A thorough classification and discussion of approaches for modeling and managing domino effects in the process industries

Safety Science - Tập 125 - Trang 104618 - 2020
Chao Chen1, Genserik Reniers1,2,3, Nima Khakzad4
1Safety and Security Science Group, Faculty of Technology, Policy and Management, TU Delft, Delft, the Netherlands
2Faculty of Applied Economics, Antwerp Research Group on Safety and Security (ARGoSS), University Antwerp, Antwerp, Belgium
3CEDON, KULeuven, Campus Brussels, Brussels, Belgium
4School of Occupational and Public Health, Ryerson University, Toronto, Canada

Tài liệu tham khảo

Abdolhamidzadeh, 2010, A new method for assessing domino effect in chemical process industry, Hazard Mater, 182, 416, 10.1016/j.jhazmat.2010.06.049 Abdolhamidzadeh, 2011, Domino effect in process-industry accidents – an inventory of past events and identification of some patterns, J. Loss Prev. Process Ind., 24, 575, 10.1016/j.jlp.2010.06.013 Ahmadi, 2019, Consequence analysis of large-scale pool fire in oil storage terminal based on computational fluid dynamic (CFD), Process Saf. Environ. Prot., 123, 379, 10.1016/j.psep.2019.01.006 Ahmed, 2012, Explosions and structural fragments as industrial hazard: domino effect and risks, Procedia Eng., 45, 159, 10.1016/j.proeng.2012.08.137 Alessandri, 2018, Probabilistic risk analysis of process plants under seismic loading based on Monte Carlo simulations, J. Loss Prev. Process Ind., 53, 136, 10.1016/j.jlp.2017.12.013 Alileche, 2015, Thresholds for domino effects and safety distances in the process industry: a review of approaches and regulations, Reliab. Eng. Syst. Saf., 143, 74, 10.1016/j.ress.2015.04.007 Alileche, 2017, Analysis of domino effect in the process industry using the event tree method, Saf. Sci., 97, 10, 10.1016/j.ssci.2015.12.028 American Petroleum Institute (API), 2004 Anderson, C., Townsend, W., Zook, J., Cowgill, G., 1974. The effects of a fire environment on a rail tank car filled with LPG. Antonioni, 2009, Development of a framework for the risk assessment of Na-Tech accidental events, Reliab. Eng. Syst. Saf., 94, 1442, 10.1016/j.ress.2009.02.026 Antonioni, 2015, Quantitative assessment of risk due to NaTech scenarios caused by floods, Reliab. Eng. Syst. Saf., 142, 334, 10.1016/j.ress.2015.05.020 Antonioni, 2007, A methodology for the quantitative risk assessment of major accidents triggered by seismic events, J. Hazard. Mater., 147, 48, 10.1016/j.jhazmat.2006.12.043 Antonioni, 2009, Application of domino effect quantitative risk assessment to an extended industrial area, J. Loss Prev. Process Ind., 22, 614, 10.1016/j.jlp.2009.02.012 API, 2013 Apostolakis, 2005, A screening methodology for the identification and ranking of infrastructure vulnerabilities due to terrorism, Risk Anal. Int. J., 25, 361, 10.1111/j.1539-6924.2005.00595.x Argentia, 2014, Frequency evaluation for domino scenarios triggered by heat radiation exposure, Chem. Eng. Trans., 36, 373 Assael, 2010 Atkins, 1998 Baesi, 2013, Application of a multi-plant QRA: a case study investigating the risk impact of the construction of a new plant on an existing chemical plant's risk levels, J. Loss Prev. Process Ind., 26, 895, 10.1016/j.jlp.2012.11.005 Bagster, 1991, The estimation of domino incident frequencies—an approach, Process Saf. Environ. Prot., 69, 195 Baybutt, 2002, Assessing risks from threats to process plants: threat and vulnerability analysis, Process Saf. Prog., 21, 269, 10.1002/prs.680210403 Bernechea, 2014, Optimizing the design of storage facilities through the application of ISD and QRA, Process Saf. Environ. Prot., 92, 598, 10.1016/j.psep.2013.06.002 Bier, 2005, Protection of simple series and parallel systems with components of different values, Reliab. Eng. Syst. Saf., 87, 315, 10.1016/j.ress.2004.06.003 Bollinger, 1997 Bubbico, 2020, Dynamic assessment of safety barriers preventing escalation in offshore Oil&Gas, Saf. Sci., 121, 319, 10.1016/j.ssci.2019.09.011 Bubbico, 2014, Security risk assessment of process plants: the role of layout Bucelli, 2018, Assessment of safety barriers for the prevention of cascading events in oil and gas offshore installations operating in harsh environment, Ocean Eng., 158, 171, 10.1016/j.oceaneng.2018.02.046 Bucelli, 2018, Integrated risk assessment for oil and gas