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Direct Use Of Pgv For Estimating Peak Nonlinear Oscillator DisplacementsKucukdogan, Bilge 01 November 2007 (has links) (PDF)
DIRECT USE OF PGV FOR ESTIMATING PEAK NONLINEAR OSCILLATOR
DISPLACEMENTS
KÜ / Ç / Ü / KDOGAN, Bilge
Recently established approximate methods for estimating the lateral deformation
demands on structures are based on the prediction of nonlinear oscillator
displacements (Sd,ie). In this study, a predictive model is proposed to estimate the
inelastic spectral displacement as a function of peak ground velocity (PGV). Prior to
the generation of the proposed model, nonlinear response history analysis is
conducted on several building models of wide fundamental period range and
hysteretic behavior to observe the performance of selected demands and the chosen
ground-motion intensity measures (peak ground acceleration, PGA, peak ground
velocity, PGV and elastic pseudo spectral acceleration at the fundamental period
(PSa(T1)). Confined to the building models used and ground motion dataset, the
correlation studies revealed the superiority of PGV with respect to the other intensity
measures while identifying the variation in global deformation demands of structural
systems (i.e., maximum roof and maximum interstory drift ratio). This rational is the
deriving force for proposing the PGV based prediction model. The proposed model
accounts for the variation of Sd,ie for bilinear hysteretic behavior under constant
ductility (µ / ) and normalized strength ratio (R) associated with postyield stiffness ratios
of = 0% and = 5%. Confined to the limitations imposed by the ground-motion
database, the predictive model can estimate Sd,ie by employing the PGV predictions
obtained from the attenuation relationships. This way the influence of important
seismological parameters can be incorporated to the variation of Sd,ie in a fairly
rationale manner. Various case studies are presented to show the consistent
estimations of Sd,ie by the proposed model using the PGV values obtained from
recent ground motion prediction equations.
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