An equivalent linearization procedure for seismic response prediction of mdof systems

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2008
Günay, Mehmet Selim
Nonlinear response history analysis is accepted as the most accurate analytical tool for seismic response determination. However, accurate estimation of displacement responses using conceptually simple, approximate analysis procedures is preferable, since there are shortcomings in the application of nonlinear response history analysis resulting from its complexity. An equivalent linearization procedure, which utilizes the familiar response spectrum analysis as the analysis tool and benefits from the capacity principles, is developed in this thesis study as an approximate method for predicting the inelastic seismic displacement response of MDOF systems under earthquake excitations. The procedure mainly consists of the construction of an equivalent linear system by reducing the stiffness of structural members which are expected to respond in the inelastic range. Different from similar studies in literature, equivalent damping is not explicitly employed in this study. Instead, predetermined spectral displacement demands are utilized in each mode of the equivalent linear system for the determination of global displacement demands. Response predictions of the equivalent linearization procedure are comparatively evaluated by using the benchmark nonlinear response history analysis results and other approximate methods including conventional pushover analysis and modal pushover analysis (MPA). It is observed that the proposed procedure results in similar accuracy with approximate methods which employ nonlinear analysis. Considering the conceptual simplicity of the procedure and the conventional analysis tools used in its application, presented equivalent linearization procedure can be suggested as a practically applicable method for the prediction of inelastic seismic displacement response parameters with sufficient accuracy.

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Citation Formats
M. S. Günay, “An equivalent linearization procedure for seismic response prediction of mdof systems,” Ph.D. - Doctoral Program, Middle East Technical University, 2008.