{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T12:15:48Z","timestamp":1781180148351,"version":"3.54.1"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T00:00:00Z","timestamp":1779494400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006284","name":"Pipeline and Hazardous Materials Safety Administration","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006284","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reliability Engineering & System Safety"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.ress.2026.112929","type":"journal-article","created":{"date-parts":[[2026,5,24]],"date-time":"2026-05-24T00:39:03Z","timestamp":1779583143000},"page":"112929","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Optimization of risk-based and cost-minimized maintenance strategy for corroded pipeline using reinforcement learning"],"prefix":"10.1016","volume":"276","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7824-3710","authenticated-orcid":false,"given":"Bingyan","family":"Cui","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8666-6900","authenticated-orcid":false,"given":"Hao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ress.2026.112929_bib0001","series-title":"Proceedings of the Rio pipeline conference & exposition","article-title":"Effects of in-line inspection sizing uncertainties on in-the-ditch validation: review of results","author":"Huyse","year":"2011"},{"issue":"6","key":"10.1016\/j.ress.2026.112929_bib0002","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1080\/15732479.2016.1187632","article-title":"Inspection and maintenance of oil & gas pipelines: a review of policies","volume":"13","author":"Iqbal","year":"2017","journal-title":"Struct Infrastruct Eng"},{"key":"10.1016\/j.ress.2026.112929_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111663","article-title":"Multi-objective optimization for pipeline systems: a maintenance model using NSGA-II considering flow capacity and total cost","volume":"266","author":"Xie","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"issue":"3","key":"10.1016\/j.ress.2026.112929_bib0004","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1007\/s10311-018-0731-x","article-title":"Factors influencing corrosion of metal pipes in soils","volume":"16","author":"Wasim","year":"2018","journal-title":"Environ Chem Lett"},{"issue":"3","key":"10.1016\/j.ress.2026.112929_bib0005","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1061\/(ASCE)PS.1949-1204.0000081","article-title":"Novel approach in pipe condition scoring","volume":"2","author":"Opila Mary","year":"2011","journal-title":"J Pipeline Syst Eng Pract"},{"issue":"1","key":"10.1016\/j.ress.2026.112929_bib0006","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.cie.2012.02.002","article-title":"An overview of time-based and condition-based maintenance in industrial application","volume":"63","author":"Ahmad","year":"2012","journal-title":"Comput Ind Eng"},{"issue":"3","key":"10.1016\/j.ress.2026.112929_bib0007","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1108\/13552510610685138","article-title":"Strategically optimum maintenance of monitoring-enabled multi-component systems using continuous-time jump deterioration models","volume":"12","author":"Gupta","year":"2006","journal-title":"J Qual Maint Eng"},{"key":"10.1016\/j.ress.2026.112929_bib0008","doi-asserted-by":"crossref","unstructured":"Zio, E., Prognostics and health management of industrial equipment. Diagnostics and prognostics of engineering systems: methods and techniques, 2013: p. 333\u201356.","DOI":"10.4018\/978-1-4666-2095-7.ch017"},{"issue":"3","key":"10.1016\/j.ress.2026.112929_bib0009","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1061\/(ASCE)PS.1949-1204.0000121","article-title":"Risk-based maintenance of a cross-country petroleum pipeline system","volume":"4","author":"Dawotola Alex","year":"2013","journal-title":"J Pipeline Syst Eng Pract"},{"issue":"4","key":"10.1016\/j.ress.2026.112929_bib0010","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.jlp.2005.06.036","article-title":"Application of risk based inspection in refinery and processing piping","volume":"18","author":"Chang","year":"2005","journal-title":"J Loss Prev Process Ind"},{"key":"10.1016\/j.ress.2026.112929_bib0011","doi-asserted-by":"crossref","unstructured":"Nessim, M., Yue H., and Zhou J., Application of reliability based design and assessment to maintenance and protection decisions for natural gas pipelines. 2010. p. 625\u201334.","DOI":"10.1115\/IPC2010-31555"},{"key":"10.1016\/j.ress.2026.112929_bib0012","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.psep.2019.09.003","article-title":"Uncertainty handling in fault tree based risk assessment: state of the art and future perspectives","volume":"131","author":"Yazdi","year":"2019","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112929_bib0013","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.jlp.2017.06.019","article-title":"Optimal maintenance strategy for corroded subsea pipelines","volume":"49","author":"Li","year":"2017","journal-title":"J Loss Prev Process Ind"},{"key":"10.1016\/j.ress.2026.112929_bib0014","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.jhazmat.2018.09.044","article-title":"Multi-level optimization of maintenance plan for natural gas system exposed to deterioration process","volume":"362","author":"BahooToroody","year":"2019","journal-title":"J Hazard Mater"},{"key":"10.1016\/j.ress.2026.112929_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpvp.2020.104105","article-title":"Availability-based