{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:54:37Z","timestamp":1776128077087,"version":"3.50.1"},"reference-count":57,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012245","name":"Science and Technology Planning Project of Guangdong Province","doi-asserted-by":"publisher","award":["2025A0505020090"],"award-info":[{"award-number":["2025A0505020090"]}],"id":[{"id":"10.13039\/501100012245","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004607","name":"Guangxi Natural Science Foundation","doi-asserted-by":"publisher","award":["2022GXNSFFA035035"],"award-info":[{"award-number":["2022GXNSFFA035035"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52368028"],"award-info":[{"award-number":["52368028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017691","name":"Guangxi Key Research and Development Program","doi-asserted-by":"publisher","award":["GKAB22036007"],"award-info":[{"award-number":["GKAB22036007"]}],"id":[{"id":"10.13039\/501100017691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.engappai.2026.114341","type":"journal-article","created":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T03:58:22Z","timestamp":1773633502000},"page":"114341","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Quantitative assessment of interfacial debonding in large-span concrete-filled steel tube arch bridges via interpretable deep hybrid learning and ultrasonic inspection"],"prefix":"10.1016","volume":"173","author":[{"given":"Minghui","family":"Yao","sequence":"first","affiliation":[]},{"given":"Shuhong","family":"Guan","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zheng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Junhui","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Cai","family":"Tan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6178-4457","authenticated-orcid":false,"given":"Yunchao","family":"Tang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.114341_bib1","article-title":"A model fusion strategy for identifying aircraft risk using CNN and att-BiLSTM","volume":"228","year":"2022","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.engappai.2026.114341_bib2","article-title":"A novel heat load prediction model of district heating system based on hybrid whale optimization algorithm (WOA) and CNN-LSTM with attention mechanism","volume":"312","year":"2024","journal-title":"Energy"},{"key":"10.1016\/j.engappai.2026.114341_bib3","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1080\/10589751003658057","article-title":"Nondestructive evaluation of defects in concrete structures based on finite element simulations of ultrasonic wave propagation","volume":"25","author":"Acciani","year":"2010","journal-title":"Nondestr. Test. Eval."},{"key":"10.1016\/j.engappai.2026.114341_bib4","article-title":"Behavior of eccentrically loaded circular concrete-filled steel tube stub columns with localized corrosion","volume":"288","year":"2023","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib5","doi-asserted-by":"crossref","first-page":"4400","DOI":"10.3390\/s22124400","article-title":"Damage detection using ultrasonic techniques in concrete-filled steel tubes (CFSTs) columns","volume":"22","author":"Callejas","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.engappai.2026.114341_bib6","author":"Chen"},{"key":"10.1016\/j.engappai.2026.114341_bib7","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2021.112778","article-title":"Interfacial imperfection detection for steel-concrete composite structures using NDT techniques: a state-of-the-art review","volume":"245","author":"Chen","year":"2021","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2022.115197","article-title":"Percussion-based quasi real-time void detection for concrete-filled steel tubular structures using dense learned features","volume":"274","author":"Chen","year":"2023","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2024.118353","article-title":"Quantitative analysis of debonding gaps in concrete-filled steel tubes on the Qinghai-Tibet Plateau under severely harsh conditions","volume":"314","author":"Chen","year":"2024","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib10","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.egyr.2023.05.090","article-title":"A hybrid CNN-GRU based probabilistic model for load forecasting from individual household to commercial building","volume":"9","author":"Chiu","year":"2023","journal-title":"Energy Rep."},{"key":"10.1016\/j.engappai.2026.114341_bib11","article-title":"Cooling-excited infrared thermography for enhancing the detection of concrete filled steel tube interfacial debonding at concrete hydration","volume":"20","year":"2024","journal-title":"Case Stud. Constr. Mater."},{"key":"10.1016\/j.engappai.2026.114341_bib12","doi-asserted-by":"crossref","DOI":"10.1016\/j.tws.2022.109503","article-title":"A systematic review on CFST members under impulsive loading","volume":"179","author":"Dabbagh","year":"2022","journal-title":"Thin-Walled Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib13","article-title":"Detection of subsurface voids in concrete-filled steel tubular (CFST) structure using percussion approach","volume":"262","year":"2020","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.114341_bib14","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.conbuildmat.2016.10.061","article-title":"Experimental studies on void detection in concrete-filled steel tubes using ultrasound","volume":"128","author":"Dong","year":"2016","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.114341_bib15","article-title":"Dynamic and explainable deep learning-based risk prediction on adjacent building induced by deep excavation","volume":"140","year":"2023","journal-title":"Tunn. Undergr. Space Technol."},{"key":"10.1016\/j.engappai.2026.114341_bib16","unstructured":"Evaluation of the bond stress transfer mechanism in CFSTs | Int. J. Civ. Eng., (n.d.). https:\/\/link.springer.com\/article\/10.1007\/s40999-022-00769-2 (accessed August 10, 2025)."