installations in sensitive areas, Ocean Eng., 150, 377, 10.1016/j.oceaneng.2017.12.035 Campedel, 2008, Extending the quantitative assessment of industrial risks to earthquake effects, Risk Anal., 28, 1231, 10.1111/j.1539-6924.2008.01092.x Casciano, 2019, Ranking chemical industrial clusters with respect to safety and security using analytic network process, Process Saf. Environ. Prot., 132, 200, 10.1016/j.psep.2019.10.024 CCPS, 2001 CCPS, 2011 Chen, 2019, Cost-benefit management of intentional domino effects in chemical industrial areas, Process Saf. Environ. Prot. Chen, 2019, Integrating safety and security resources to protect chemical industrial parks from man-made domino effects: a dynamic graph approach, Reliab. Eng. Syst. Saf., 191 Chen, 2018, An innovative methodology for quickly modeling the spatial-temporal evolution of domino accidents triggered by fire, J. Loss Prev. Process Ind., 54, 312, 10.1016/j.jlp.2018.04.012 Chen, 2019, Probabilistic risk analysis for ship-ship collision: state-of-the-art, Saf. Sci., 117, 108, 10.1016/j.ssci.2019.04.014 Cincotta, 2019, Resilience-based optimal firefighting to prevent domino effects in process plants, J. Loss Prev. Process Ind., 58, 82, 10.1016/j.jlp.2019.02.004 Clini, 2010, Historical analysis of accidents involving domino effect, 335 CNN, 2019. Texas district attorney files charges against chemical plant for its 4-day fire. Retrieved from: https://edition.cnn.com/2019/04/29/us/deer-park-itc-plant-fire-charges/index.html (accessed April 30, 2019). Coster, 2003, Risk assessment of antagonistic hazards, J. Loss Prev. Process Ind., 16, 545, 10.1016/j.jlp.2003.08.005 Cozzani, 2014, Quantitative assessment of domino and NaTech scenarios in complex industrial areas, J. Loss Prev. Process Ind., 28, 10, 10.1016/j.jlp.2013.07.009 Cozzani, 2006, Quantitative assessment of domino scenarios by a GIS-based software tool, J. Loss Prev. Process Ind., 19, 463, 10.1016/j.jlp.2005.11.007 Cozzani, 2010, Industrial accidents triggered by flood events: analysis of past accidents, J. Hazard. Mater., 175, 501, 10.1016/j.jhazmat.2009.10.033 Cozzani, 2005, The assessment of risk caused by domino effect in quantitative area risk analysis, J. Hazard. Mater., 127, 14, 10.1016/j.jhazmat.2005.07.003 Cozzani, 2006, Escalation thresholds in the assessment of domino accidental events, J. Hazard. Mater., 129, 1, 10.1016/j.jhazmat.2005.08.012 Cozzani, 2004, The quantitative assessment of domino effect caused by overpressure: Part II. Case studies, J. Hazard. Mater., 107, 81, 10.1016/j.jhazmat.2003.09.014 Cozzani, 2004, The quantitative assessment of domino effects caused by overpressure: Part I. Probit models, J. Hazard. Mater., 107, 67, 10.1016/j.jhazmat.2003.09.013 Cozzani, 2004, Threshold values for domino effects caused by blast wave interaction with process equipment, J. Loss Prev. Process Ind., 17, 437, 10.1016/j.jlp.2004.08.003 Cozzani, 2007, Prevention of domino effect: from active and passive strategies to inherently safer design, J. Hazard. Mater., 139, 209, 10.1016/j.jhazmat.2006.06.041 Cozzani, 2009, The development of an inherent safety approach to the prevention of domino accidents, Accid. Anal. Prev., 41, 1216, 10.1016/j.aap.2008.06.002 Cozzani, 2001, 1263 Dan, 2015, Layout optimization of LNG-liquefaction process on LNG-FPSO preventing domino effects, J. Chem. Eng. Jpn., 48, 646, 10.1252/jcej.14we322 Darbra, 2010, Domino effect in chemical accidents: main features and accident sequences, J. Hazard. Mater., 183, 565, 10.1016/j.jhazmat.2010.07.061 Dasgotra, 2018, CFD modeling of large-scale flammable cloud dispersion using FLACS, J. Loss Prev. Process Ind., 56, 531, 10.1016/j.jlp.2018.01.001 David, 2005 de Lira-Flores, 2014, A MINLP approach for layout designs based on the domino hazard index, J. Loss Prev. Process Ind., 30, 219, 10.1016/j.jlp.2013.07.007 de Lira-Flores, 2018, A MILP approach for optimal storage vessels layout based on the quantitative risk analysis methodology, Process Saf. Environ. Prot., 120, 1, 10.1016/j.psep.2018.08.028 Delvosalle, C., 1998. A methodology for the identification and evaluation of domino effects. Rep. CRC/MT/003, Belgian Ministry of Employment and Labour, Bruxelles (B). Ding, 2019, FSEM: an approach to model contribution of synergistic effect of fires for domino