TY - JOUR ID - 240750 TI - Optimum Seismic Design of Tuned Story Mass Damper Using Multi-Objective Genetic Algorithm JO - Journal of Seismology and Earthquake Engineering JA - JSEE LA - en SN - 1735-1669 AU - Azadpour, Mohammad Vahid AU - Zare, Abdolreza AU - Rahmani, Hamid AD - Yasouj University Y1 - 2016 PY - 2016 VL - 18 IS - 4 SP - 275 EP - 284 KW - Optimization KW - Seismic Response KW - genetic algorithm KW - Tuned Story Mass Damper DO - N2 - A new system called Tuned Story Mass Damper (TSMD) is proposed and modified to enhance the seismic performance of mid-rise buildings. In TSMD systems, some part of a story's mass is utilized as Mass Damper, and an external passive damping device is used to provide the expected control force. For an 11-story structural model under seismic excitations, the equations of motion are solved in state space and two objective functions, the maximum displacement and maximum velocity of the top floor are considered to be minimized simultaneously. Using a fast and elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) approach, the optimum design parameters of the TSMD system, including mass, stiffness and damping as well as the best location of the TSMD system among the floors of the structure are obtained. The results show that considering the TSMD system on the fifth floor leads to the most reduction in displacement and velocity, not only for the roof, but also for the other floors as well. For the system under study, comparing with the noncontrolled system, a reduction of about 31% on maximum displacement and 42% on maximum velocity of the top floor are obtained. UR - http://www.jsee.ir/article_240750.html L1 - http://www.jsee.ir/article_240750_60ff2280498ae5cd7c259efc6ac61a2c.pdf ER -