{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T07:07:14Z","timestamp":1768720034726,"version":"3.49.0"},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers &amp; Chemical Engineering"],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1016\/j.compchemeng.2021.107290","type":"journal-article","created":{"date-parts":[[2021,3,18]],"date-time":"2021-03-18T02:12:08Z","timestamp":1616033528000},"page":"107290","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":34,"special_numbering":"C","title":["Deeppipe: a customized generative model for estimations of liquid pipeline leakage parameters"],"prefix":"10.1016","volume":"149","author":[{"given":"Jianqin","family":"Zheng","sequence":"first","affiliation":[]},{"given":"Yongtu","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Ning","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Bohong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Taicheng","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Zhengbing","family":"Li","sequence":"additional","affiliation":[]},{"given":"Qi","family":"Liao","sequence":"additional","affiliation":[]},{"given":"Haoran","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.compchemeng.2021.107290_bib0001","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.compchemeng.2017.09.022","article-title":"A novel data-driven leak detection and localization algorithm using the Kantorovich distance","volume":"108","author":"Arifin","year":"2018","journal-title":"Comput. Chem. Eng."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0002","unstructured":"Arjovsky, M. and Bottou, L., 2017. Towards principled methods for training generative adversarial networks. arXiv preprint arXiv:1701.04862."},{"issue":"12","key":"10.1016\/j.compchemeng.2021.107290_bib0003","doi-asserted-by":"crossref","first-page":"2675","DOI":"10.1002\/aic.690441209","article-title":"Leak detection in liquefied gas pipelines by artificial neural networks","volume":"44","author":"Belsito","year":"1998","journal-title":"AIChE J."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0004","series-title":"A review of pipeline leak detection technology, Pipeline systems","first-page":"287","author":"Black","year":"1992"},{"issue":"8","key":"10.1016\/j.compchemeng.2021.107290_bib0005","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1016\/j.ndteint.2006.04.003","article-title":"MFL signals and artificial neural networks applied to detection and classification of pipe weld defects","volume":"39","author":"Carvalho","year":"2006","journal-title":"Ndt & E Int."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0006","series-title":"Advances in neural information processing systems","first-page":"2172","article-title":"Infogan: Interpretable representation learning by information maximizing generative adversarial nets","author":"Chen","year":"2016"},{"issue":"3","key":"10.1016\/j.compchemeng.2021.107290_bib0007","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.1109\/TPWRS.2018.2794541","article-title":"Model-free renewable scenario generation using generative adversarial networks","volume":"33","author":"Chen","year":"2018","journal-title":"IEEE Trans. Power Syst."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0008","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.enbuild.2018.06.029","article-title":"Building occupancy modeling using generative adversarial network","volume":"174","author":"Chen","year":"2018","journal-title":"Energy Build."},{"issue":"3-4","key":"10.1016\/j.compchemeng.2021.107290_bib0009","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.petrol.2005.05.004","article-title":"Leak detection in petroleum pipelines using a fuzzy system","volume":"49","author":"Da Silva","year":"2005","journal-title":"J. Petroleum Sci. Eng."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.compchemeng.2020.106881","article-title":"Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems","volume":"140","author":"Fisher","year":"2020","journal-title":"Comput. Chem. Eng."},{"issue":"468","key":"10.1016\/j.compchemeng.2021.107290_bib0011","first-page":"1976","article-title":"Leak detection and localization in a pipeline system by application of statistical analysis techniques","volume":"51","author":"Fukuda","year":"1985","journal-title":"Nippon Kikai Gakkai Ronbunshu, C Hen"},{"issue":"8","key":"10.1016\/j.compchemeng.2021.107290_bib0012","doi-asserted-by":"crossref","first-page":"1669","DOI":"10.1016\/j.compchemeng.2007.08.011","article-title":"Analysis of the smallest detectable leakage flow rate of negative pressure wave-based leak detection systems for liquid pipelines","volume":"32","author":"Ge","year":"2008","journal-title":"Comput. Chem. Eng."},{"issue":"4","key":"10.1016\/j.compchemeng.2021.107290_bib0013","first-page":"193","article-title":"State-of-the-art in leak detection and localization","volume":"32","author":"Geiger","year":"2006","journal-title":"Oil Gas Eur. Mag."