Quantitative Assessment of Risk Caused by Domino Accidents

Domino Effects in the Process Industries: Modelling, Prevention and Managing

Volumn , Issue , 2013, Pages 208-228

  Cozzani, Valerio ^a   Antonioni, Giacomo ^a   Khakzad, Nima ^b   Khan, Faisal ^b   Taveau, Jerome ^c   Reniers, Genserik ^d  

^a UNIVERSITY OF BOLOGNA   (Italy)

^b MEMORIAL UNIVERSITY OF NEWFOUNDLAND   (Canada)

^c Fike Corporation   (United States)

^d UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Domino effect; Industrial risk; Major accident hazard; Quantitative risk assessment

Indexed keywords

ACCIDENTS; MONTE CARLO METHODS; RISK PERCEPTION;

BAYESIAN TECHNIQUES; DOMINO ACCIDENTS; DOMINO EFFECTS; INDUSTRIAL RISKS; MAJOR-ACCIDENT HAZARDS; QUANTITATIVE APPROACH; QUANTITATIVE ASSESSMENTS; QUANTITATIVE RISK ASSESSMENT;

RISK ASSESSMENT;

EID: 84902422539     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-0-444-54323-3.00010-5     Document Type: Chapter

References (39)

1. Abdolhamidzadeh B., Abbasi T., Rashtchian D., Abbasi S.A. A new method for assessing domino effect in chemical process industry. Journal of Hazardous Materials 2010, 182:416-426.
2. Antonioni G., Spadoni G., Cozzani V. Application of domino effect quantitative risk assessment to an extended industrial area. Journal of Loss Prevention in the Process Industries 2009, 22:614-624.
3. Antonioni G., Cozzani V., Gubinelli G., Spadoni G., Zanelli S. The estimation of vulnerability in domino accidental events. Proc. Eur. Safety and Reliability Conf 2004, 3212-3217. Springer, London, UK.
4. Bagster D.F., Pitblado R.M. The estimation of domino incident frequencies: an approach. Process Safety Environmental Protection 1991, 69:196.
5. Bobbio A., Portinale L., Minichino M., Ciancamerla E. Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Journal of Reliability Engineering and System Safety 2001, 71:249-260.
6. Carter D.A., Hirst I.L. "Worst case" methodology for the initial assessment of societal risk from proposed major accident installations. Journal of Hazardous Materials 2000, 71:117-128.
7. CCPS, Center for Chemical Process Safety Guidelines for Chemical Process Quantitative Risk Analysis 2000, American Institute of Chemical Engineers, New York, USA.
8. CCPS (Center for Chemical Process Safety) Guidelines for Hazard Evaluation Procedures 2008, AIChE, New York. third ed.
9. Contini S., Boy S., Atkinson M., Labath N., Banca M., Nordvik J.P. Domino effect evaluation of major industrial installations: a computer aided methodological approach. Proc. European Seminar on Domino Effects 1996, 21-34. Leuven (B).
10. Cozzani V., Gubinelli G., Antonioni G., Spadoni G., Zanelli S. The assessment of risk caused by domino effect in quantitative area risk analysis. Journal of Hazardous Materials 2005, 127:14-30.
11. Cozzani V., Antonioni G., Spadoni G. Quantitative assessment of domino scenarios by a GIS-based software tool. Journal of Loss Prevention in the Process Industries 2006, 19:463.
12. Cozzani V., Tugnoli A., Salzano E. The development of an inherent safety approach to the prevention of domino accidents. Accident Analysis and Prevention 2009, 41:1216-1227.
13. COVO Risk Analysis of Six Potentially Hazardous Industrial Objects in the Rijnmond Area, A Pilot Study. A Report to the Rijnmond Public Authority. Central 1982, Environmental Control Agency, Schiedam, NL.
14. 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.
15. Delvosalle C., Fievez C., Pipart A., Debray B. ARAMIS project: a comprehensive methodology for the identification of reference accident scenarios in process industries. Journal of Hazardous Materials 2006, 130:200-219.
16. Directive 82/501/EEC, Council Directive 82/501/EEC of 24 June 1982 on the major accident hazards of certain industrial activities. Official Journal of the European Communities L230/25, Brussels, 5.8.82.
