Optimizing Hysteresis Parameters for RC Structural Elements Using Genetic Algorithm in OpenSees

An accurate numerical model is crucial for predicting the cyclic hysteresis response of Reinforced Concrete (RC) structural elements, capturing strength and stiffness degradations along with the pinched hysteresis response typical of RC members. OpenSees, an open-source fiber modeling and analysis software, is versatile for modeling RC, steel, and composite structural elements subjected to seismic loading. While the OpenSees library offers various hysteresis material models for the cyclic response of members, selecting the hysteresis parameters of each model often relies on a black-box approach. This study optimizes hysteresis parameters using a Genetic Algorithm (GA) search method. The dynamic GA search compares the energy dissipation in each cycle of the experimental specimens with the numerical models in OpenSees to optimize the hysteresis parameters. The results show an improvement in the fitness between the simulated and experimental hysteresis curves across the generations, plateauing around the 3rd generation. The modified GA methodology terminates the GA when the fitness function plateaus, saving considerable computational run time. This approach offers a reliable method for estimating hysteresis parameters which is consistent with the experimental results.