reliability-centered maintenance planning for gas transmission pipelines","volume":"183","author":"Zakikhani","year":"2020","journal-title":"Int J Press Vessels Pip"},{"key":"10.1016\/j.ress.2026.112929_bib0016","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/j.psep.2022.12.041","article-title":"Maintenance strategy optimization of pipeline system with multi-stage corrosion defects based on heuristically genetic algorithm","volume":"170","author":"Xie","year":"2023","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112929_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109894","article-title":"Multi-objective maintenance strategy for corroded pipelines considering the correlation of different failure modes","volume":"243","author":"Wang","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112929_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111640","article-title":"Resilience modeling for an engineered network with multimodal performance under multiple recurrent hazards","volume":"266","author":"Wei","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112929_bib0019","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/23789689.2025.2574202","article-title":"Optimal maintenance of a critical infrastructure subject to dependent recurrent hazards","author":"Wei","year":"2025","journal-title":"Sustain Resilient Infrastruct"},{"key":"10.1016\/j.ress.2026.112929_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2024.110170","article-title":"A probabilistic analysis method for evaluating the safety & resilience of urban gas pipeline network","volume":"248","author":"Chen","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112929_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2026.112249","article-title":"Distributed hierarchical reinforcement learning for dynamic maintenance scheduling of large-scale airline fleets","volume":"271","author":"Zhang","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112929_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111889","article-title":"A reinforcement learning approach to network-level maintenance planning of co-located road and water infrastructures with interdependencies","volume":"267","author":"Wang","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112929_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.strusafe.2019.101906","article-title":"Optimal policy for structure maintenance: a deep reinforcement learning framework","volume":"83","author":"Wei","year":"2020","journal-title":"Struct Saf"},{"issue":"11","key":"10.1016\/j.ress.2026.112929_bib0024","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.1111\/mice.12558","article-title":"Deep reinforcement learning for long-term pavement maintenance planning","volume":"35","author":"Yao","year":"2020","journal-title":"Comput-Aided Civ Infrastruct Eng"},{"issue":"2","key":"10.1016\/j.ress.2026.112929_bib0025","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.ijtst.2021.05.006","article-title":"Planning maintenance and rehabilitation activities for airport pavements: a combined supervised machine learning and reinforcement learning approach","volume":"11","author":"Barua","year":"2022","journal-title":"Int J Transp Sci Technol"},{"key":"10.1016\/j.ress.2026.112929_bib0026","doi-asserted-by":"crossref","first-page":"5708","DOI":"10.3390\/s20195708","article-title":"Condition-based maintenance with reinforcement learning for dry gas pipeline subject to internal corrosion","volume":"20","author":"Mahmoodzadeh","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.ress.2026.112929_bib0027","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.psep.2024.05.011","article-title":"Pipeline corrosion prediction and uncertainty analysis with an ensemble Bayesian neural network approach","volume":"187","author":"Cui","year":"2024","journal-title":"Process Saf Environ Prot"},{"issue":"1","key":"10.1016\/j.ress.2026.112929_bib0028","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1007\/s10462-023-10562-9","article-title":"A survey of uncertainty in deep neural networks","volume":"56","author":"Gawlikowski","year":"2023","journal-title":"Artif Intell Rev"},{"issue":"5","key":"10.1016\/j.ress.2026.112929_bib0029","doi-asserted-by":"crossref","first-page":"332","DOI":"10.5006\/1.3319138","article-title":"Predictive model for pitting corrosion in buried oil and gas pipelines","volume":"65","author":"Vel\u00e1zquez","year":"2009","journal-title":"Corrosion"},{"issue":"11","key":"10.1016\/j.ress.2026.112929_bib0030","doi-asserted-by":"crossref","first-page":"2628","DOI":"10.1016\/j.corsci.2009.06.052","article-title":"Modelling steel corrosion damage in soil environment","volume":"51","author":"Alamilla","year":"2009","journal-title":"Corros Sci"},{"key":"10.1016\/j.ress.2026.112929_bib0031","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpvp.2024.105234","article-title":"A probabilistic framework for external pitting corrosion growth modelling for buried steel pipelines considering soil properties","volume":"210","author":"Majdabadi Farahani","year":"2024","journal-title":"Int J Press Vessels Pip"},{"key":"10.1016\/j.ress.2026.112929_bib0032","doi-asserted-by":"crossref","first-page":"221","DOI":"10.4028\/www.scientific.net\/SSP.110.221","article-title":"Reliability of buried pipeline using a theory of probability of failure","volume":"110","author":"Lee","year":"2005","journal-title":"Solid State