effects, Reliab. Eng. Syst. Saf., 189, 271, 10.1016/j.ress.2019.04.041 Directive, 2012, Directive 2012/19/EU of the European Parliament and of the Council of 4 July 2012 on waste electrical and electronic equipmentWEEE, Off. J. Eur. Union L, 197, 38 Eisenberg, N.A., Lynch, C.J., Breeding, R.J., 1975. Vulnerability model. A simulation system for assessing damage resulting from marine spills. Enviro control inc rockville md. European Commission, 1997, Council directive 96/82/EC of 9 December 1996 on the control of major-accident hazards involving dangerous substances, Off. J. Eur. Commun., 1 Evans, 2002, Database searches for qualitative research, J. Med. Lib. Assoc., 90, 290 Fabbrocino, 2005, Quantitative risk analysis of oil storage facilities in seismic areas, J. Hazard. Mater., 123, 61, 10.1016/j.jhazmat.2005.04.015 Ge, 2019, A method for fast evaluation of potential consequences of dam, Breach. Water, 11 Gexcon, 2018. Software. Retrieved from: https://www.gexcon.com/products-services-index/Software/5/en. (accessed June 6, 2019). Ghasemi, 2017, A framework for minimizing domino effect through optimum spacing of storage tanks to serve in land use planning risk assessments, Saf. Sci., 97, 20, 10.1016/j.ssci.2016.04.017 Gomez-Mares, 2008, Jet fires and the domino effect, Fire Saf. J., 43, 583, 10.1016/j.firesaf.2008.01.002 Gubinelli, 2009, Assessment of missile hazards: evaluation of the fragment number and drag factors, J. Hazard. Mater., 161, 439, 10.1016/j.jhazmat.2008.03.116 Gubinelli, 2009, Assessment of missile hazards: identification of reference fragmentation patterns, J. Hazard. Mater., 163, 1008, 10.1016/j.jhazmat.2008.07.056 Gubinelli, 2004, A simplified model for the assessment of the impact probability of fragments, J. Hazard. Mater., 116, 175, 10.1016/j.jhazmat.2004.09.002 Hauptmanns, 2001, A Monte-Carlo based procedure for treating the flight of missiles from tank explosions, Probab. Eng. Mech., 16, 307, 10.1016/S0266-8920(01)00023-6 Hauptmanns, 2001, A procedure for analyzing the flight of missiles from explosions of cylindrical vessels, J. Loss Prev. Process Ind., 14, 395, 10.1016/S0950-4230(01)00011-0 Hemmatian, 2014, The significance of domino effect in chemical accidents, J. Loss Prev. Process Ind., 29, 30, 10.1016/j.jlp.2014.01.003 Hosseinnia, 2018, An emergency response decision matrix against terrorist attacks with improvised device in chemical clusters, Int. J. Saf. Secur. Eng., 8, 187 Hosseinnia, 2018, Multi-plant emergency response for tackling major accidents in chemical industrial areas, Saf. Sci., 102, 275, 10.1016/j.ssci.2017.11.003 HSE, 1978 Janssens, 2015, A decision model to allocate protective safety barriers and mitigate domino effects, Reliab. Eng. Syst. Saf., 143, 44, 10.1016/j.ress.2015.05.022 Ji, 2018, Risk-based domino effect analysis for fire and explosion accidents considering uncertainty in processing facilities, Ind. Eng. Chem. Res., 57, 3990, 10.1021/acs.iecr.8b00103 Jia, 2017, An innovative framework for determining the damage probability of equipment exposed to fire, Fire Saf. J., 92, 177, 10.1016/j.firesaf.2017.05.015 Jiang, 2019, Assessment of tanks vulnerability and domino effect analysis in chemical storage plants, J. Loss Prev. Process Ind., 10.1016/j.jlp.2019.04.016 Jones, 2004, Application of systematic review methods to qualitative research: practical issues, J. Adv. Nurs., 48, 271, 10.1111/j.1365-2648.2004.03196.x Jujuly, 2015, LNG pool fire simulation for domino effect analysis, Reliab. Eng. Syst. Saf., 143, 19, 10.1016/j.ress.2015.02.010 Jung, 2011, New approach to optimizing the facility siting and layout for fire and explosion scenarios, Ind. Eng. Chem. Res., 50, 3928, 10.1021/ie101367g Kadri, 2013, Method for quantitative assessment of the domino effect in industrial sites, Process Saf. Environ. Prot., 91, 452, 10.1016/j.psep.2012.10.010 Kamil, 2019, Dynamic domino effect risk assessment using Petri-nets, Process Saf. Environ. Prot., 124, 308, 10.1016/j.psep.2019.02.019 Khakzad, 2015, Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures, Reliab. Eng. Syst. Saf., 138, 263, 10.1016/j.ress.2015.02.007 Khakzad, 2018, A graph theoretic approach to optimal firefighting in oil terminals, Energies, 11 Khakzad, 2018, Impact of wildfires on Canada's oil sands facilities, Nat. Hazards