buckling":[11,53,116,141,207,260],"behaviour":[12],"of":[13,23,44,61,71,118,143,204,245,261],"concrete":[14,104,262],"thin-shells,":[15],"using":[16,153,172,178],"Multi-Fidelity":[17,72,165,235,265],"deep":[18,88],"learning.":[19],"The":[20,115,275],"prediction":[21],"speed":[22],"these":[24],"models":[25,73,196,276],"could":[26],"potentially":[27],"be":[28,240,254],"used":[29,162,255],"improve":[31],"design":[32],"space":[33],"exploration":[34],"during":[35],"structural":[37],"shape":[38],"optimisation":[39],"phase.":[40],"Indeed,":[41],"use":[43,70],"Finite":[46,285],"Element":[47,286],"(FE)":[48],"analysis":[49],"for":[50,86,228],"estimating":[51],"factor":[54,117,208],"is":[55,248],"unpractical":[56],"in":[57,122,147,168],"such":[58],"settings":[59],"because":[60],"its":[62],"high":[63],"computational":[64,77,137,270],"cost.":[65,138],"considers":[68],"mitigate":[75],"cost":[78],"required":[79,227],"constitute":[81],"sufficiently":[83],"large":[84],"dataset":[85,96,100,125,150],"training":[87],"learning":[89,252],"models.":[90],"Two":[91],"datasets":[92,160],"\u2013":[93,101],"low-fidelity":[95,124],"and":[97,109,177],"high-fidelity":[99,149,246],"that":[102,194],"contain":[103],"thin-shells":[105,121,146],"with":[106],"various":[107],"shapes":[108],"material":[110],"properties":[111],"were":[112,126,151,161,184,197,237],"therefore":[113],"generated.":[114],"20,000":[120],"obtained":[127,152],"through":[128],"linear":[129],"eigenvalue":[130],"FE":[131,157,231],"analysis,":[132],"which":[133],"has":[134],"low":[136],"Additionally,":[139,233],"factors":[142],"5,000":[145],"computationally":[154],"expensive":[155],"analyses.":[158],"These":[159,181],"train":[164],"Multilayer":[166],"Perceptrons":[167],"two":[169,182],"different":[170],"approaches:":[171],"several":[173],"sequentially":[174],"connected":[175],"models,":[176],"Transfer":[179],"Learning.":[180],"approaches":[183,236,266],"also":[185],"compared":[186],"Single-Fidelity":[189],"baseline.":[190],"It":[191],"was":[192],"found":[193,238],"able":[198],"make":[200],"highly":[201],"accurate":[202],"predictions":[203],"(Mean":[209],"Absolute":[210],"Errors":[211],"are":[212,267,272,277],"consistently":[213],"below":[214],"0.65%),":[215],"while":[216],"being":[217],"more":[218,278],"than":[219,223,279,283],"97,000":[220,280],"times":[221,281],"quicker":[222],"average":[225],"time":[226],"analysis.":[232,287],"beneficial":[241,268],"when":[242,269],"amount":[244],"data":[247],"limited.":[249,273],"\u2022":[250,264,274],"Deep":[251],"can":[253],"predict":[257],"shells.":[263],"resources":[271],"faster":[282]},"counts_by_year":[],"updated_date":"2026-03-22T06:30:12.169137","created_date":"2026-03-22T00:00:00"}
