Stochastic representation of blast load damage in a reinforced concrete building

In building engineering, deterministic analyses of system level disaster scenarios, including buildings subject to explosive loading, have been widely researched and as a result there are many sophisticated methods and algorithms for simulation of such events. Similarly structural reliability or “risk-based” analyses are also well developed and the computation of the probability of failure of a structural system is readily achievable. This paper combines the Monte Carloethod, used in many structural reliability algorithms, with a simplified but conservative progressive collapse structural model. This resulting algorithm is then used to generate a dataset representing the percentage damage a ten storey reinforced concrete building sustains when subject to an explosive load of a given magnitude located randomly in the ground floor car park. The progressive collapse structural model has a non-linear transient finite element method at its core. The explosive location, magnitude and duration, as well as the building imposed loading are all modelled as random variables. Using this preliminary model, a statistical analysis of the generated data provides evidence that the percentage damage in a concrete framed building due to an explosion is Weibull distributed.

► A simplified structural model simulates explosive damage to a concrete building.
► The building sustains a ground explosion in the open car park on the ground floor.
► Monte Carlo simulation computes the percentage damage to the building.
► Statistical analyses of the dataset results are carried out.
► Probability distributions for the amount of building damage are proposed.