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May 1, 2009

Predictive Models for the Median and Variability of Building Period and Damping

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Publication: Journal of Structural Engineering
Volume 135, Issue 5

Abstract

There are two goals in this paper: (1) the presentation of a comprehensive database of over 4,000 fundamental period and damping measurements from nearly 1,000 buildings; and (2) the derivation of predictive models for period and damping. The modeling approach presented in the companion paper, which accounts for the statistically nonconforming properties that characterize building data, is used herein to derive models which include two intrinsic sources of variability: that associated with multiple measurements from different excitations on the same building and variability between buildings that are nominally identical. The period models are in general agreement with those currently used, with model parameters that are in terms of height, material, and lateral force resisting system. The damping models show a decrease in damping as building height increases and, for steel and reinforced structures, a twofold increase in damping for earthquake excitations as opposed to other, lower amplitude excitations.

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Acknowledgments

This material is based upon work partially supported by the National Science Foundation at Johns Hopkins University under Grant No. NSFDMI-0087032. This research support is gratefully acknowledged.

References

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Information & Authors

Information

Published In

Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 135Issue 5May 2009
Pages: 576 - 586

History

Received: Feb 1, 2007
Accepted: Nov 5, 2008
Published online: May 1, 2009
Published in print: May 2009

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Notes

Note. Associate Editor: Sankaran Mahadevan

Authors

Affiliations

William P. Fritz
19 Hickory Ridge Ct., Catonsville, MD 21228.
Nicholas P. Jones, M.ASCE
Benjamin T. Rome Dean, Whiting School of Engineering, Johns Hopkins Univ., Baltimore, MD 21218.
Takeru Igusa, A.M.ASCE [email protected]
Professor, Dept. of Civil Engineering, Johns Hopkins Univ., Baltimore, MD 21218 (corresponding author). E-mail: [email protected]

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