{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T21:58:59Z","timestamp":1780955939658,"version":"3.54.1"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reliability Engineering & System Safety"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ress.2026.112874","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T02:39:05Z","timestamp":1778812745000},"page":"112874","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P2","title":["A gas turbine performance mitigation control method based on state assessment"],"prefix":"10.1016","volume":"275","author":[{"given":"Xiaoyu","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4953-8886","authenticated-orcid":false,"given":"Yunpeng","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongsheng","family":"Qu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weixing","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujia","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.ress.2026.112874_bib0001","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TCST.2018.2870044","article-title":"Ensemble Kalman filters for state estimation and prediction of two-time scale nonlinear systems with application to gas turbine engines","volume":"27","author":"Daroogheh","year":"2018","journal-title":"IEEE Trans Control Syst Technol"},{"key":"10.1016\/j.ress.2026.112874_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2024.110316","article-title":"Distributed-collaborative surrogate modeling approach for creep-fatigue reliability assessment of turbine blades considering multi-source uncertainty","volume":"250","author":"Gao","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112874_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.applthermaleng.2019.114664","article-title":"Anomaly detection of gas turbines based on normal pattern extraction","volume":"166","author":"Bai","year":"2020","journal-title":"Appl Therm Eng"},{"issue":"4","key":"10.1016\/j.ress.2026.112874_bib0004","doi-asserted-by":"crossref","first-page":"1184","DOI":"10.1109\/TCST.2015.2480003","article-title":"Sensor fault detection, isolation, and identification using multiple-model-based hybrid Kalman filter for gas turbine engines","volume":"24","author":"Pourbabaee","year":"2015","journal-title":"IEEE Trans Control Syst Technol"},{"key":"10.1016\/j.ress.2026.112874_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118814","article-title":"Hierarchical level fault detection and diagnosis of ship engine systems","volume":"213","author":"Kang","year":"2023","journal-title":"Expert Syst Appl"},{"key":"10.1016\/j.ress.2026.112874_bib0006","series-title":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","first-page":"1","article-title":"Hierarchical health assessment of equipment with uncertain fault diagnosis result","author":"Zhang","year":"2019"},{"key":"10.1016\/j.ress.2026.112874_bib0007","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.ymssp.2017.11.024","article-title":"A review on the application of deep learning in system health management","volume":"107","author":"Khan","year":"2018","journal-title":"Mech Syst Signal Process"},{"key":"10.1016\/j.ress.2026.112874_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.110863","article-title":"A distributed inference method integrating causal analysis and surrogate models for optimizing tuned mass damper parameters to enhance offshore wind turbine safety","volume":"257","author":"Zhang","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"issue":"2","key":"10.1016\/j.ress.2026.112874_bib0009","first-page":"664","article-title":"A kernel entropy method and its application in monitoring and assessment of wind turbine degradation performance","volume":"29","author":"Ren","year":"2022","journal-title":"Teh Vjesn"},{"issue":"2","key":"10.1016\/j.ress.2026.112874_bib0010","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1109\/TPWRS.2014.2360851","article-title":"Hierarchical risk assessment of transmission system considering the influence of active distribution network","volume":"30","author":"Jia","year":"2015","journal-title":"IEEE Trans Power Syst"},{"issue":"2","key":"10.1016\/j.ress.2026.112874_bib0011","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1007\/s41660-023-00372-5","article-title":"Artificial neural networks based parametric curve generation for health assessment of industrial gas turbine systems","volume":"8","author":"Raghavan","year":"2024","journal-title":"Process Integr Optim Sustain"},{"issue":"11","key":"10.1016\/j.ress.2026.112874_bib0012","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6501\/ae1a9e","article-title":"Gas turbine anomaly detection using a spatial-temporal feature-enhanced fusion network","volume":"36","author":"Han","year":"2025","journal-title":"Meas Sci Technol"},{"key":"10.1016\/j.ress.2026.112874_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111261","article-title":"Practical semi-supervised learning framework for real-time warning of aerodynamic instabilities: applications from compressors to gas turbine engines","volume":"264","author":"Zhang","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112874_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109404","article-title":"Deep learning framework for gas turbine performance digital twin and degradation prognostics from airline operator perspective","volume":"238","author":"Sun","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112874_bib0015","article-title":"An anomaly detection method for gas turbines in power plants using conditional variational autoencoder optimized with self-attention","volume":"353","author":"Tanaka","year":"2024","journal-title":"Appl Energy"},{"issue":"5","key":"10.1016\/j.ress.2026.112874_bib0016","first-page":"7215","article-title":"LSTM-fuzzy logic for fault forecasting and mitigation in propulsion system","volume":"20","author":"Kim","year":"2024","journal-title":"IEEE Trans Ind Inform"},{"key":"10.1016\/j.ress.2026.112874_bib0017","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2025.122389","article-title":"Research on marine gas turbine acoustic signals anomaly detection method based on physical prior knowledge and spatial-temporal graph neural network","volume":"340","author":"Han","year":"2025","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112874_bib0018","article-title":"Adaptive turbofan engine health assessment for multi-component performance degradation coupling scenarios: a spatiotemporal attention graph convolutional network approach","volume":"211","author":"Wang","year":"2025","journal-title":"Mech Syst Signal Process"},{"issue":"11","key":"10.1016\/j.ress.2026.112874_bib0019","doi-asserted-by":"crossref","first-page":"966","DOI":"10.3390\/aerospace10110966","article-title":"Research