Domino effect in process-industry accidents – An inventory of past events and identification of some patterns

Dust explosions pose the most serious and widespread of explosion hazards in the process industry alongside vapour cloud explosions (VCE) and boiling liquid expanding vapour explosions (BLEVE). Dust explosions almost always lead to serious financial losses in terms of damage to facilities and down time. They also often cause serious injuries to personnel, and fatalities. We present the gist of the dust explosion state-of-the-art. Illustrative case studies and past accident analyses reflect the high frequency, geographic spread, and damage potential of dust explosions across the world. The sources and triggers of dust explosions, and the measures with which different factors associated with dust explosions can be quantified are reviewed alongside dust explosion mechanism. The rest of the review is focused on the ways available to prevent dust explosion, and on cushioning the impact of a dust explosion by venting when the accident does take place.

A systematic procedure for the quantitative assessment of the risk caused by domino effect was developed. Escalation vectors, defined as the physical effects responsible of possible accident propagation, were identified for the primary scenarios usually considered in the QRA procedure. Starting from the assessment of the escalation vectors, the methodology allows the identification of credible domino scenarios and the estimation of their expected severity. A simplified technique was introduced for consequence and vulnerability assessment of domino scenarios. The overall contribution of domino effect to individual risk, societal risk and to the potential life loss index was calculated by a specific procedure, taking into account all the credible combinations of secondary events that may be triggered by each primary scenario. The development of a software package allowed the application of the procedure to several case-studies. The results evidenced the relevant modifications of the risk indexes caused by domino effect and the importance of including the quantitative analysis of domino effect in QRA, in order to correctly assess and control the risk caused by escalation scenarios.