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0014","first-page":"2672","article-title":"Generative adversarial nets","author":"Goodfellow","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0015","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.jhazmat.2017.02.039","article-title":"A method for simulating the entire leaking process and calculating the liquid leakage volume of a damaged pressurized pipeline","volume":"332","author":"He","year":"2017","journal-title":"J. Hazard. Mater."},{"issue":"11","key":"10.1016\/j.compchemeng.2021.107290_bib0016","doi-asserted-by":"crossref","first-page":"4185","DOI":"10.1007\/s11269-015-1053-4","article-title":"An optimization approach to leak detection in pipe networks using simulated annealing","volume":"29","author":"Huang","year":"2015","journal-title":"Water Resour. Manage."},{"issue":"5","key":"10.1016\/j.compchemeng.2021.107290_bib0017","doi-asserted-by":"crossref","first-page":"4279","DOI":"10.1109\/TIE.2017.2764861","article-title":"Novel Leakage Detection by Ensemble CNN-SVM and Graph-based Localization in Water Distribution Systems","volume":"65","author":"Kang","year":"2018","journal-title":"IEEE Trans. Indust. Electron."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0018","series-title":"2008. ICARCV 2008. 10th International Conference on","first-page":"1178","article-title":"A new failure detection method and its application in leak monitor of pipeline, Control, Automation, Robotics and Vision","author":"Li","year":"2008"},{"key":"10.1016\/j.compchemeng.2021.107290_bib0019","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.psep.2019.01.010","article-title":"A novel location algorithm for pipeline leakage based on the attenuation of negative pressure wave","volume":"123","author":"Li","year":"2019","journal-title":"Process Saf. Environ. Prot."},{"issue":"3","key":"10.1016\/j.compchemeng.2021.107290_bib0020","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1016\/j.engappai.2011.08.010","article-title":"Assessing and classifying risk of pipeline third-party interference based on fault tree and SOM","volume":"25","author":"Liang","year":"2012","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0021","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1016\/j.cherd.2018.06.016","article-title":"An MILP approach for detailed scheduling of multi-product pipeline in pressure control mode","volume":"136","author":"Liao","year":"2018","journal-title":"Chem. Eng. Res. Des."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0022","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.cherd.2019.01.017","article-title":"A data-driven method for pipeline scheduling optimization","volume":"144","author":"Liao","year":"2019","journal-title":"Chem. Eng. Res. Des."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0023","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1016\/j.petrol.2018.12.078","article-title":"An integrated detection and location model for leakages in liquid pipelines","volume":"175","author":"Liu","year":"2019","journal-title":"J. Petroleum Sci. Eng."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0024","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.measurement.2019.01.029","article-title":"A leak detection method for oil pipeline based on markov feature and two-stage decision scheme","volume":"138","author":"Liu","year":"2019","journal-title":"Measurement"},{"key":"10.1016\/j.compchemeng.2021.107290_bib0025","series-title":"Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific","first-page":"1","article-title":"Application of negative pressure wave method in nuclear pipeline leakage detection","author":"Liu","year":"2011"},{"key":"10.1016\/j.compchemeng.2021.107290_bib0026","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.psep.2016.08.014","article-title":"A novel noise reduction method applied in negative pressure wave for pipeline leakage localization","volume":"104","author":"Lu","year":"2016","journal-title":"Process Saf. Environ. Prot."},{"issue":"6","key":"10.1016\/j.compchemeng.2021.107290_bib0027","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1016\/j.jlp.2012.05.010","article-title":"A survey on gas leak detection and localization techniques","volume":"25","author":"Murvay","year":"2012","journal-title":"J. Loss Prev. Process Ind."},{"issue":"7","key":"10.1016\/j.compchemeng.2021.107290_bib0028","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1061\/(ASCE)0733-9429(1992)118:7(1031)","article-title":"Leaks in pipe networks","volume":"118","author":"Pudar","year":"1992","journal-title":"J. Hydraul. Eng."},{"issue":"3","key":"10.1016\/j.compchemeng.2021.107290_bib0029","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1080\/00221681003726304","article-title":"Optimum leak detection and calibration of pipe networks by inverse transient analysis","volume":"48","author":"Shamloo","year":"2010","journal-title":"J. Hydraulic Res."