Dynamic risk assessment methodology of operation process for deepwater oil and gas equipment

Hatefi, 2023, Risk assessment of oil and gas drilling operation: an empirical case using a hybrid GROC-VIMUN-modified FMEA method, Process Saf Environ Prot, 170, 392, 10.1016/j.psep.2022.12.006 Roberts, 2015, Everything was fine”*: an analysis of the drill crew's situation awareness on Deepwater Horizon, J Loss Prev Process Ind, 38, 87, 10.1016/j.jlp.2015.08.008 Incardona, 2014, Deepwater Horizon crude oil impacts the developing hearts of large predatory pelagic fish, Proc Natl Acad Sci, 111, E1510, 10.1073/pnas.1320950111 Yang, 2013, Precursor-based hierarchical Bayesian approach for rare event frequency estimation: a case of oil spill accidents, Process Saf Environ Prot, 91, 333, 10.1016/j.psep.2012.07.006 Maidana, 2023, Supervised dynamic probabilistic risk assessment: review and comparison of methods, Reliab Eng Syst Safe, 230, 10.1016/j.ress.2022.108889 Dui, 2023, Importance measure-based resilience management: review, methodology and perspectives on maintenance, Reliab Eng Syst Safe, 237, 10.1016/j.ress.2023.109383 Levitin, 2022, Mission aborting and system rescue for multi-state systems with arbitrary structure, Reliab Eng Syst Safe, 219, 10.1016/j.ress.2021.108225 Zhou, 2023, An improved method to search all minimal paths in networks, IEEE Trans Reliab Bai, 2021, Improved resilience measure for component recovery priority in power grids, Front Eng Manag, 8, 545, 10.1007/s42524-021-0161-5 Dui, 2023, Cascading failures and resilience optimization of hospital infrastructure systems against the COVID-19, Comput Ind Eng, 179, 10.1016/j.cie.2023.109158 Wang, 2021, Current status and prospects of reliability systems engineering in China, Front Eng Manag, 8, 492, 10.1007/s42524-021-0172-2 Dui, 2022, Evaluation methodology for preventive maintenance in multi-state manufacturing systems considering different costs, Int J Prod Res, 10.1080/00207543.2022.2127163 Liu, 2021, Risk assessment on deepwater drilling well control based on dynamic Bayesian network, Process Saf Environ Prot, 149, 643, 10.1016/j.psep.2021.03.024 Cai, 2015, Real-time reliability evaluation methodology based on dynamic Bayesian networks: a case study of a subsea pipe ram BOP system, ISA Trans, 58, 595, 10.1016/j.isatra.2015.06.011 Hu, 2022, Guided simulation for dynamic probabilistic risk assessment of complex systems: concept, method, and application, Reliab Eng Syst Safe, 217, 10.1016/j.ress.2021.108047 Raveendran, 2022, A comprehensive review on dynamic risk analysis methodologies, J Loss Prev Process Ind, 76, 10.1016/j.jlp.2022.104734 Bhatia, 2019, Dynamic risk-based inspection methodology, J Los Preven Pro, 62 Kaneko, 2023, Novel method of dynamic event tree keeping the number of simulations in risk analysis small, Reliab Eng Syst Safe, 231, 10.1016/j.ress.2022.109009 Singh, 2022, Integrating α-cut interval based fuzzy fault tree analysis with Bayesian network for criticality analysis of submarine pipeline leakage: a novel approach, Process Saf Environ Prot, 166, 189, 10.1016/j.psep.2022.07.058 Almeida, 2023, Combining the bow-tie method and fuzzy logic using Mamdani inference model, Process Saf Environ Prot, 169, 159, 10.1016/j.psep.2022.11.005 Pan, 2023, A reliability analysis method based on the mixed correlated competition model considering multi-performance degradation and sudden failures, Eng Fail Anal, 146, 10.1016/j.engfailanal.2023.107126 Wang, 2023, Piecewise deterministic Markov process for condition-based imperfect maintenance models, Reliab Eng Syst Safe, 236, 10.1016/j.ress.2023.109271 He, 2022, Inversion-based model for quantitative interpretation by a dual- measurement points in managed pressure drilling, Process Saf Environ Prot, 165, 969, 10.1016/j.psep.2022.04.035 Li, 2023, Implicit Kalman filtering method for remaining useful life prediction of rolling bearing with adaptive detection of degradation stage transition point, Reliab Eng Syst Safe, 235, 10.1016/j.ress.2023.109269 Yu, 2019, Activated sludge process faults