COI code: CEUCONF04_119
Paper Language: English
How to Download This Paper
For Downloading the Fulltext of CIVILICA papers please visit the orginal Persian Section of website.
Authors Calculating Optimum Parameters of Tuned Mass Damper via Grey Wolf Optimization Method for Seismic ApplicationMilad Yazdan - Structural engineering graduate student, Department of Civil Engineering, Shahrood University of Technology
Omid Khadem Hosseini - Dept. of Civil and Architectural Engineering, Shahrood University of Technology, Shahrood, I. R. of Iran
Ali Keyhani - Dept. of Civil and Architectural Engineering, Shahrood University of Technology, Shahrood, I. R. of Iran
Mohammad Shamekhi Amiri - Dept. of Civil and Architectural Engineering, Shahrood University of Technology, Shahrood, I. R. of Iran
Abstract:In this article, optimimum mass damper is applied to decrease dynamic response in multi-story which is exposed to earthquake stimulation. Grey wolf algorithm which is meta-heuristic algorithm is a suitable method to optimize and to correct the parameters of passive mass damper. To this purpose, a Matlab program is developed which does numerical optimization and decreasing stimulation time. Optimization criterion is applied as the sum of proportion values in maximum displacement and transfer function of the first floor in controlled structure to uncontrolled structure. The impact of nonlinear material is ignored and material behavior is assumed in elastic limit. The goal of providing this procedure is optimizing mass damper parameters which are optimized in comparison to other mass damper by different methods and have better performances and more energy is dissipated. To guarantee good performance of this approach, some numerical examples are implemented to verify the effectiveness and feasibility of the presented approach. The comparison of the results to other previous works present preference for this method, because it causes the maximum of story related location being less
Keywords:Tuned Mass Damper, Grey Wolf Algorithm, Optimization, Control, State Space
COI code: CEUCONF04_119
how to cite to this paper:If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Yazdan, Milad; Omid Khadem Hosseini; Ali Keyhani & Mohammad Shamekhi Amiri, 2016, Calculating Optimum Parameters of Tuned Mass Damper via Grey Wolf Optimization Method for Seismic Application, 4th national conference on applied research in civil engineering, architecture and urban management, تهران , دانشگاه صنعتي خواجه نصيرالدين طوسي, https://www.civilica.com/Paper-CEUCONF04-CEUCONF04_119.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Yazdan, Milad; Omid Khadem Hosseini; Ali Keyhani & Mohammad Shamekhi Amiri, 2016)
Second and more: (Yazdan; Khadem Hosseini; Keyhani & Shamekhi Amiri, 2016)
For a complete overview of how to citation please review the following CIVILICA Guide (Citation)
The University/Research Center Information:
Type: state university
Paper No.: 7051
in University Ranking and Scientometrics the Iranian universities and research centers are evaluated based on scientific papers.
Research Info Management
Export Citation info of this paper to research management softwares
New Related Papers
- REVIEW ON THE USERS’ COMMENTS ON THE PATTERN USE OF A IRANIAN GARDEN IN PARKS CASE STUDY: SEMNAN CITY PARKS
- Permanent Lining Design of Tunnels Junction using Hyperstatic Reaction Method
- Investigation of changing shear strength Stability of Foundation in Major Structures
- Behavior of Prefabricated Structures in Developed and Developing Countries
- Concrete containing waste rubber particles under impact loading
The Above articles are recently indexed in the related subjects
Iran Scientific Advertisment Netword
Share this paper
WHAT IS COI?
COI is a national code dedicated to all Iranian Conference and Journal Papers. the COI of each paper can be verified online.