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Optimal Distribution of Damping Coefficients for Viscous Dampers in Buildings

Author(s):


Medium: journal article
Language(s): English
Published in: International Journal of Structural Stability and Dynamics, , n. 4, v. 17
Page(s): 1750054
DOI: 10.1142/s0219455417500547
Abstract:

Design guidelines for implementing viscous dampers to buildings have been broadly included in seismic design codes worldwide. Although the relationship between the damping coefficient of viscous dampers and the added damping ratio to the structure has been theoretically studied, the process of distributing the damping coefficient onto each story of a building has not been regulated by the codes. For practical applications, some distribution methods have been previously proposed. However, no comparison has been made between these proposed methods considering the controllability and design economy. In this paper, two search methods based on the genetic algorithms (GAs) are adopted to examine the optimal distribution of damping coefficients. The results are then compared with a variety of existing distribution methods. A comparison is made for the distribution methods assuming the same added damping ratio for the structure. Three two-dimensional frames are adopted in the comparison: a regular moment frame, a moment frame with a soft-story, and a setback building. The results indicated that similar seismic response reduction can be achieved by using different distribution methods if the supplemental damping ratio is the same, while the optimal story damping coefficient can be obtained by using the proposed optimization method. Moreover, the “story shear strain energy to efficient stories” (SSSEES) method, among others, offers advantages in terms of seismic reduction efficiency, economical design, and practical application simplicity.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1142/s0219455417500547.
  • About this
    data sheet
  • Reference-ID
    10352397
  • Published on:
    14/08/2019
  • Last updated on:
    14/08/2019
 
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