Earth Syst. Sci., 18, 3153, 10.5194/nhess-18-3153-2018 Khakzad, 2018, Reducing the attractiveness of chemical plants to terrorist attacks: dehorning rhinos, Process Saf. Prog., 37, 150, 10.1002/prs.11907 Khakzad, 2018, Which fire to extinguish first? A risk-informed approach to emergency response in oil terminals, Risk Anal., 38, 1444, 10.1111/risa.12946 Khakzad, 2019, Modeling wildfire spread in wildland-industrial interfaces using dynamic Bayesian network, Reliab. Eng. Syst. Saf., 189, 165, 10.1016/j.ress.2019.04.006 Khakzad, 2018, How to address model uncertainty in the escalation of domino effects?, J. Loss Prev. Process Ind., 54, 49, 10.1016/j.jlp.2018.03.001 Khakzad, 2018, Quantitative assessment of wildfire risk in oil facilities, J. Environ. Manage., 223, 433, 10.1016/j.jenvman.2018.06.062 Khakzad, 2011, Safety analysis in process facilities: comparison of fault tree and Bayesian network approaches, Reliab. Eng. Syst. Saf., 96, 925, 10.1016/j.ress.2011.03.012 Khakzad, 2013, Domino effect analysis using Bayesian networks, Risk Anal., 33, 292, 10.1111/j.1539-6924.2012.01854.x Khakzad, 2014, Risk management of domino effects considering dynamic consequence analysis, Risk Anal., 34, 1128, 10.1111/risa.12158 Khakzad, 2018, Cost-effective fire protection of chemical plants against domino effects, Reliab. Eng. Syst. Saf., 169, 412, 10.1016/j.ress.2017.09.007 Khakzad, 2017, Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects, Reliab. Eng. Syst. Saf., 167, 232, 10.1016/j.ress.2017.06.004 Khakzad, 2017, Application of graph theory to cost-effective fire protection of chemical plants during domino effects, Risk Anal., 37, 1652, 10.1111/risa.12712 Khakzad, 2015, Risk-based design of process plants with regard to domino effects and land use planning, J. Hazard. Mater., 299, 289, 10.1016/j.jhazmat.2015.06.020 Khakzad, 2015, Using graph theory to analyze the vulnerability of process plants in the context of cascading effects, Reliab. Eng. Syst. Saf., 143, 63, 10.1016/j.ress.2015.04.015 Khakzad, 2017, Cost-effective allocation of safety measures in chemical plants w.r.t land-use planning, Saf. Sci., 97, 2, 10.1016/j.ssci.2015.10.010 Khakzad, 2019, Low-capacity utilization of process plants: a cost-robust approach to tackle man-made domino effects, Reliab. Eng. Syst. Saf., 191 Khakzad, 2016, Vulnerability analysis of process plants subject to domino effects, Reliab. Eng. Syst. Saf., 154, 127, 10.1016/j.ress.2016.06.004 Khakzad, N., Reniers, G., Landucci, G., 2017c. Application of Bayesian network to safety assessment of chemical plants during fire-induced domino effects, 26th Conference on European Safety and Reliability. ESREL 2016, Glasgow, UK, pp. 786–792. Khakzad, 2018, Vulnerability of industrial plants to flood-induced natechs: a Bayesian network approach, Reliab. Eng. Syst. Saf., 169, 403, 10.1016/j.ress.2017.09.016 Khan, 1996, Simulation of accidents in a chemical industry using the software package MAXCRED, Indian J. Chem. Technol., 3, 338 Khan, 2015, Safety challenges in harsh environments: lessons learned, Process Saf. Prog., 34, 191, 10.1002/prs.11704 Khan, 2015, Methods and models in process safety and risk management: past, present and future, Process Saf. Environ. Prot., 98, 116, 10.1016/j.psep.2015.07.005 Khan, 1998, Models for domino effect analysis in chemical process industries, Process Saf. Prog., 17, 107, 10.1002/prs.680170207 Khan, 1999, Major accidents in process industries and an analysis of causes and consequences, J. Loss Prev. Process Ind., 12, 361, 10.1016/S0950-4230(98)00062-X Khan, 2001, An assessment of the likelihood of occurrence, and the damage potential of domino effect (chain of accidents) in a typical cluster of industries, J. Loss Prev. Process Ind., 14, 283, 10.1016/S0950-4230(00)00048-6 Khan, 1998, DOMIFFECT (DOMIno eFFECT): user-friendly software for domino effect analysis, Environ. Modell. Softw., 13, 163, 10.1016/S1364-8152(98)00018-8 Khan, 2000, Studies on the probabilities and likely impacts of chains of accident (domino effect) in a fertilizer industry, Process Saf. Prog., 19, 40, 10.1002/prs.680190110 Khan, 2003, How to make inherent safety practice a reality, Can. J. Chem. Eng., 81, 2, 10.1002/cjce.5450810101 Khan, 2001, Rapid risk assessment of a fertilizer industry using recently