OPTIMUM DESIGN OF TUNED MASS DAMPER PARAMETERS TO REDUCE SEISMIC RESPONSE ON STRUCTURE USING GENETIC ALGORITHM

Abstract

A tuned mass damper (TMD) is a system to improve structural performance in reducing vibration response under seismic loads. This study optimizes TMD parameters using a genetic algorithm. In this study, the structure is modeled as a spring-mass system to obtain mathematical equations. Then, those equations are used to estimate vibration due to seismic loads. A genetic algorithm is used to find optimum parameters which correspond to minimum vibrations. The simulation result shows that the genetic algorithm can find values of parameters such as the ratio of mass, stiffness, and damping values ​​which reduces vibrations on the structure. Based on the tests, it is found that the best combination of genetic algorithm parameters to produce the most optimal fitness value is population size 30, generation size 800, crossover probability 0.5, and mutation probability 0.5. Applying the genetic algorithm shows that the optimal parameter ratio values of TMD ​​to reduce the vibration response are 10% mass, 10% stiffness, and 1% damping of mass, stiffness, and damping in the structure. The result of the vibration response analysis shows that the maximum amplitude value of the main structure without TMD is 0.24259 m reduced to 0.034385 m with the addition of TMD. This shows that the TMD successfully reduces vibrations in the main structure with a percentage of 85.94%. Where the TMD manages to dissipate the energy that should only be received by the structure to the TMD itself.