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Development of Flammable Dispersion Quantitative Property–Consequence Relationship Models Using Extreme Gradient Boosting
6 references·2 citing·31 second hop
Development of Flammable Dispersion Quantitative Property–Consequence Relationship Models Using Extreme Gradient Boosting (2020)Development of Flammable Dispersion Quant…Modeling and analysis of flammable gas dispersion and deflagration from offshore platform blowout (2020)Modeling and analysis of flam…Review of recent developments of quantitative structure-property relationship models on fire and explosion-related properties (2019)Review of recent developments…Verification and validation of Phast consequence models for accidental releases of toxic or flammable chemicals to the atmosphere (2018)Verification and validation o…CFD modeling of large-scale flammable cloud dispersion using FLACS (2018)CFD modeling of large-scale f…The real-time estimation of hazardous gas dispersion by the integration of gas detectors, neural network and gas dispersion models (2015)The real-time estimation of h…CSB investigation of the explosions and fire at the BP texas city refinery on March 23, 2005 (2006)CSB investigation of the expl…Machine learning based quantitative consequence prediction models for toxic dispersion casualty (2022)Machine learning based quanti…Development of novel combustion risk index for flammable liquids based on unsupervised clustering algorithms (2021)Development of novel combusti…Guidance on risk analysis and safety implications of a large liquefied natural gas (LNG) spill over water. (2004)LNG Risk Based Safety (2010)Validation of FLACS against experimental data sets from the model evaluation database for LNG vapor dispersion (2010)A dynamic multi-agent approach for modeling the evolution of multi-hazard accident scenarios in chemical plants (2020)Dynamic vulnerability assessment of process plants with respect to vapor cloud explosions (2020)A novel vulnerability model considering synergistic effect of fire and overpressure in chemical processing facilities (2021)Emergency Relief System Design Using DIERS Technology (1993)Guidelines for Use of Vapor Cloud Dispersion Models (1996)Guidelines for Chemical Process Quantitative Risk Analysis (2001)Deep learning based quantitative property-consequence relationship (QPCR) models for toxic dispersion prediction (2021)Deep learning-based dispersion prediction model for hazardous chemical leaks using transfer learning (2024)Risk assessment of ammonia bunkering operations: Perspectives on different release scales (2024)Quantitative assessment of hydrocarbon explosion and fire risks in offshore installations (2011)Quantitative risk analysis of oil and gas drilling, using Deepwater Horizon as case study (2011)Quantitative risk analysis of offshore drilling operations: A Bayesian approach (2013)Real-time risk assessment of explosion on offshore platform using Bayesian network and CFD (2021)The mitigation performance of ventilation on the accident consequences of H2S-containing natural gas release (2021)Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments (2023)Combustion hazards posed by the pressurized atomization of high-flashpoint liquids (1994)Liquid flammability ratings predicted by machine learning considering aerosolization (2019)Opportunities and threats to process safety in digitalized process systems—An overview (2022)The Bhopal disaster and its aftermath: a review (2005)Chemical process safety: fundamentals with applications (2011)Recent application of Computational Fluid Dynamics (CFD) in process safety and loss prevention: A review (2020)Predicting possible recommendations related to causes and consequences in the HAZOP study worksheet using natural language processing and machine learning: BERT, clustering, and classification (2024)Integrated quantitative explosion risk assessment and safety zone delineation applied in a pressure vessel adopting PHAST numerical simulation approach: an Iranian case analysis (2025)An Efficient Sampling Technique for Off-Line Quality Control (1997)Information sharing and trust during major incidents: Findings from the oil industry (2012)Advanced methods of risk assessment and management: An overview (2020)Development of an inherent system safety index (ISSI) for ranking of chemical processes at the concept development stage (2021)Predicting flammability-leading properties for liquid aerosol safety via machine learning (2021)
this work references cited by second hop

References

  • 2018CFD modeling of large-scale flammable cloud dispersion using FLACS89 cited
  • 2015The real-time estimation of hazardous gas dispersion by the integration of gas detectors, neural network and gas dispersion models86 cited
  • 2019Review of recent developments of quantitative structure-property relationship models on fire and explosion-related properties77 cited
  • 2018Verification and validation of Phast consequence models for accidental releases of toxic or flammable chemicals to the atmosphere56 cited
  • 2006CSB investigation of the explosions and fire at the BP texas city refinery on March 23, 200544 cited
  • 2020Modeling and analysis of flammable gas dispersion and deflagration from offshore platform blowout36 cited

Cited by

  • 2022Machine learning based quantitative consequence prediction models for toxic dispersion casualty25 cited
  • 2021Development of novel combustion risk index for flammable liquids based on unsupervised clustering algorithms17 cited

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