Optimum Parameters for Tuned Mass Damper Using Shuffled Complex Evolution (SCE) Algorithm

Authors

  • Hashem Shariatmadar Associated Professor, Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
  • Hessamoddin Meshkat Razavi Ph.D. Candidate, Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Abstract:

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.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

optimum parameters for tuned mass damper using shuffled complex evolution (sce) algorithm

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 ...

full text

Optimization of Tuned Mass Damper Parameters Using Evolutionary Operation Algorithm

Optimum parameters of Tuned Mass Dampers (TMD) are determined in this paper to minimize dynamic response of a multi-storied building system. The response of the structural system is simulated under lateral excitation. To optimize dynamic parameters of the TMD system for minimum top deflection of the structure, a numerical global optimization algorithm called Evolutionary Operation (EVOP) is use...

full text

multi reservoir optimal operation using shuffled complex evolution (sce) algorithm (case study: karkheh basin)

in recent decades, evolutionary algorithms have been applied successfully in various water resource engineering and management issue especially in optimal operation of reservoirs. in this paper, a model based on shuffled complex evolution (sce) algorithm has been developed for modeling optimal operation of complex multi reservoir system of karkheh basin. the system includes 4 different agricult...

full text

Real time tuned mass damper simulation system

The major concern in the construction industry in constructing tall structures is vibration due to wind and earthquake. Tuned mass dampers are an effective and practical ways to reduce the effect of vibration in structures. This thesis presents a tool, which simulates the effect of tuned mass dampers on the structure. This tool has been proposed to form a part of the website, moment.mit.edu. Ja...

full text

A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters

[1] Markov Chain Monte Carlo (MCMC) methods have become increasingly popular for estimating the posterior probability distribution of parameters in hydrologic models. However, MCMC methods require the a priori definition of a proposal or sampling distribution, which determines the explorative capabilities and efficiency of the sampler and therefore the statistical properties of the Markov Chain...

full text

Automatic Calibration Tool for Hydrologic Simulation Program-FORTRAN Using a Shuffled Complex Evolution Algorithm

Hydrologic Simulation Program-Fortran (HSPF) model calibration is typically done manually due to the lack of an automated calibration tool as well as the difficulty of balancing objective functions to be considered. This paper discusses the development and demonstration of an automated calibration tool for HSPF (HSPF-SCE). HSPF-SCE was developed using the open source software “R”. The tool empl...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 48  issue 1

pages  83- 100

publication date 2015-06-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023