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Story‐by‐story estimation of the stiffness parameters of laterally‐torsionally coupled buildings using forced or ambient vibration data: I. Formulation and verification
Author(s) -
Omrani Roshanak,
Hudson Ralph E.,
Taciroglu Ertugrul
Publication year - 2011
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/eqe.1192
Subject(s) - vibration , stiffness , torsion (gastropod) , structural engineering , benchmark (surveying) , amplitude , algorithm , stiffness matrix , engineering , computer science , acoustics , geology , physics , medicine , surgery , geodesy , quantum mechanics
SUMMARY A new parameter estimation algorithm is described for identifying the stiffness properties of torsionally coupled shear buildings from their linear response due to ambient excitations or during low‐amplitude forced‐vibration tests. The algorithm is based on the time‐domain equations of motion, and yields estimates of the stiffness properties using a measure of the equilibrium of forces acting on each floor over a time interval. The banded structure of the stiffness matrix — a property intrinsic to torsion‐shear buildings — is exploited to decompose the initial inverse problem into several problems of reduced size. This decomposition allows the identification of lateral and torsional stiffnesses of individual stories, independent of the others. The algorithm utilizes vibration data where input excitation is known/measured, which is typical for forced‐vibration tests and earthquakes. If the ambient vibrations of the structure are adequately uncorrelated to the (unknown) external forces that induce such vibrations, then the algorithm can also be modified for output‐only system identification. The proposed algorithm is verified — and its various attributes are investigated — using simulation data from the ‘Analytical Phase I’ of the IASC (International Association for Structural Control)‐ASCE (American Society of Civil Engineers) benchmark studies. The companion article is devoted to the algorithm's application to experimental data, using data from the ‘Experimental Phase’ of the same benchmark studies. Copyright © 2011 John Wiley & Sons, Ltd.