Statistically-based air blast load factors based on imprecise parameter statistics for reinforced concrete wall

The determination of acceptable air blast load factors for Load and Resistance Factor Design (LRFD) is complicated due to highly variable loads and to non-linear and rate dependent material and structural response that can result. This has resulted in the use of blast load factors that are set equal to unity since load uncertainty, which is typically used as a probabilistic basis for developing LRFD load factors, is not considered. A precise distribution of random variables also has been required for load and resistance factor determination in LRFD. However, in the case where their distributions are uncertain due to insufficient data, such as for blast events, assumptions will be made that overlook uncertainties that should be accounted in the derivation. In this study, a combination of Response Surface Metamodels (RSM), Monte Carlo Simulations (MCS), and Probability Box (P-Box) that incorporate nonlinear finite element models were used to derive statistically-based blast load factors for LRFD. Load factor development centered on a case study involving a reinforced concrete (RC) cantilevered wall subjected to free air blasts. The resulting load factor was found to be 1.41 when precise parameter statistics were assumed. This blast load factor was then used to design a new RC cantilevered wall and this new wall was found to have its reliability close to the target value. However, when parameter uncertainty was considered, the resulting load factors based on P-Box representation were found to be a range between 1.16 and 1.74, indicating that there was a possibility that the load factor of 1.41 obtained from precise parameter statistic assumptions could be unreliable.