},{"key":"10.1016\/j.engappai.2026.114341_bib17","article-title":"Experimental and numerical analysis of force transfer mechanisms in joints of concrete-filled steel tube truss arch bridge","volume":"341","year":"2025","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.26599\/JIC.2023.9180005","article-title":"Cement grouting online monitoring and intelligent control for dam foundations","volume":"1","author":"Fan","year":"2023","journal-title":"J. Intell. Constr."},{"key":"10.1016\/j.engappai.2026.114341_bib19","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.105622","article-title":"Predicting concentration levels of air pollutants by transfer learning and recurrent neural network","volume":"192","author":"Fong","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.engappai.2026.114341_bib20","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)CF.1943-5509.0001479","article-title":"Air void and cap gap composite defects of concrete-filled steel-tube arch bridge transverse brace","volume":"34","author":"Guo","year":"2020","journal-title":"J. Perform. Constr. Facil."},{"key":"10.1016\/j.engappai.2026.114341_bib21","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.jcsr.2014.04.016","article-title":"Developments and advanced applications of concrete-filled steel tubular (CFST) structures: members","volume":"100","author":"Han","year":"2014","journal-title":"J. Constr. Steel Res."},{"key":"10.1016\/j.engappai.2026.114341_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.compositesb.2025.113320","article-title":"Bond durability of FRP bar-concrete interface under marine exposure: from a comprehensive review to an improved prediction method","volume":"312","author":"He","year":"2026","journal-title":"Composites, Part B"},{"key":"10.1016\/j.engappai.2026.114341_bib23","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.engappai.2026.114341_bib24","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2023.117252","article-title":"Size effect on axial behavior of stub CFST columns strengthened with square steel tube and sandwiched concrete jackets","volume":"301","author":"Huang","year":"2024","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib25","article-title":"Interaction diagrams of concrete-filled steel tube columns exposed to fire considering the slenderness effect","volume":"289","year":"2023","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib26","unstructured":"Investigation of interfacial debonding identification for concrete filled steel tube columns based on acoustic signals - ScienceDirect, (n.d.). https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0263224124013964 (accessed August 10, 2025)."},{"key":"10.1016\/j.engappai.2026.114341_bib27","article-title":"Investigation of interfacial debonding identification for concrete filled steel tube columns based on acoustic signals","volume":"240","year":"2025","journal-title":"Measurement"},{"key":"10.1016\/j.engappai.2026.114341_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhazmat.2019.121322","article-title":"Prediction of mechanical properties of green concrete incorporating waste foundry sand based on gene expression programming","volume":"384","author":"Iqbal","year":"2020","journal-title":"J. Hazard. Mater."},{"key":"10.1016\/j.engappai.2026.114341_bib29","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.autcon.2011.06.013","article-title":"Evaluation of ultrasonic inspection and imaging systems for concrete pipes","volume":"22","author":"Iyer","year":"2012","journal-title":"Autom. ConStruct."},{"key":"10.1016\/j.engappai.2026.114341_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2021.103785","article-title":"A deep learning approach for fast detection and classification of concrete damage","volume":"128","author":"Jiang","year":"2021","journal-title":"Autom. ConStruct."},{"key":"10.1016\/j.engappai.2026.114341_bib31","doi-asserted-by":"crossref","DOI":"10.1088\/0964-1726\/24\/11\/113001","article-title":"Monitoring of concrete structures using the ultrasonic pulse velocity method","volume":"24","author":"Karaiskos","year":"2015","journal-title":"Smart Mater. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib32","doi-asserted-by":"crossref","DOI":"10.1016\/j.conbuildmat.2023.134491","article-title":"Automated detection and segmentation of internal defects in reinforced concrete using deep learning on ultrasonic images","volume":"411","author":"Kuchipudi","year":"2024","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.engappai.2026.114341_bib33","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"Lecun","year":"1998","journal-title":"Proc. IEEE"},{"key":"10.1016\/j.engappai.2026.114341_bib34","first-page":"174","article-title":"Temperature action and effect of concrete-filled steel tubular bridges: a review","volume":"7","author":"Liu","year":"2020","journal-title":"J. Traffic Transp. Eng. Engl. Ed."},{"key":"10.1016\/j.engappai.2026.114341_bib35","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2023.110214","article-title":"Interfacial debonding detection for CFST structures using an ultrasonic phased array: application to the Shenzhen SEG building","volume":"192","author":"Liu","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib36","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2023.110641","article-title":"Impact acoustic inspection of interfacial debonding defects in concrete-filled steel tubes","volume":"200","author":"Liu","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib37","article-title":"Long-term traffic flow forecasting using a hybrid CNN-BiLSTM model","volume":"121","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114341_bib38","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2024.118258","article-title":"Experimental study and theoretical prediction of axial compression behavior in PMC-Reinforced CFST columns with void defects","volume":"313","author":"Luo","year":"2024","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114341_bib39","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2024.111443","article-title":"A CNN-BiLSTM-Attention approach for EHA degradation prediction based on time-series generative adversarial network","volume":"215","author":"Ma","year":"2024","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib40","article-title":"Mesoscale numerical analysis and test on the effect of debonding defect of rectangular CFSTs on wave propagation with a homogenization method","volume":"163","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib41","article-title":"Numerical and experimental study on the evolution of thermal contrast for infrared detection of debonding in concrete filled steel tubular structure","volume":"258","year":"2025","journal-title":"Appl. Therm. Eng."