17. Egidi D., Foraboschi F.P., Spadoni G., Amendola A. The ARIPAR project: an analysis of the major accident risks connected with industrial and transportation activities in the Ravenna area. Journal of Reliability Engineering and System Safety 1995, 49:75.
18. Finney D.J. Probit Analysis 1971, Cambridge University Press, Cambridge, UK.
19. Gledhill J., Lines I. Development of Methods to Assess the Significance of Domino Effects from Major Hazard Sites, CR Report 183. Health and Safety Executive 1998, London, UK.
20. HSE, Health and Safety Executive Canvey: An Investigation of Potential Hazards from Operations in the Canvey Island/Thurrock Area 1978, HM Stationary Office, London, UK.
21. HSE, Health and Safety Executive Canvey: A Second Report. A Review of the Potential Hazards from Operations in the Canvey Island/Thurrock Area Three Years after Publication of the Canvey Report 1981, HM Stationery Office, London, UK.
22. Jensen F.V., Nielsen T.D. Bayesian Networks and Decision Graphs 2007, Springer, New York, USA. second ed.
23. Khakzad N., Khan F., Amyotte P. Safety analysis in process facilities: comparison of fault tree and Bayesian network approaches. Journal of Reliability Engineering and System Safety 2011, 96:925-932.
24. Khakzad N., Khan F.I., Amyotte P., Cozzani V. Domino effect analysis using Bayesian networks. Risk Analysis 2013, 33:292-303.
25. Khan F.I., Abbasi S.A. Models for domino effect analysis in chemical process industries. Process Safety Progress 1998, 17:107.
26. Khan F.I., Abbasi S.A. DOMIFFECT (DOMIno eFFECT): user-friendly software for domino effect analysis. Environmental Modelling and Software 1998, 13:163-177.
27. Latha P., Gautam G., Raghavan K.V. Strategies for the quantification of thermally initiated cascade effects. Journal of Loss Prevention in the Process Industries 1992, 5:18.
28. Leonelli P., Bonvicini S., Spadoni G. New detailed numerical procedures for calculating risk measures in hazardous materials transportation. Journal of Loss Prevention in the Process Industries 1999, 12:507-515.
29. Mannan S. Lees' Loss Prevention in the Process Industries 2005, Elsevier, Oxford, UK. third ed.
30. Morris M., Miles A., Copper J. Quantification of escalation effects in offshore quantitative risk assessment. Journal of Loss Prevention in the Process Industries 1994, 7:337.
31. Paltrinieri N., Dechy N., Salzano E., Wardman M., Cozzani V. Lessons learned from Toulouse and Buncefield disasters: from risk analysis failures to the identification of atypical scenarios through a better knowledge management. Risk Analysis 2012, 32:1404-1419.
32. Pettitt G.N., Schumacher R.R., Seeley L.A. Evaluating the probability of major hazardous incidents as a result of escalation events. Journal of Loss Prevention in the Process Industries 1993, 6:37.
33. RIVM Instrument Domino Effecten 2003, Rijksinstituut voor Volksgezondheid en Milieu, Bilthoven, NL.
34. Spadoni G., Egidi D., Contini S. Through ARIPAR-GIS the quantified area risk analysis supports land-use planning activities. Journal of Hazardous Materials 2000, 71:423-437.
35. Tugnoli A., Gyenes Z., Van Wijk L., Christou M., Spadoni G., Cozzani V. Reference criteria for the identification of accident scenarios in the framework of land use planning. Journal of Loss Prevention in the Process Industries 2013, 26:614-627.
36. Uijt de Haag P.A.M., Ale B.J.M. Guidelines for Quantitative Risk Assessment (Purple Book) 1999, Committee for the Prevention of Disasters, The Hague, NL.
37. Van Den Bosh C.J.H., Merx W.P.M., Jansen C.M.A., De Weger D., Reuzel P.G.J., Leeuwen D.V., Blom-Bruggerman J.M. Methods for the Calculation of Possible Damage (Green Book) 1989, Committee for the Prevention of Disasters, The Hague, NL.
38. Van Den Bosh C.J.H., Weterings R.A.P.M. Methods for the Calculation of Physical Effects (Yellow Book) 1997, Committee for the Prevention of Disasters, The Hague, NL.
39. Zhang X.M., Chen G.H. Modeling and algorithm of domino effect in chemical industrial parks using discrete isolated island method. Safety Science 2011, 49:463-467.