Prediction of the impact force on reinforced concrete beams from a drop weight

Abstract

It is always a challenge to efficiently and accurately estimate the force on structures from falling objects. This study aims to predict the maximum impact force on reinforced concrete beams subjected to drop-weight impact using artificial neural network. A new empirical model including a comprehensive version and a simplified version is proposed to estimate the maximum impact force. The model was verified against a database collected from the literature including 67 reinforced concrete beams tested under drop-weight impacts. The database covers the concrete strengths ranging from 23 to 47 MPa, the projectile mass from 150 to 500 kg, and the impact velocity up to 9.3 m/s. The prediction of the comprehensive version of the proposed model fits the experimental results very well with an average absolute error of 11.6%. The simplified version of the proposed model is established for easy estimation, with the average error of 23.2% in prediction of the maximum impact force.