Abstract
A procedure for estimating potential damage to buildings induced by accidental explosions on the railway is developed. By the damage failures of nearby structures due to actions generated by the accidental explosions are meant. This damage is measured in terms of probabilities of potential failures caused by explosions. The estimation of the damage probabilities is based on stochastic simulation of railway accidents 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. The foundation of the procedure is a computer intensive method known as the Bayesian bootstrap. It is used for approximating the posterior distributions of damage probabilities. The 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 accidental explosions.
Highlights
Accidental explosions (AEs) on the railway are dangerous, generally large-scale phenomena
This paper develops a procedure for estimating potential damage to buildings induced by accidental explosions on the railway
The present paper considers practical application of the Bayesian bootstrap to quantitative risk assessment (QRA) focused on assessing damage to structures
Summary
Accidental explosions (AEs) on the railway are dangerous, generally large-scale phenomena. By the damage failures of nearby structures caused by actions generated by AEs are meant This damage is measured in terms of probabilities of potential failures caused by AEs. The estimation of the damage probabilities is based on 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. The application of the Bayesian bootstrap makes the proposed procedure highly automatic and convenient for assessing structures subjected to the hazard of accidental actions. 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 AEs
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