developed computer-automated tool TORAP, J. Loss Prev. Process Ind., 14, 413, 10.1016/S0950-4230(00)00055-3 Khan, 2001, Risk analysis of a petrochemical industry using ORA (Optimal Risk Analysis) procedure, Process Saf. Prog., 20, 95, 10.1002/prs.680200207 Khan, 1998, Accident simulation as a tool for assessing and controlling environmental risks in chemical process industries: a case study, Korean J. Chem. Eng., 15, 124, 10.1007/BF02707064 Kletz, 2003, Inherently safer design—its scope and future, Process Saf. Environ. Prot., 81, 401, 10.1205/095758203770866566 Krausmann, 2011, Industrial accidents triggered by natural hazards: an emerging risk issue, Nat. Hazards Earth Syst. Sci., 11, 921, 10.5194/nhess-11-921-2011 Krausmann, 2011, Industrial accidents triggered by earthquakes, floods and lightning: lessons learned from a database analysis, Nat. Hazards, 59, 285, 10.1007/s11069-011-9754-3 Landucci, 2012, Release of hazardous substances in flood events: damage model for atmospheric storage tanks, Reliab. Eng. Syst. Saf., 106, 200, 10.1016/j.ress.2012.05.010 Landucci, 2016, Domino effect frequency assessment: the role of safety barriers, J. Loss Prev. Process Ind., 44, 706, 10.1016/j.jlp.2016.03.006 Landucci, 2015, Quantitative assessment of safety barrier performance in the prevention of domino scenarios triggered by fire, Reliab. Eng. Syst. Saf., 143, 30, 10.1016/j.ress.2015.03.023 Landucci, 2017, A methodology for the analysis of domino and cascading events in Oil & Gas facilities operating in harsh environments, Saf. Sci., 95, 182, 10.1016/j.ssci.2016.12.019 Landucci, 2016, Modeling heat transfer and pressure build-up in LPG vessels exposed to fires, Int. J. Therm. Sci., 104, 228, 10.1016/j.ijthermalsci.2016.01.002 Landucci, 2009, The assessment of the damage probability of storage tanks in domino events triggered by fire, Accid. Anal. Prev., 41, 1206, 10.1016/j.aap.2008.05.006 Landucci, 2009, Modeling the performance of coated LPG tanks engulfed in fires, J. Hazard. Mater., 172, 447, 10.1016/j.jhazmat.2009.07.029 Landucci, 2017, Risk assessment of mitigated domino scenarios in process facilities, Reliab. Eng. Syst. Saf., 160, 37, 10.1016/j.ress.2016.11.023 Landucci, 2014, Release of hazardous substances in flood events: damage model for horizontal cylindrical vessels, Reliab. Eng. Syst. Saf., 132, 125, 10.1016/j.ress.2014.07.016 Landucci, 2015, Vulnerability of industrial facilities to attacks with improvised explosive devices aimed at triggering domino scenarios, Reliab. Eng. Syst. Saf., 143, 53, 10.1016/j.ress.2015.03.004 Landucci, 2008, Inherent safety key performance indicators for hydrogen storage systems, J. Hazard. Mater., 159, 554, 10.1016/j.jhazmat.2008.02.080 Latifi, 2017, Process plant layout optimization with uncertainty and considering risk, Comput. Chem. Eng., 106, 224, 10.1016/j.compchemeng.2017.05.022 Lee, 2006, A new approach for allocating explosive facilities in order to minimize the domino effect using NLP, J. Chem. Eng. Jpn., 39, 731, 10.1252/jcej.39.731 Lee, 2005, Optimization for allocating the explosive facilities in order to minimize ptimiz the domino effect using nonlinear programming, Korean J. Chem. Eng., 22, 649, 10.1007/BF02705777 Lees, 2012 Li, Wang, Ge, Wei, Li, 2019. Risk Analysis of Earth-Rock Dam Breach Based on Dynamic Bayesian Network. Water 11. Li, 2017, A bibliometric analysis of peer-reviewed publications on domino effects in the process industry, J. Loss Prev. Process Ind., 49, 103, 10.1016/j.jlp.2016.06.003 Lisi, 2014, Domino effects due to the projection of fragments: estimation of the impact probability using a Monte Carlo simulation, Chem. Eng. Trans., 36, 361 Lisi, 2015, Estimation of the impact probability in domino effects due to the projection of fragments, Process Saf. Environ. Prot., 93, 99, 10.1016/j.psep.2014.05.003 López-Molina, 2013, An approach for domino effect reduction based on optimal layouts, J. Loss Prev. Process Ind., 26, 887, 10.1016/j.jlp.2012.11.001 Misuri, 2019, Lessons learnt from the impact of hurricane Harvey on the chemical and process industry, Reliab. Eng. Syst. Saf., 190 Misuri, 2020, Assessment of safety barrier performance in Natech scenarios, Reliab. Eng. Syst. Saf., 193 Moodie, 1988, Experiments and modelling:-an overview with particular reference to