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0030","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1016\/j.energy.2014.01.028","article-title":"Pump network optimization for a cooling water system","volume":"67","author":"Sun","year":"2014","journal-title":"Energy"},{"key":"10.1016\/j.compchemeng.2021.107290_bib0031","series-title":"IEEE International Conference on Service Operations and Logistics, and Informatics","first-page":"372","article-title":"Negative pressure wave based pipeline Leak Detection: Challenges and algorithms","author":"Tian","year":"2012"},{"issue":"6","key":"10.1016\/j.compchemeng.2021.107290_bib0032","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1061\/(ASCE)0733-9496(2007)133:6(519)","article-title":"Experimental observation and analysis of inverse transients for pipeline leak detection","volume":"133","author":"V\u00edtkovsk\u00fd","year":"2007","journal-title":"J. Water Resour. Plann. Manage."},{"issue":"1","key":"10.1016\/j.compchemeng.2021.107290_bib0033","doi-asserted-by":"crossref","first-page":"23","DOI":"10.3390\/jmse4010023","article-title":"Consensus ecological risk assessment of potential transportation-related Bakken and Dilbit crude oil spills in the Delaware Bay watershed, USA","volume":"4","author":"Walker","year":"2016","journal-title":"J. Marine Sci. Eng."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0034","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.cherd.2019.03.009","article-title":"Optimisation of a downstream oil supply chain with new pipeline route planning","volume":"145","author":"Wang","year":"2019","journal-title":"Chem. Eng. Res. Des."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0035","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jclepro.2017.08.147","article-title":"An industrial area layout design methodology considering piping and safety using genetic algorithm","volume":"167","author":"Wang","year":"2017","journal-title":"J. Cleaner Prod."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0036","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1016\/j.applthermaleng.2016.08.212","article-title":"Rule-based optimization strategy for energy efficient water networks","volume":"110","author":"Wang","year":"2017","journal-title":"Appl. Therm. Eng."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0037","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.cherd.2016.12.005","article-title":"A chemical industry area-wide layout design methodology for piping implementation","volume":"118","author":"Wu","year":"2017","journal-title":"Chem. Eng. Res. Des."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0038","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.psep.2018.11.009","article-title":"A small leakage detection approach for oil pipeline using an inner spherical ball","volume":"124","author":"Xu","year":"2019","journal-title":"Process Saf. Environ. Prot."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0039","series-title":"2009. ICIEA 2009. 4th IEEE Conference on. IEEE","first-page":"3220","article-title":"Leakage detection and location for long range oil pipeline using negative pressure wave technique, Industrial Electronics and Applications","author":"Yi-bo","year":"2009"},{"key":"10.1016\/j.compchemeng.2021.107290_bib0040","unstructured":"Yu, L., Zhang, W., Wang, J. and Seqgan, Y.Y., 2016. sequence generative adversarial nets with policy gradient. arXiv preprint. arXiv preprint arXiv:1609.05473, 2(3): 5."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0041","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1016\/j.energy.2016.11.027","article-title":"A hybrid computational approach for detailed scheduling of products in a pipeline with multiple pump stations","volume":"119","author":"Zhang","year":"2017","journal-title":"Energy"},{"issue":"7","key":"10.1016\/j.compchemeng.2021.107290_bib0042","first-page":"3143","article-title":"Improved PSO-based Method for Leak Detection and Localization in Liquid Pipelines","volume":"14","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0043","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.ssci.2018.04.003","article-title":"A risk assessment based optimization method for route selection of hazardous liquid railway network","volume":"110","author":"Zhang","year":"2018","journal-title":"Saf. Sci."},{"key":"10.1016\/j.compchemeng.2021.107290_bib0044","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.jclepro.2019.01.032","article-title":"A voyage with minimal fuel consumption for cruise ships","volume":"215","author":"Zheng","year":"2019","journal-title":"J. Cleaner Prod."}],"container-title":["Computers &amp; Chemical Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098135421000685?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098135421000685?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T17:53:21Z","timestamp":1758822801000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0098135421000685"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6]]},"references-count":44,"alternative-id":["S0098135421000685"],"URL":"https:\/\/doi.org\/10.1016\/j.compchemeng.2021.107290","relation":{},"ISSN":["0098-1354"],"issn-type":[{"value":"0098-1354","type":"print"}],"subject":[],"published":{"date-parts":[[2021,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deeppipe: a customized generative model for estimations of liquid pipeline leakage parameters","name":"articletitle","label":"Article Title"},{"value":"Computers & Chemical Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compchemeng.2021.107290","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"107290"}}