Abstract In the context of risk assessment and loss prevention in chemical process industries, the term domino effect denotes ‘chain of accidents’, or situations when a fire/explosion/missile/toxic load generated by an accident in one unit in an industry causes secondary and higher order accidents in other units. Most of the past risk assessment studies deal with accident in a single industry, more so in one of the units of an industry. But, often, accident in one unit can cause a secondary accident in a nearby unit, which in turn may trigger a tertiary accident, and so on. The probability of occurrence and adverse impacts of such ‘domino’ or ‘cascading’ effects are increasing due to increasing congestion in industrial complexes and increasing density of human population around such complexes. The multi-accident catastrophe which occurred in a refinery at Vishakhapatnam, India, on 14 September 1997, claiming 60 lives and causing loss of property worth over Rs 600 million, is the most recent example of the damage potential of domino effect [Lees F.P. Loss prevention in process industries, 2nd ed. Butterworths, 1-3, London; Khan, F.I., & Abbasi, S.A. (1999a). Major accidents in process industries and an analysis of their causes and consequences. Journal of Loss Prevention in Process Industries, 12, 361–378; Khan, F.I., & Abbasi, S.A. (1999b). The worst chemical industry accident of 1990's–what happened and what might have been: A quantitative study. Process Safety Progress, 18, 135–145]. Recently, we have proposed a systematic methodology called ‘domino effect analysis’ (DEA). A computer automated tool DOMIFFECT has also been developed by us based on DEA [Khan, F.I., & Abbasi, S.A. (1998a). Models for domino effect analysis in chemical process industries. Process Safety Progress — AIChE, 17 (2), 107–113; Khan, F.I., & Abbasi, S.A. (1998b). DOMIFFECT (DOMIno eFFECT): a new software for domino effect analysis in chemical process industries. Environmental Modelling and Software, 13, 163–177.]. The methodology is based on deterministic models used in conjunction with probabilistic analysis. This paper illustrates the application of DEA and DOMIFFECT to an industrial complex. Out of 16 credible accident scenarios envisaged in four closely situated industries namely Madras Fertilisers Limited (MFL), SPIC–Heavy Chemical Division (SPIC–HCD). Manali Petrochemical Limited (MPL), and Tamilnadu Petroproducts Limited (TPL), ten scenarios forecast domino effect. Further analysis reveals that accidents in the ammonia synthesis unit, secondary reformer, and urea reactor of MFL may cause domino effect. Similarly, accidents in the storage units of propylene oxide, ethylene oxide and mono propylene glycol at MPL, hydrogen storage units at SPIC–HCD, and the propylene oxide and fuel oil storage units of TPL are likely to cause a domino effect. The consequences of all these credible accidents have also been forecast. The paper makes a strong case for making DEA an integral part of all risk assessment initiatives.
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