fire engulfment, J. Hazard. Mater., 20, 149, 10.1016/0304-3894(88)87011-0 Moore, 2007, Development of a security vulnerability assessment process for the RAMCAP chemical sector, J. Hazard. Mater., 142, 689, 10.1016/j.jhazmat.2006.06.133 Mukhim, 2017, Domino effect in chemical process industries triggered by overpressure—formulation of equipment-specific probits, Process Saf. Environ. Prot., 106, 263, 10.1016/j.psep.2017.01.004 Murata, 1989, Petri nets: properties, analysis and applications, Proc. IEEE, 77, 541, 10.1109/5.24143 Necci, 2016, Quantitative assessment of risk due to major accidents triggered by lightning, Reliab. Eng. Syst. Saf., 154, 60, 10.1016/j.ress.2016.05.009 Necci, 2013, A model for process equipment damage probability assessment due to lightning, Reliab. Eng. Syst. Saf., 115, 91, 10.1016/j.ress.2013.02.018 Necci, 2014, Accident scenarios triggered by lightning strike on atmospheric storage tanks, Reliab. Eng. Syst. Saf., 127, 30, 10.1016/j.ress.2014.02.005 Necci, 2015, Assessment of domino effect: state of the art and research Needs, Reliab. Eng. Syst. Saf., 143, 3, 10.1016/j.ress.2015.05.017 Nomen, 2014, QRA including domino effect as a tool for engineering design, Procedia Eng., 84, 23, 10.1016/j.proeng.2014.10.406 Papadakis, 1997 Pavlova, 2011, A sequential-move game for enhancing safety and security cooperation within chemical clusters, J. Hazard. Mater., 186, 401, 10.1016/j.jhazmat.2010.11.013 Pietersen, 1988, Analysis of the LPG-disaster in Mexico City, J. Hazard. Mater., 20, 85, 10.1016/0304-3894(88)87008-0 Pula, 2007, A model for estimating the probability of missile impact: missiles originating from bursting horizontal cylindrical vessels, Process Saf. Prog., 26, 129, 10.1002/prs.10178 Qin, 2020, An overview of the impact of Hurricane Harvey on chemical and process facilities in Texas, Int. J. Disaster Risk Reduct., 45 Rad, 2014, FREEDOM II: an improved methodology to assess domino effect frequency using simulation techniques, Process Saf. Environ. Prot., 92, 714, 10.1016/j.psep.2013.12.002 Ramírez-Camacho, 2019, Analysis of crater formation in buried NG pipelines: a survey based on past accidents and evaluation of domino effect, J. Loss Prev. Process Ind., 58, 124, 10.1016/j.jlp.2019.01.011 Ramirez-Camacho, 2015, Analysis of domino effect in pipelines, J. Hazard. Mater., 298, 210, 10.1016/j.jhazmat.2015.05.033 Reniers, 2009, Terrorism security in the chemical industry: results of a qualitative investigation, Secur. J., 24, 69, 10.1057/sj.2009.10 Reniers, 2010, An external domino effects investment approach to improve cross-plant safety within chemical clusters, J. Hazard. Mater., 177, 167, 10.1016/j.jhazmat.2009.12.013 Reniers, 2013 Reniers, 2012, A game-theory based Multi-plant Collaboration Model (MCM) for cross-plant prevention in a chemical cluster, J. Hazard. Mater., 209–210, 164, 10.1016/j.jhazmat.2012.01.004 Reniers, 2008, Managing domino effect-related security of industrial areas, J. Loss Prev. Process Ind., 21, 336, 10.1016/j.jlp.2007.06.007 Reniers, 2009, Domino effects within a chemical cluster: a game-theoretical modeling approach by using Nash-equilibrium, J. Hazard. Mater., 167, 289, 10.1016/j.jhazmat.2008.12.113 Reniers, G., Dullaert, W., Soudan, K., 2004. A domino effect evaluation model. Reniers, 2018, The impact of nature on chemical industrial facilities: dealing with challenges for creating resilient chemical industrial parks, J. Loss Prev. Process Ind., 10.1016/j.jlp.2018.09.010 Reniers, 2010, A game-theoretical approach for reciprocal security-related prevention investment decisions, Reliab. Eng. Syst. Saf., 95, 1, 10.1016/j.ress.2009.07.001 Reniers, 2016 Reniers, 2008, Preventing intentional disasters by investigating the security of chemical industrial areas, Disaster Adv., 1, 14 Reniers, 2014, Preparing for major terrorist attacks against chemical clusters: intelligently planning protection measures w.r.t. domino effects, Process Saf. Environ. Prot., 92, 583, 10.1016/j.psep.2013.04.002 Reniers, 2007, DomPrevPlanning©: user-friendly software for planning domino effects prevention, Saf. Sci., 45, 1060, 10.1016/j.ssci.2006.10.004 Reniers, 2008, Knock-on accident prevention in a chemical cluster, Expert Syst. Appl., 34, 42, 10.1016/j.eswa.2006.08.033 Reniers, 2005, Developing an