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title

EFFICIENCY OF OPTIMIZATION METHODS IN RETROFIT OF STEEL MOMENT RESISTING FRAMES WITH ADDED VISCOUS DAMPERS

Credit to Download: 1 | Page Numbers 16 | Abstract Views: 78
Year: 2017
Present: ارايه پوستري
COI code: ICSAU05_1757
Paper Language: English

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Authors EFFICIENCY OF OPTIMIZATION METHODS IN RETROFIT OF STEEL MOMENT RESISTING FRAMES WITH ADDED VISCOUS DAMPERS

Yadollah Davari - PHD Candidate, Azad University of Qazvin, Iran,
Maysam Reshad - PHD Candidate, Shakhespajhoh Institute ,Isfahan, Iran,

Abstract:

In this paper control of the seismic response of multi-storey steel moment resisting frames using optimally placed viscous dampers have been investigated. Therefore, five practical methods for optimal damper distribution have been investigated for two steel moment resisting frames with 8 stories. First four methods are based on simple design formulas that are based on some assumptions. The latter is simplified sequential search algorithm (SSSA) has been known as an efficient tool. Here some improvements have been proposed to enhance application of SSSA in practical design or retrofit of existing buildings. Also an efficiency index have been proposed based on sum on damper coefficients and maximum drift occurred in structure to compare resulted optimal configurations of viscous damper. Given results show that distribution of damper based on shear strain energy and improved SSSA may be efficient for practical engineers.

Keywords:

Viscous Damper, Optimal Retrofit, Steel Frames, Optimization

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COI code: ICSAU05_1757

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Davari, Yadollah & Maysam Reshad, 2017, EFFICIENCY OF OPTIMIZATION METHODS IN RETROFIT OF STEEL MOMENT RESISTING FRAMES WITH ADDED VISCOUS DAMPERS, 5th international congress of structure, architecture and urban development, تهران, دبيرخانه دايمي كنفرانس, https://www.civilica.com/Paper-ICSAU05-ICSAU05_1757.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: (Davari, Yadollah & Maysam Reshad, 2017)
Second and more: (Davari & Reshad, 2017)
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