TY - JOUR ID - 53709 TI - Optimum Parameters for Tuned Mass Damper Using Shuffled Complex Evolution (SCE) Algorithm JO - Civil Engineering Infrastructures Journal JA - CEIJ LA - en SN - 2322-2093 AU - Meshkat Razavi, Hessamoddin AU - Shariatmadar, Hashem AD - Ph.D. Candidate, Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran AD - Associated Professor, Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran Y1 - 2015 PY - 2015 VL - 48 IS - 1 SP - 83 EP - 100 KW - Dynamic Magnification Factors KW - Earthquake excitation KW - Response Reduction KW - Shuffled Complex Evolution (SCE) KW - Tuned Mass Damper (TMD) DO - 10.7508/ceij.2015.01.007 N2 - This study is investigated the optimum parameters for a tuned mass damper (TMD) under the seismic excitation. Shuffled complex evolution (SCE) is a meta-heuristic optimization method which is used to find the optimum damping and tuning frequency ratio for a TMD. The efficiency of the TMD is evaluated by decreasing the structural displacement dynamic magnification factor (DDMF) and acceleration dynamic magnification factor (ADMF) for a specific vibration mode of the structure. The optimum TMD parameters and the corresponding optimized DDMF and ADMF are achieved for two control levels (displacement control and acceleration control), different structural damping ratio and mass ratio of the TMD system. The optimum TMD parameters are checked for a 10-storey building under earthquake excitations. The maximum storey displacement and acceleration obtained by SCE method are compared with the results of other existing approaches. The results show that the peak building response decreased with decreases of about 20% for displacement and 30% for acceleration of the top floor. To show the efficiency of the adopted algorithm (SCE), a comparison is also made between SCE and other meta-heuristic optimization methods such as genetic algorithm (GA), particle swarm optimization (PSO) method and harmony search (HS) algorithm in terms of success rate and computational processing time. The results show that the proposed algorithm outperforms other meta-heuristic optimization methods. UR - https://ceij.ut.ac.ir/article_53709.html L1 - https://ceij.ut.ac.ir/article_53709_744617dc553f1b80dc30f13fdf35991f.pdf ER -