external domino accident prevention framework: Hazwim, J. Loss Prev. Process Ind., 18, 127, 10.1016/j.jlp.2005.03.002 Reniers, 2005, The use of current risk analysis tools evaluated towards preventing external domino accidents, J. Loss Prev. Process Ind., 18, 119, 10.1016/j.jlp.2005.03.001 Reniers, 2010, Transportation Risk ANalysis tool for hazardous Substances (TRANS) – a user-friendly, semi-quantitative multi-mode hazmat transport route safety risk estimation methodology for Flanders, Transp. Res. Part D: Transp. Environ., 15, 489, 10.1016/j.trd.2010.07.001 Reniers, 2014, Resilience of chemical industrial areas through attenuation-based security, Reliab. Eng. Syst. Saf., 131, 94, 10.1016/j.ress.2014.05.005 Rum, 2018, Coupling of integral methods and CFD for modeling complex industrial accidents, J. Loss Prev. Process Ind., 53, 115, 10.1016/j.jlp.2017.09.006 Safety, 2000 Salzano, 2003 Salzano, 2005, The analysis of domino accidents triggered by vapor cloud explosions, Reliab. Eng. Syst. Saf., 90, 271, 10.1016/j.ress.2004.11.012 Salzano, 2006, A fuzzy set analysis to estimate loss intensity following blast wave interaction with process equipment, J. Loss Prev. Process Ind., 19, 343, 10.1016/j.jlp.2005.08.002 Salzano, 2014, Domino effects related to home-made explosives, Chem. Eng. Trans., 36, 349 Scarponi, 2018, Experimental and numerical study of the behavior of LPG tanks exposed to wildland fires, Process Saf. Environ. Prot., 114, 251, 10.1016/j.psep.2017.12.013 Shaluf, 2003, Fire and explosion at mutual major hazard installations: review of a case history, J. Loss Prev. Process Ind., 16, 149, 10.1016/S0950-4230(02)00094-3 Silva, 2016, Underground parallel pipelines domino effect: an analysis based on pipeline crater models and historical accidents, J. Loss Prev. Process Ind., 43, 315, 10.1016/j.jlp.2016.05.031 So, 2011, Optimal layout of additional facilities for minimization of domino effects based on worst-case scenarios, Korean J. Chem. Eng., 28, 656, 10.1007/s11814-010-0445-7 Srivastava, 2010, New methodologies for security risk assessment of oil and gas industry, Process Saf. Environ. Prot., 88, 407, 10.1016/j.psep.2010.06.004 Sun, 2013, Influence of the protective layer of polyvinylchloride resin on failure of LPG vessel caused by heat radiation, Procedia Eng., 62, 564, 10.1016/j.proeng.2013.08.101 Sun, 2013, Study on the rationality and validity of probit models of domino effect to chemical process equipment caused by overpressure, J. Phys. Conf. Ser., 423, 10.1088/1742-6596/423/1/012002 Sun, 2016, Ballistic experiments on the mechanism of protective layer against domino effect caused by projectiles, J. Loss Prev. Process Ind., 40, 17, 10.1016/j.jlp.2015.11.020 Sun, 2012, Parametric approach of the domino effect for structural fragments, J. Loss Prev. Process Ind., 25, 114, 10.1016/j.jlp.2011.06.029 Sun, 2016, Investigation of multiple domino scenarios caused by fragments, J. Loss Prev. Process Ind., 40, 591, 10.1016/j.jlp.2016.01.023 Sun, 2017, Investigation on the approach of intercepting fragments generated by vessel explosion using barrier net, J. Loss Prev. Process Ind., 49, 989, 10.1016/j.jlp.2016.10.012 Swuste, 2019, Domino effects in chemical factories and clusters: an historical perspective and discussion, Process Saf. Environ. Prot., 10.1016/j.psep.2019.01.015 Tsai, 2018, Integrated self-assessment module for fire rescue safety in a chemical plant – a case study, J. Loss Prev. Process Ind., 51, 137, 10.1016/j.jlp.2017.12.011 Tugnoli, 2012, Mitigation of fire damage and escalation by fireproofing: a risk-based strategy, Reliab. Eng. Syst. Saf., 105, 25, 10.1016/j.ress.2011.11.002 Tugnoli, 2013, Reducing the consequences of accidental fires in oil & gas facilities: a risk-based procedure for identification of the fireproofing zones, Chem. Eng. Trans., 32, 103 Tugnoli, 2014, Assessment of fragment projection hazard: probability distributions for the initial direction of fragments, J. Hazard. Mater., 279, 418, 10.1016/j.jhazmat.2014.07.034 Tugnoli, 2008, Safety assessment in plant layout design using indexing approach: implementing inherent safety perspective. Part 1 - guideword applicability and method description, J. Hazard. Mater., 160, 100, 10.1016/j.jhazmat.2008.02.089 Tugnoli, 2008, Safety assessment in plant