Physics-based probabilistic demand model and reliability analysis for reinforced concrete beams under blast loads

This paper proposes a general physics-based probabilistic demand model for the reliability analysis of reinforced concrete (RC) beams under blast loading. The formulation proposed builds on computationally convenient representation governing physical laws from structural dynamics and adds correction term error. Specifically, starts with predictions generalized single-degree-of-freedom (SDOF) RC beam, derived conservation law energy; removes implicit bias improves accuracy model, error captures remaining uncertainty in predictions. Unknown parameters are included Once formulated, is calibrated data experimental tests or high-fidelity computational models. inclusion avoids strong dependence specific used calibration. uses Bayesian inference that combines SDOF any prior information to estimate unknown parameters. then Finally, illustrates novel contributions by estimating an beam loading three damage levels. As part analyses, also identifies dominant sources failure probability. • Probabilistic predict loads. combining data. Physic based takes into account strain-rate effects. Correction terms introduced models correct bias. Dominant probability identified.