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Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments
16 references·4 citing·50 second hop
Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments (2023)Integration of functional resonance analy…Resilience evaluation of maritime liquid cargo emergency response by integrating FRAM and a BN: A case study of a propylene leakage emergency scenario (2022)Resilience evaluation of mari…Application of integrated STAMP-BN in safety analysis of subsea blowout preventer (2022)Application of integrated STA…A data-driven Bayesian network model integrating physical knowledge for prioritization of risk influencing factors (2022)A data-driven Bayesian networ…Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model (2021)Risk coupling analysis of sub…Risk assessment on deepwater drilling well control based on dynamic Bayesian network (2021)Risk assessment on deepwater …Dynamic risk analysis of emergency operations in deepwater blowout accidents (2021)Dynamic risk analysis of emer…Operational risk analysis of blowout scenario in offshore drilling operation (2020)Operational risk analysis of …Modeling and analysis of flammable gas dispersion and deflagration from offshore platform blowout (2020)Modeling and analysis of flam…Human reliability assessment for complex physical operations in harsh operating conditions (2020)Human reliability assessment …Framing the FRAM: A literature review on the functional resonance analysis method (2020)Framing the FRAM: A literatur…A novel approach to reduce fire-induced domino effect risk by leveraging loading/unloading demands in chemical industrial parks (2020)A novel approach to reduce fi…Human Error Probability Assessment During Maintenance Activities of Marine Systems (2017)Human Error Probability Asses…Understanding industrial safety: Comparing Fault tree, Bayesian network, and FRAM approaches (2016)Understanding industrial safe…Dynamic hazard identification and scenario mapping using Bayesian network (2016)Dynamic hazard identification…A Monte Carlo evolution of the Functional Resonance Analysis Method (FRAM) to assess performance variability in complex systems (2016)A Monte Carlo evolution of th…Explosion modeling and analysis of BP Deepwater Horizon accident (2013)Explosion modeling and analys…Risk-accident emergence and prevention method of high-speed railway system: based on an improved Functional Resonance Analysis Method (2025)Risk-accident emergence and p…Using risk data as a source for human reliability assessment during shipping LNG offloading work (2024)Using risk data as a source f…Improving safety in complex systems: A review of integration of functional resonance analysis method with semi‐quantitative and quantitative approaches (2024)Improving safety in complex s…Enhancing emergency response planning for natech accidents in process operations using functional resonance analysis method (FRAM): A case of fuel storage tank farm (2024)Enhancing emergency response …Learning from the Piper Alpha Accident: A Postmortem Analysis of Technical and Organizational Factors (1993)Modelling of BP Texas City refinery accident using dynamic risk assessment approach (2010)Chemical process safety: fundamentals with applications (2011)Combustion products toxicity risk assessment in an offshore installation (2013)Accident modeling of toxic gas-containing flammable gas release and explosion on an offshore platform (2020)The contribution of latent human failures to the breakdown of complex systems (1990)FRAM: The Functional Resonance Analysis Method. 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References

  • 2020Framing the FRAM: A literature review on the functional resonance analysis method299 cited
  • 2016A Monte Carlo evolution of the Functional Resonance Analysis Method (FRAM) to assess performance variability in complex systems224 cited
  • 2017Human Error Probability Assessment During Maintenance Activities of Marine Systems123 cited
  • 2016Dynamic hazard identification and scenario mapping using Bayesian network118 cited
  • 2021Risk assessment on deepwater drilling well control based on dynamic Bayesian network112 cited
  • 2021Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model94 cited
  • 2016Understanding industrial safety: Comparing Fault tree, Bayesian network, and FRAM approaches83 cited
  • 2013Explosion modeling and analysis of BP Deepwater Horizon accident76 cited
  • 2020Operational risk analysis of blowout scenario in offshore drilling operation71 cited
  • 2022Resilience evaluation of maritime liquid cargo emergency response by integrating FRAM and a BN: A case study of a propylene leakage emergency scenario71 cited
  • 2022A data-driven Bayesian network model integrating physical knowledge for prioritization of risk influencing factors68 cited
  • 2020Human reliability assessment for complex physical operations in harsh operating conditions43 cited
  • 2021Dynamic risk analysis of emergency operations in deepwater blowout accidents37 cited

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  • 2020Modeling and analysis of flammable gas dispersion and deflagration from offshore platform blowout36 cited
  • 2020A novel approach to reduce fire-induced domino effect risk by leveraging loading/unloading demands in chemical industrial parks35 cited
  • 2022Application of integrated STAMP-BN in safety analysis of subsea blowout preventer33 cited
  • Cited by

    • 2024Enhancing emergency response planning for natech accidents in process operations using functional resonance analysis method (FRAM): A case of fuel storage tank farm22 cited
    • 2024Using risk data as a source for human reliability assessment during shipping LNG offloading work17 cited
    • 2025Risk-accident emergence and prevention method of high-speed railway system: based on an improved Functional Resonance Analysis Method11 cited
    • 2024Improving safety in complex systems: A review of integration of functional resonance analysis method with semi‐quantitative and quantitative approaches8 cited