AI and FE Based Response of Structural Column against Blast Effects from Various Explosives Materials

Abstract

Frequent terrorist activities worldwide enhance the security threat for critical buildings and bridges which emphasizes the need of wide range research and making design guidelines for blast loaded structural elements. Moreover, accidental blasts can also have overwhelming effects of nearby structures leading to their collapse. To safeguard against all such eventualities, this numerical study focuses on parametric analysis of blast loaded RCC structural members. The purpose of this research is to examine the response of reinforced concrete column under blast loading and to find out the relative importance of the different design parameters that contribute to the resistance against blast loading. The experimental data of reinforced concrete column is taken from literature and is modelled in Finite Element Analysis software ABAQUS. The numerical model of RC column is validated with the experimental model taken from literature. After validation of the model, the Pressure-Time curves developed for numerous explosive materials are applied to the Finite Element model in terms of TNT (Trinitrotoluene). Parametric study is performed by using FE models with different geometrical and material properties. For generating empirical relations, Multiple/Gene expression programming; An artificial intelligence technique has been adopted. Results indicate good convergence of numerical models to validate experimental results involving deflection and crack patterns. Moreover, AI tools helped in simulating and predicting response of RC column against various blast loading configurations.