diagnosis based on an improved particle filter algorithm, Process Saf Environ Prot, 127, 66, 10.1016/j.psep.2019.04.021 Liu, 2023, Efficient Bayesian model updating for dynamic systems, Reliab Eng Syst Safe, 236, 10.1016/j.ress.2023.109294 Zhou, 2021, Sub-period division strategies combined with multiway principle component analysis for fault diagnosis on sequence batch reactor of wastewater treatment process in paper mill, Process Saf Environ Prot, 146, 9, 10.1016/j.psep.2020.08.032 Hazra, 2022, Likelihood-free Hamiltonian Monte Carlo for modelling piping degradation and remaining useful life prediction using the mixed gamma process, Int J Pres Ves Pip, 200, 10.1016/j.ijpvp.2022.104834 Lou, 2022, A bidirectional wear model based on Inverse Gaussian (IG) process for PEEK against AISI630 stainless steel in seawater hydraulic components, Tribology Int, 175, 10.1016/j.triboint.2022.107815 Ma, 2023, A multi-phase Wiener process-based degradation model with imperfect maintenance activities, Reliab Eng Syst Safe, 232, 10.1016/j.ress.2022.109075 Xu, 2023, A two-stage estimation method based on Conceptors-aided unsupervised clustering and convolutional neural network classification for the estimation of the degradation level of industrial equipment, Expert Syst Appl, 213, 10.1016/j.eswa.2022.118962 Chen, 2023, Coupling of adjoint-based Markov/CCMT predictive analytics with data assimilation for real-time risk scenario forecasting of industrial digital process control systems, Process Saf Environ Prot, 171, 951, 10.1016/j.psep.2023.01.077 Wu, 2022, A Markov resilience assessment framework for tension leg platform under mooring failure, Reliab Eng Syst Safe, 231 Berrouanea, 2020, Bayesian Stochastic Petri Nets (BSPN) - a new modelling tool for dynamic safety and reliability analysis, Reliab Eng Syst Safe, 193 Kamil, 2019, Dynamic domino effect risk assessment using Petri-nets, Process Saf Environ Prot, 124, 308, 10.1016/j.psep.2019.02.019 George, 2021, Evolution of Safety and Security Risk Assessment methodologies towards the use of Bayesian Networks in Process Industries, Process Saf Environ Prot, 149, 758, 10.1016/j.psep.2021.03.031 Wang, 2021, Reliabilities analysis of evacuation on offshore platforms: a dynamic Bayesian network model, Process Saf Environ Prot, 150, 179, 10.1016/j.psep.2021.04.009 Unluakın, 2021, Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs, Reliab Eng Syst Safe, 211 Xu, 2023, Dynamic risk assessment for underground gas storage facilities based on Bayesian network, J Loss Prevent Proc, 82, 10.1016/j.jlp.2022.104961 Han, 2021, Hybrid dynamic risk modelling for safety critical equipment on offshore installations, Process Saf Environ Prot, 156, 482, 10.1016/j.psep.2021.10.038 Li, 2022, A Copula-Bayesian approach for risk assessment of decommissioning operation of aging subsea pipelines, Process Saf Environ Prot, 167, 412, 10.1016/j.psep.2022.09.019 Wang, 2022, A dynamic failure analysis methodology for fault diagnosis of fatigue cracks of subsea wellhead connectors with material aging, Process Saf Environ Prot, 159, 36, 10.1016/j.psep.2021.12.044 Li, 2016, Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesian network, Process Saf Environ Prot, 103, 163, 10.1016/j.psep.2016.06.006 Cai, 2013, Performance evaluation of subsea BOP control systems using dynamic Bayesian networks with imperfect repair and preventive maintenance, Eng Appl Artif Intell, 26, 2661, 10.1016/j.engappai.2013.08.011 Liu, 2022, Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model, Reliab Eng Syst Safe, 218, 10.1016/j.ress.2021.108160 Cai, 2020, Remaining useful life estimation of structure systems under the influence of multiple causes: subsea pipelines as a case study, IEEE Trans Ind Electron, 67, 5737, 10.1109/TIE.2019.2931491 Cai, 2011, Optimization of submersible solenoid valves for subsea blowout preventers, IEEE Tran Magn, 47, 451, 10.1109/TMAG.2010.2100825 Elusakina, 2020, Reliability analysis of subsea blowout preventers with condition-based maintenance using stochastic Petri nets, J Loss Prevent Proc, 63