Phenom"},{"issue":"10","key":"10.1016\/j.ress.2026.112929_bib0033","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1016\/j.ijpvp.2010.07.011","article-title":"System reliability of corroding pipelines","volume":"87","author":"Zhou","year":"2010","journal-title":"Int J Press Vessels Pip"},{"issue":"3","key":"10.1016\/j.ress.2026.112929_bib0034","article-title":"Time-dependent reliability analysis of corroded buried pipelines considering external defects","volume":"22","author":"Miran Seyedeh","year":"2016","journal-title":"J Infrastruct Syst"},{"key":"10.1016\/j.ress.2026.112929_bib0035","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.engfailanal.2019.01.064","article-title":"Reliability assessments of corroded pipelines based on internal pressure \u2013 a review","volume":"98","author":"Amaya-G\u00f3mez","year":"2019","journal-title":"Eng Fail Anal"},{"key":"10.1016\/j.ress.2026.112929_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.engfailanal.2020.104891","article-title":"Probabilistic investigation on the reliability assessment of mid- and high-strength pipelines under corrosion and fracture conditions","volume":"118","author":"Guillal","year":"2020","journal-title":"Eng Fail Anal"},{"key":"10.1016\/j.ress.2026.112929_bib0037","first-page":"323","article-title":"Determination of burst pressure of thin-walled pressure vessels","volume":"67","author":"Gajdo\u0161","year":"2012","journal-title":"Eng Mech"},{"issue":"7","key":"10.1016\/j.ress.2026.112929_bib0038","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1139\/cjce-2016-0519","article-title":"Revisiting burst pressure models for corroded pipelines","volume":"44","author":"Phan","year":"2017","journal-title":"Can J Civ Eng"},{"key":"10.1016\/j.ress.2026.112929_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpvp.2022.104656","article-title":"Development of probabilistic failure pressure models for pipelines with single corrosion defect","volume":"197","author":"Kere","year":"2022","journal-title":"Int J Press Vessels Pip"},{"key":"10.1016\/j.ress.2026.112929_bib0040","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.compstruct.2014.04.015","article-title":"Analysis of a glass fibre reinforced polyurethane composite repair system for corroded pipelines at elevated temperatures","volume":"114","author":"da Costa Mattos","year":"2014","journal-title":"Compos Struct"},{"issue":"4","key":"10.1016\/j.ress.2026.112929_bib0041","doi-asserted-by":"crossref","DOI":"10.1115\/1.4036534","article-title":"Nanofillers reinforced polymer composites wrap to repair corroded steel pipe lines","volume":"139","author":"Chandra Khan","year":"2017","journal-title":"J Press Vessel Technol"},{"key":"10.1016\/j.ress.2026.112929_bib0042","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.engfailanal.2016.09.001","article-title":"Gas transmission pipeline failure probability estimation and defect repairs activities based on in-line inspection data","volume":"70","author":"Witek","year":"2016","journal-title":"Eng Fail Anal"},{"key":"10.1016\/j.ress.2026.112929_bib0043","first-page":"1995","article-title":"Dueling network architectures for deep reinforcement learning","author":"Ziyu","year":"2015","journal-title":"PMLR"},{"key":"10.1016\/j.ress.2026.112929_bib0044","doi-asserted-by":"crossref","unstructured":"ROBOT LEARNING, edited by Jonathan H. Connell and Sridhar Mahadevan, Kluwer, Boston, 1993\/1997, xii+240\u2006pp., ISBN 0-7923-9365-1 (Hardback, 218.00 Guilders, $120.00, \u00a389.95). Robotica, 1999. 17(2): p. 229\u201335.","DOI":"10.1017\/S0263574799271172"},{"key":"10.1016\/j.ress.2026.112929_bib0045","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.psep.2019.11.031","article-title":"A risk-based approach to determination of optimal inspection intervals for buried oil pipelines","volume":"134","author":"Abubakirov","year":"2020","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112929_bib0046","unstructured":"Schaul, T., Quan, J., Antonoglou, I., Silver, D., Prioritized experience replay. arXiv preprint, 2015. arXiv:1511.05952."},{"issue":"7540","key":"10.1016\/j.ress.2026.112929_bib0047","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"Mnih","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.ress.2026.112929_bib0048","series-title":"The assessment of the effects of deposits and corrosion on flow efficiency in petroleum products pipelines for integrity management","author":"Marigi","year":"2024"},{"key":"10.1016\/j.ress.2026.112929_bib0049","unstructured":"EPA, U., Composite wrap for non-leaking pipeline defects, in Lessons Learn. from Nat. Gas STAR Partners. 2006. p. 1\u201311."}],"container-title":["Reliability Engineering & System Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026007398?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026007398?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T22:21:45Z","timestamp":1780006905000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0951832026007398"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":49,"alternative-id":["S0951832026007398"],"URL":"https:\/\/doi.org\/10.1016\/j.ress.2026.112929","relation":{},"ISSN":["0951-8320"],"issn-type":[{"value":"0951-8320","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Optimization of risk-based and cost-minimized maintenance strategy for corroded pipeline using reinforcement learning","name":"articletitle","label":"Article Title"},{"value":"Reliability Engineering & System Safety","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ress.2026.112929","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"112929"}}