The GBESO Method Based on FEA with Discrete Models and Application for Aided Design to Members in RC D-Region

Abstract

To better utilize topology optimization theory to assist in designing reinforced concrete (RC) D-region members, a novel application mode, the Genetic Bi-directional Evolutionary Structural Optimization (GBESO) method based on Finite Element Analysis (FEA) with discrete models is proposed. Correspondingly a design method for reinforcement layout of RC D-region members is also derived. Non-linear FEA verification is conducted on numerical examples involving deep beams with openings. The results demonstrate that the GBESO algorithm exhibits better global optimization capacities compared to Evolutionary Structural Optimization-type (ESO-type) algorithms. It also provides rebar topologies that are more in line with the optimization objective, bringing lower steel consumption and higher rebar utilization rates. Moreover, by introducing inclined rebar to the members, their shear strength is enhanced to a level comparable to the flexural one, significantly improving ultimate load-bearing capacity, elastoplastic deformation capacity, and better ductility compared to empirical method.