Genetic Optimization for the design of seismic retrofitting of plane RC frames with Buckling Restrained Braces (BRBs)

The increasing development of computational power in modern digital devices has spread the use of structural optimization in design applications of different fields of engineering problems. This approach exposes engineers to challenging design procedures aimed to optimize all variables to satisfy the imposed requirements, finding the “optimal” solution. Despite this wide use, the application of optimization algorithms for the design of seismic retrofitting strategies becomes tougher, due to the difficulties in finding a mathematical expression which includes and combines all the key variables (i.e., cost, safety, sustainability, design) and the nonlinearity of the analysis. In this paper, the Genetic Algorithm search method (GA) has been used to optimize the retrofitting, using Buckling-Restrained Braces (BRBs), of a three-storeys RC structure designed to resist only gravity loads. The optimization aims to ensure the safety level required, minimizing intervention costs and use of materials, particularly finding the best topology solution for BRB positioning. To this purpose, an objective function has been applied to the model to minimize retrofit costs intervention using GA. The procedure has been implemented in Python Programming Language. In particular non-linear static analysis has been run using OpenSeesPy framework to evaluate the seismic required safety level at each simulation, while GA has been carried out with a custom design code to provide the best topology position of BRBs to minimize costs and consequently the use of materials. The method brought out the real possibility to ensure the required seismic safety level while reducing intervention cost and use of materials with an optimized and structured BRB positioning.