{"id":"https://openalex.org/W7134837364","doi":"https://doi.org/10.48550/arxiv.2603.07201","title":"A Dual-Graph Spatiotemporal GNN Surrogate for Nonlinear Response Prediction of Reinforced Concrete Beams under Four-Point Bending","display_name":"A Dual-Graph Spatiotemporal GNN Surrogate for Nonlinear Response Prediction of Reinforced Concrete Beams under Four-Point Bending","publication_year":2026,"publication_date":"2026-03-07","ids":{"openalex":"https://openalex.org/W7134837364","doi":"https://doi.org/10.48550/arxiv.2603.07201"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07201","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128684548","display_name":"Zhaoyang Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Zhaoyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128630942","display_name":"Qilin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Qilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3045605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.6908000111579895,"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":0.6908000111579895,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.06939999759197235,"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/T11096","display_name":"Aeroelasticity and Vibration Control","score":0.0284000001847744,"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/parametric-statistics","display_name":"Parametric statistics","score":0.667900025844574},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6276999711990356},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.5034999847412109},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.4465000033378601},{"id":"https://openalex.org/keywords/bending","display_name":"Bending","score":0.4422999918460846},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41670000553131104},{"id":"https://openalex.org/keywords/finite-element-method","display_name":"Finite element method","score":0.3959999978542328},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.39469999074935913}],"concepts":[{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.6949999928474426},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.667900025844574},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6276999711990356},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.5034999847412109},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C87210426","wikidata":"https://www.wikidata.org/wiki/Q1072476","display_name":"Bending","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.3928999900817871},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.38339999318122864},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3815000057220459},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C155165730","wikidata":"https://www.wikidata.org/wiki/Q1319519","display_name":"von Mises yield criterion","level":3,"score":0.3255999982357025},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31769999861717224},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C2988805333","wikidata":"https://www.wikidata.org/wiki/Q184190","display_name":"Reinforced concrete","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2858000099658966},{"id":"https://openalex.org/C2781256830","wikidata":"https://www.wikidata.org/wiki/Q210729","display_name":"Nonlinear element","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C200288055","wikidata":"https://www.wikidata.org/wiki/Q2621792","display_name":"Element (criminal law)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.2522999942302704},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07201","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07201","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.07201","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7538866400718689}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"High-fidelity":[0],"nonlinear":[1,194],"finite-element":[2],"(FE)":[3],"simulations":[4],"of":[5,32,190,193],"reinforced-concrete":[6],"(RC)":[7],"structures":[8],"are":[9,110],"still":[10],"costly,":[11],"especially":[12],"in":[13,94,169],"parametric":[14,45,198],"settings":[15],"where":[16],"loading":[17,53,66],"positions":[18],"vary.":[19],"We":[20,115],"develop":[21],"a":[22,44,56,95,127,188],"dual-graph":[23],"spatiotemporal":[24],"GNN":[25],"surrogate":[26,183],"to":[27,161,163],"approximate":[28],"the":[29,51,89,103,152,159,182,191],"time":[30],"histories":[31],"RC":[33],"beams":[34],"under":[35],"four-point":[36],"bending.":[37],"To":[38],"generate":[39],"training":[40],"data,":[41],"we":[42],"run":[43],"Abaqus":[46],"campaign":[47],"that":[48],"independently":[49],"shifts":[50],"two":[52,123],"blocks":[54],"on":[55,151],"mesh-aligned":[57],"grid":[58],"and":[59,73,88,119,137,200],"exports":[60],"full-field":[61],"responses":[62],"at":[63,187],"fixed":[64],"normalized":[65],"levels.":[67],"The":[68],"model":[69],"rolls":[70],"out":[71],"autoregressively":[72],"jointly":[74],"predicts":[75],"nodal":[76],"displacements,":[77],"element":[78,108,153],"wise":[79],"von":[80],"Mises":[81],"stress,":[82],"element-wise":[83],"equivalent":[84],"plastic":[85],"strain":[86],"(PEEQ),":[87],"global":[90,146,176],"vertical":[91],"reaction":[92],"force":[93,147],"single":[96],"multi-task":[97],"setup.":[98],"A":[99],"key":[100],"motivation":[101],"is":[102],"peak":[104],"loss":[105],"introduced":[106],"when":[107],"quantities":[109],"forced":[111],"through":[112,149],"node-based":[113],"representations.":[114],"therefore":[116],"couple":[117],"node-":[118],"element-level":[120,139],"dynamics":[121],"using":[122],"recurrent":[124,132],"graph":[125,129],"branches:":[126],"node-level":[128],"convolutional":[130],"gated":[131],"unit":[133],"(GConvGRU)":[134],"for":[135,141],"kinematics":[136],"an":[138],"GConvGRU":[140],"history-dependent":[142],"internal":[143],"variables,":[144],"with":[145],"predicted":[148],"pooling":[150],"branch.":[154],"In":[155],"controlled":[156],"ablations,":[157],"removing":[158],"Element":[160,164],"Node":[162],"pathway":[165],"improves":[166],"peak-sensitive":[167],"prediction":[168],"localized":[170],"high-gradient":[171],"stress/PEEQ":[172],"regions":[173],"without":[174],"degrading":[175],"load":[177],"displacement":[178],"trends.":[179],"After":[180],"training,":[181],"produces":[184],"full":[185],"trajectories":[186],"fraction":[189],"cost":[192],"FE,":[195],"enabling":[196],"faster":[197],"evaluation":[199],"design":[201],"exploration.":[202]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}
