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An “atypical” incident scenario is a scenario deviating from normal expectations and, thus, not deemed credible by common processes of risk assessment. Past experience shows that non identified incident scenarios as such represent a latent risk for industry and society and sometimes their occurrence can lead to consequences of unexpected extent. An evident example of atypical accident is the case at Buncefield, where on December 11th 2005 an overflowing petroleum storage tank generated an extended flammable vapour cloud and gave rise to a large explosion, whose magnitude would not have been foreseen by standard assessment techniques. Before this event, a classical risk assessment of the Buncefield site considered a large pool fire as worst incident scenario. In hindsight, it can be stated that the assessment was inadequate. A detailed analysis of this and other cases in literature has shed some light on the great complexity of their causal factors, demonstrating that an atypical major accident is not the consequence of a single uncommon event, but rather the result of a series of failures at different levels of risk management. Thus, it has been a big challenge to foresee combinations of such failures and corresponding unidentified incident scenarios. Two complementary approaches to deal with this challenge are: - improved identification of atypical scenarios, to reduce the occurrence of unforeseen events - improved early detection, to reduce the possibility of remaining unforeseen events leading to an accident For this reason the Resilience based Early Warning Indicator (REWI) method has been considered in this contribution. In fact, the concept of resilience refers to the capability of recognizing, adapting to, and coping with the unexpected and one of its key characteristics is the interaction and interchange between different (organizational) system layers, levels, and focal points. The REWI method allows to establish a set of early warning indicators on the basis of issues of contributing success factors (CSFs) being attributes of resilience. The main aim of this work will be to show the preliminary results of the application of this method to the site at Buncefield. A candidate set of resilience based early warning indicators will then be adapted taking into account characteristics of the oil depot. Then, the accident causes identified in the analysis will be related to the indicators, in order to understand the relevance of these resilience based indicators as early warnings of the atypical incident scenario occurrence and to which extent this major accident could have been prevented. |