on a method for online damage evaluation of turbine blades in a gas turbine based on operating conditions","volume":"10","author":"Zhu","year":"2023","journal-title":"Aerospace"},{"issue":"1","key":"10.1016\/j.ress.2026.112874_bib0020","doi-asserted-by":"crossref","first-page":"37","DOI":"10.3390\/jmse10010037","article-title":"Fatigue assessment of moorings for floating offshore wind turbines by advanced spectral analysis methods","volume":"10","author":"Piscopo","year":"2021","journal-title":"J Mar Sci Eng"},{"key":"10.1016\/j.ress.2026.112874_bib0021","article-title":"An improved Cox proportional hazards model for reliability analysis of aviation gas turbines considering varying environmental conditions and operational settings","author":"Cui","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112874_bib0022","article-title":"Degradation performance rapid prediction and multi-objective operation optimization of gas turbine blades","volume":"247","author":"Zhao","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"issue":"6","key":"10.1016\/j.ress.2026.112874_bib0023","first-page":"885","article-title":"A proposed algorithm based on long short-term memory network and gradient boosting for aeroengine thrust estimation on transition State","volume":"238","author":"Chen","year":"2024","journal-title":"Proc Inst Mech Eng G: J Aerosp Eng"},{"issue":"2","key":"10.1016\/j.ress.2026.112874_bib0024","doi-asserted-by":"crossref","DOI":"10.1587\/elex.20.20230444","article-title":"An optimization algorithm used in PMSM model predictive control","volume":"21","author":"Wang","year":"2024","journal-title":"IEICE Electron Express"},{"issue":"6","key":"10.1016\/j.ress.2026.112874_bib0025","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.1109\/TCST.2023.3254137","article-title":"An online joint optimization\u2013estimation architecture for distribution networks","volume":"31","author":"Guo","year":"2023","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"1","key":"10.1016\/j.ress.2026.112874_bib0026","first-page":"101","article-title":"Auto-updating model-based control for thrust variation mitigation and acceleration performance enhancement of gas turbine aero-engines","volume":"38","author":"He","year":"2025","journal-title":"Chin J Aeronaut"},{"key":"10.1016\/j.ress.2026.112874_bib0027","article-title":"A new control strategy for compensating degraded performance in gas turbine combined cycles","volume":"283","author":"Rodriguez","year":"2023","journal-title":"Energy"},{"key":"10.1016\/j.ress.2026.112874_bib0028","article-title":"A novel model-based multivariable framework for aircraft gas turbine engine limit protection control","volume":"132","author":"Wang","year":"2023","journal-title":"Aerosp Sci Technol"},{"issue":"3","key":"10.1016\/j.ress.2026.112874_bib0029","first-page":"1345","article-title":"Improving the reliability of aero-engine control system via virtual sensor-assisted fault-tolerant control","volume":"32","author":"Patel","year":"2024","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"4","key":"10.1016\/j.ress.2026.112874_bib0030","first-page":"2537","article-title":"Unknown input observer-based robust fault estimation for systems corrupted by partially decoupled disturbances","volume":"63","author":"Gao","year":"2015","journal-title":"IEEE Trans Ind Electron"},{"issue":"1","key":"10.1016\/j.ress.2026.112874_bib0031","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.apenergy.2004.03.006","article-title":"Matlab\/Simulink-based simulation for digital-control system of marine three-shaft gas-turbine","volume":"80","author":"Yu","year":"2005","journal-title":"Appl Energy"},{"issue":"6","key":"10.1016\/j.ress.2026.112874_bib0032","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1109\/72.963766","article-title":"Self-organizing maps, vector quantization, and mixture modeling","volume":"12","author":"Heskes","year":"2001","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"10.1016\/j.ress.2026.112874_bib0033","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/4235.985692","article-title":"The particle swarm-explosion, stability, and convergence in a multidimensional complex space","volume":"6","author":"Clerc","year":"2002","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"10.1016\/j.ress.2026.112874_bib0034","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0370-1573(00)00070-3","article-title":"The random walk's guide to anomalous diffusion: a fractional dynamics approach","volume":"339","author":"Metzler","year":"2000","journal-title":"Phys Rep"},{"key":"10.1016\/j.ress.2026.112874_bib0035","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.isatra.2024.11.004","article-title":"An overhaul cycle performance degradation modeling method for marine gas turbines","volume":"156","author":"Luan","year":"2025","journal-title":"ISA Trans"},{"key":"10.1016\/j.ress.2026.112874_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.apenergy.2024.123419","article-title":"Research on gas turbine health assessment method based on physical prior knowledge and spatial-temporal graph neural network","volume":"367","author":"Cheng","year":"2024","journal-title":"Appl Energy"},{"key":"10.1016\/j.ress.2026.112874_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129326","article-title":"Integrated scheduling method for heavy-haul transportation with virtual coupling based on two-phase optimization strategy","volume":"297","author":"Wu","year":"2026","journal-title":"Expert Syst Appl"},{"issue":"6","key":"10.1016\/j.ress.2026.112874_bib0038","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/s40314-025-03267-y","article-title":"FDIPA-SOC: a MATLAB package for nonlinear second-order cone programs: A. Canelas et al","volume":"44","author":"Canelas","year":"2025","journal-title":"Comput Appl Math"}],"container-title":["Reliability Engineering & System Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026006848?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026006848?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T21:14:24Z","timestamp":1780953264000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0951832026006848"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":38,"alternative-id":["S0951832026006848"],"URL":"https:\/\/doi.org\/10.1016\/j.ress.2026.112874","relation":{},"ISSN":["0951-8320"],"issn-type":[{"value":"0951-8320","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A gas turbine performance mitigation control method based on state assessment","name":"articletitle","label":"Article Title"},{"value":"Reliability Engineering & System Safety","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ress.2026.112874","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"112874"}}