Volume 6, Number 4 (10-2016)                   2016, 6(4): 595-610 | Back to browse issues page

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Khatibinia M, Gholami H, Labbafi S F. MULTI–OBJECTIVE OPTIMIZATION OF TUNED MASS DAMPERS CONSIDERING SOIL–STRUCTURE INTERACTION. International Journal of Optimization in Civil Engineering. 2016; 6 (4) :595-610
URL: http://ijoce.iust.ac.ir/article-1-275-en.html

Abstract:   (1864 Views)

Tuned  mass  dampers  (TMDs)  are  as  a  efficient  control  tool  in  order  to  reduce  undesired vibrations  of  tall  buildings  and  large–span  bridges  against  lateral  loads  such  as  wind  and earthquake. Although many researchers has been widely  investigated  TMD systems  due to its  simplicity  and  application,  the  optimization  of  parameters  and  placement  of  TMD  are challenging tasks. Furthermore, ignoring the effects of soil–structure interaction (SSI) may lead to unrealistic desig of structure and its dampers. Hence, the  effects of SSI should be considered  in  the  design  of  TMD.  Therefore,  the  main  aim  of  this  study  is  to  optimize parameters  of  TMD  subjected  to  earthquake  and  considering  the  effects  of  SSI.  In  this regard,  the  parameters  of  TMD  including  mass,  stiffness  and   damping  optimization  are considered  as  the  variables  of  optimization.  The  maximum  absolute  displacement  and acceleration of structure are also simultaneously selected as objective functions. The multi –objective particle  swarm optimization  (MOPSO) algorithm  is adopted  to find  the  optimal parameters  of  TMD.  In  this  study,  the  Lagrangian  method  is  utilized  for  obtaining  the equations of motion for SSI system, and the time domain analysis is implemented based on Newmark method. In order to investigate the effects of SSI in the optimal design of TMD, a 40 storey shear building with a TMD subjected to the El–Centro earthquake is considered. The  numerical  results  show  that  the  SSI  effects  have  the  significant  influence  on  the optimum parameters of TMD.

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Type of Study: Research | Subject: Optimal design
Received: 2016/05/7 | Accepted: 2016/05/7 | Published: 2016/05/7

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