layout design using indexing approach: implementing inherent safety perspective. Part 2-Domino Hazard Index and case study, J. Hazard. Mater., 160, 110, 10.1016/j.jhazmat.2008.02.091 Tugnoli, 2014, Assessment of the hazard due to fragment projection: a case study, J. Loss Prev. Process Ind., 28, 36, 10.1016/j.jlp.2013.08.015 U.S. Department of Homeland Security, 2013. Critical Infrastructure Sectors, Washington. Uijt de Haag, 1999 UPI, 2019. Death toll rises to 78 in Chinese chemical plant explosion. Retrieved from: https://www.upi.com/Top_News/World-News/2019/03/26/Death-toll-rises-to-78-in-Chinese-chemical-plant-explosion/1601553571988/ (accessed April 30, 2019). Van Den Bosh, 1997 van der Voort, 2007, A quantitative risk assessment tool for the external safety of industrial plants with a dust explosion hazard, J. Loss Prev. Process Ind., 20, 375, 10.1016/j.jlp.2007.04.024 Wang, 2018, Work safety in China’s Thirteenth Five-Year plan period (2016–2020): current status, new challenges and future tasks, Saf. Sci., 104, 164, 10.1016/j.ssci.2018.01.012 Wang, 2019, A brief report and analysis on the July 19, 2019, explosion in the Yima gasification plant in Sanmenxia, China. Process Saf. Prog. Whiteley, 2004, Initial perspectives on process threat management, J. Hazard. Mater., 115, 163, 10.1016/j.jhazmat.2004.05.011 Wu, 2019, Improved set pair analysis and its application to environmental impact evaluation of dam break, Water, 11 Xue, 2019, Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships’ maneuvering decisions using grey and fuzzy theories, Saf. Sci., 120, 323, 10.1016/j.ssci.2019.07.019 Yang, 2018, The probability prediction method of domino effect triggered by lightning in chemical tank farm, Process Saf. Environ. Prot., 116, 106, 10.1016/j.psep.2018.01.019 Yang, 2019, Vulnerability assessment of atmospheric storage tanks to floods based on logistic regression, Reliab. Eng. Syst. Saf. Yuan, 2016, Domino effect analysis of dust explosions using Bayesian networks, Process Saf. Environ. Prot., 100, 108, 10.1016/j.psep.2016.01.005 Zeng, 2019, Developing an advanced dynamic risk analysis method for fire-related domino effects, Process Saf. Environ. Prot. Zhang, 2018, DAMS: a model to assess domino effects by using agent-based modeling and simulation, Risk Anal., 38, 1585, 10.1111/risa.12955 Zhang, 2016, A game-theoretical model to improve process plant protection from terrorist attacks, Risk Anal., 36, 2285, 10.1111/risa.12569 Zhang, 2008, An improved probit method for assessment of domino effect to chemical process equipment caused by overpressure, J. Hazard. Mater., 158, 280, 10.1016/j.jhazmat.2008.01.076 Zhang, 2019, Propagation probability of domino effect based on analysis of accident chain in storage tank area, J. Loss Prev. Process Ind., 62 Zhang, 2013, Mechanism analysis and risk assessment of escalation scenario in chemical industry zones, Process Saf. Environ. Prot., 91, 79, 10.1016/j.psep.2012.02.003 Zhang, 2009, The analysis of domino effect impact probability triggered by fragments, Saf. Sci., 47, 1026, 10.1016/j.ssci.2008.11.005 Zhou, 2016, Petri-net based simulation analysis for emergency response to multiple simultaneous large-scale fires, J. Loss Prev. Process Ind., 40, 554, 10.1016/j.jlp.2016.01.026 Zhou, 2017, Analysis of emergency response actions for preventing fire-induced domino effects based on an approach of reversed fuzzy Petri-net, J. Loss Prev. Process Ind., 47, 169, 10.1016/j.jlp.2017.03.011 Zhou, 2017, Petri-net based cascading effect analysis of vapor cloud explosions, J. Loss Prev. Process Ind., 48, 118, 10.1016/j.jlp.2017.04.017 Zhou, 2018, A matrix-based modeling and analysis approach for fire-induced domino effects, Process Saf. Environ. Prot., 116, 347, 10.1016/j.psep.2018.02.014 Zhou, 2018, Modeling and analysis of vapour cloud explosions knock-on events by using a Petri-net approach, Saf. Sci., 108, 188, 10.1016/j.ssci.2018.04.019 Zhou, 2018, Petri-net based evaluation of emergency response actions for preventing domino effects triggered by fire, J. Loss Prev. Process Ind., 51, 94, 10.1016/j.jlp.2017.12.001 Zhou, 2016, Application of event sequence diagram to evaluate emergency response actions during fire-induced domino effects, Reliab. Eng. Syst. Saf., 150, 202, 10.1016/j.ress.2016.02.005