Inference of Blast Wavefront Parameter Uncertainty for Probabilistic Risk Assessment

Abstract

Probabilistic risk assessment methodologies are typically employed to optimize resource allocations for blast risk mitigation schemes, which may be necessary for the design of new blast resistant facilities as well as the hardening of existing construction. A key aspect of any blast risk assessment methodology is the quantification of uncertainty inherent in the prediction of shock wave parameters. In this study, a blast pressure database that was generated from arena testing using live explosives is used to infer the probability distributions that best represent the model error affecting the prediction of four key wavefront parameters, namely: the peak pressure, specific impulse, duration, and waveform coefficient of the positive pressure phase. Confidence intervals are given for the descriptors of each distribution and their percentiles. In addition, two sets of partial factors are developed for the blast-resistant design of structures requiring high level of protection (LOP) based on a simplified reliability approach. Two recent North American standards addressing the design of buildings subjected to blast loads recommend load combinations in which a partial load factor of 1.0 is applied to blast induced actions. Although this approach aligns with the current design practice followed in the case of rare events (e.g., earthquakes), it may not be applicable in the case of blast loads as a result of the degree of uncertainty present even when a design basis threat is quantified. To account for this uncertainty, partial factors for the major wavefront parameters of the reflected shock wavefront are presented.