Methodology for predicting dynamic response of multi-layer aluminum foam protected RC slabs under blast loading

Abstract

Multi-layer aluminum foam with varying density distribution has been proven to exhibit significant blast alleviation capabilities under blast loads. Using the equivalent multiple degree of freedom (MDOF) method and rigid-perfectly-plastic-locking (RPPL) model, an analytical model for multi-layer aluminum foam protected RC (MF-RC) slabs is developed to predict displacement and energy properties. Studies on MF-RC slabs show that multi-layer aluminum foam with greater energy absorption causes more damage to RC slabs, revealing the limitations of the energy assessment method. RC slab displacement is used as a comprehensive assessment parameter for multi-layer aluminum foam using the pressure-impulse (P–I) diagram approach. Calculations and analyses of assessment indicators for different foam density distributions of triple-layer foam are carried out to compare their mitigation capacities under blast. Moreover, the multi-layer feedforward neural network (MFNN) is used as the surrogate model of the MDOF module, and an optimum Pareto solution between energy absorption and structural damage prevention is obtained using the non-dominated sorting genetic algorithm II (NSGA-II).