Blast resistance and multi-objective optimization of aluminum foam-cored sandwich panels

Abstract In this work, a group of metallic aluminum foam-cored sandwich panels (AFSPs) were used as vehicle armor against blast loading. The dynamic responses of the AFSPs with various combinations of face-sheet materials were analyzed using LS-DYNA. It was found that the AFSP with an aluminum (AA2024 T3) front face and a Rolled Homogeneous Armor (RHA) steel back face (labeled T3-AF-RHA) outperformed the other panel configurations in terms of maximum back face deflection (MaxD) and areal specific energy absorption (ASEA). It was also found that boundary conditions and the standoff distance (SoD) between an explosive and a target surface both have a remarkable influence on the blast response of the AFSPs. Using artificial neural network (ANN) approximation models, multi-objective design optimization (MDO) of the T3-AF-RHA panel was performed both with and without variations in blast load intensity. The optimization results show that the two objectives of MaxD minimization and ASEA maximization conflict with each other and that the optimal designs must be identified in a Pareto sense. Moreover, the Pareto curves obtained are different for varied blast impulse levels. Consequently, it is concluded that loading variation should be considered when designing such sandwich armors to achieve more robust blast-resistant performance.