Performing Dynamic Analysis of the Conceret Structures using Genetic Algorithm and Determining the Optimal Range during a Natural Hazard Crisis (Tempe, Arizona, USA)

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The approach employs a binary genetic algorithm alongside natural numbers. Given the differences between accelerometers and scale coefficients, the genetic algorithm introduced herein is a hybrid, featuring two chromosomes. A key factor influencing the accuracy and effectiveness of these programs is the precise estimation of their parameters. When these parameters are determined accurately, the gap between the average response spectrum and the design spectrum is significantly minimized. This program operates with two genetics that run concurrently, yielding results that closely approximate the optimal solution. The program itself is capable of offering users a range of desired coefficients, as well as values for the covariance and mutation of each chromosome. The algorithm detailed in this article can generate a new generation of individuals from an infinite array of ground motion records, utilizing processes such as natural selection, mating, and mutation, and continue this cycle until an individual meets the desired characteristics. This paper presents a novel method for optimally selecting accelerometers and scaling them for dynamic time history analysis, aiming for an average response spectrum that closely aligns with the target spectrum, reflecting the expected seismic activity for the structure in Tempe district in Arizona State. Given the relatively high number of parameters involved, reliance on trial-and-error methods is significantly influenced by the user’s skill set; thus, the hybrid genetic algorithm presented here addresses this limitation.