Abstract
The paper contains a case study covering forecasting mechanical effects of an explosion which can be generated during a road accident. It illustrates a practical application of the simulation‐based procedure developed for such forecasting in the first part of the paper. The case study reveals the amount and character of the knowledge necessary to carry out this forecasting. Its final result is a probabilistic model describing likelihood of occurrence of accidental explosion as well as characteristics of the incident blast wave generated by this explosion. The accident simulation is based on the classical Bayesian approach to risk assessment. The case study described in the paper shows how to formulate the initial knowledge in line with this approach. Particular attention has been given to handling subjective information (expert opinions) within the problem under analysis. It is shown that this information is indispensable for dealing with the sparseness of hard experience data on most of the phenomena leading to an accidental explosion. The stochastic simulation demonstrated in the paper serves the purpose of propagating uncertainties related to these phenomena. The probabilistic action model describing the potential explosion takes account of these uncertainties.
Highlights
This paper illustrates the theoretical discussion about the simulation-based forecasting mechanical effects of accidental explosions which can occur during a road transportation of explosive goods and materials
This paper illustrated an application of the simulation-based procedure developed for forecasting mechanical effects of accidental explosions on the road [1]
The form of this forecasting was a probabilistic model selected for actions induced by an accidental explosion (AE)
Summary
This paper illustrates the theoretical discussion about the simulation-based forecasting mechanical effects of accidental explosions which can occur during a road transportation of explosive goods and materials (see the fist part of the paper [1]). The case study reveals the amount and character of knowledge necessary to carry out the accident simulation. This knowledge is utilised by following the theoretical concepts embodied in the classical Bayesian approach to risk analysis. The case study demonstrates that a part of input information can be purely subjective if the knowledge in the form of hard experience data is not available for the analyst. It is shown how to introduce subjective information in the final result of the simulation, namely, a probabilistic model describing the mechanical effects of the accidental explosion. An explanation is given only to those mathematical symbols and abbreviations which are introduced in the second part
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