},{"key":"10.1016\/j.engappai.2026.114341_bib42","series-title":"Convolutional Neural Networks for Accurate and Robust Noninvasive Pressure Measurements in Sealed Systems","author":"Pereira","year":"2025"},{"key":"10.1016\/j.engappai.2026.114341_bib43","unstructured":"Real-time prediction of axial force in concrete-filled steel tubular columns under fire conditions using modular artificial intelligence techniques - ScienceDirect, (n.d.). https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0952197625006177 (accessed August 10, 2025)."},{"key":"10.1016\/j.engappai.2026.114341_bib44","article-title":"Research on void identification of concrete filled steel tube under data imbalance and constraint condition change","volume":"72","year":"2025","journal-title":"Structures"},{"key":"10.1016\/j.engappai.2026.114341_bib45","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.ymssp.2018.07.011","article-title":"Reverse time migration of Acoustic waves for imaging based defects detection for concrete and CFST structures","volume":"117","year":"2019","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib46","series-title":"2019 IEEE Int. Conf. Big Data Big Data","first-page":"3285","article-title":"The performance of LSTM and BiLSTM in forecasting time series","author":"Siami-Namini","year":"2019"},{"key":"10.1016\/j.engappai.2026.114341_bib47","doi-asserted-by":"crossref","first-page":"49","DOI":"10.4028\/www.scientific.net\/KEM.293-294.49","article-title":"Ultrasonic\/guided waves for structural health monitoring","volume":"293\u2013294","author":"Staszewski","year":"2005","journal-title":"Key Eng. Mater."},{"key":"10.1016\/j.engappai.2026.114341_bib48","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1016\/j.jrmge.2022.06.015","article-title":"Real-time prediction of mechanical behaviors of underwater shield tunnel structure using machine learning method based on structural health monitoring data","volume":"15","author":"Tan","year":"2023","journal-title":"J. Rock Mech. Geotech. Eng."},{"key":"10.1016\/j.engappai.2026.114341_bib49","doi-asserted-by":"crossref","DOI":"10.1016\/j.compositesb.2021.108816","article-title":"Fatigue damage characterization for composite laminates using deep learning and laser ultrasonic","volume":"216","author":"Tao","year":"2021","journal-title":"Composites, Part B"},{"key":"10.1016\/j.engappai.2026.114341_bib50","article-title":"Tutorial on time series prediction using 1D-CNN and BiLSTM: a case example of peak electricity demand and system marginal price prediction","volume":"126","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114341_bib51","unstructured":"Ultrasonic guided wave based structural damage detection and localization using model assisted convolutional and recurrent neural networks - ScienceDirect, (n.d.). https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0957417420309234 (accessed August 10, 2025)."},{"key":"10.1016\/j.engappai.2026.114341_bib52","article-title":"Ultrasonic identification of CFST debonding via a novel bayesian optimized-LSTM network","volume":"238","year":"2025","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib53","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.istruc.2022.06.042","article-title":"Automatic detection of defects in concrete structures based on deep learning","volume":"43","author":"Wang","year":"2022","journal-title":"Structures"},{"key":"10.1016\/j.engappai.2026.114341_bib54","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2021.108761","article-title":"Ultrasonic guided wave imaging with deep learning: applications in corrosion mapping","volume":"169","author":"Wang","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114341_bib55","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.jcsr.2011.08.002","article-title":"Effects of debonding on circular CFST stub columns","volume":"69","author":"Xue","year":"2012","journal-title":"J. Constr. Steel Res."},{"key":"10.1016\/j.engappai.2026.114341_bib56","article-title":"Short-time multi-energy load forecasting method based on CNN-Seq2Seq model with attention mechanism","volume":"5","author":"Zhang","year":"2021","journal-title":"Mach. Learn. Appl."},{"key":"10.1016\/j.engappai.2026.114341_bib57","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.eng.2017.12.003","article-title":"Concrete-filled steel tube arch bridges in China","volume":"4","author":"Zheng","year":"2018","journal-title":"Engineering"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626006226?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626006226?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:09:33Z","timestamp":1776125373000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626006226"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":57,"alternative-id":["S0952197626006226"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114341","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Quantitative assessment of interfacial debonding in large-span concrete-filled steel tube arch bridges via interpretable deep hybrid learning and ultrasonic inspection","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114341","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114341"}}