Bayesian approach to forecasting damage to buildings from accidental explosions on railway

Abstract

A procedure for estimating potential damage to buildings induced by accidental explosions on railway is developed. By the damage are meant failures of nearby structures due to actions generated by the accidental explosions. This damage is measured in terms of probabilities of potential failures caused by the explosions. The estimation of the damage probabilities is based on a stochastic simulation of railway accident involving an explosion. The proposed simulation-based procedure quantifies epistemic (state-of-knowledge) uncertainties in the damage probabilities. These uncertainties are expressed in terms of Bayesian prior and posterior distributions. A foundation of the procedure is a computer intensive method known as a Bayesian bootstrap. It is used for approximating the posterior distributions of damage probabilities. An application of the Bayesian bootstrap makes the proposed procedure highly automatic and convenient for assessing structures subjected to the hazard of the accidental actions. In addition, it can be used for specifying safe distances between the railway and nearby buildings. Structures of these buildings can be designed for tolerable probabilities of failures induced by the accidental explosions.