Variability in Inelastic Displacement Demands: Uncertainty in System Parameters versus Randomness in Ground Records
Quantifying the relative contribution of (1) widely recognized Record-to-Record variability, versus (2) inherent randomness in system parameters, to the total variance in the inelastic displacement ratios for first mode-dominant structures with equal nominal relative lateral strength, is the major goal of this paper. Random System Parameters addressed herein are: the system normalized lateral yield strength and the system viscous damping ratio, independently considered. Monte Carlo Simulation technique is used to generate a large number of displacement ratios for a wide range of SDOF systems subjected to a selected set of 20 scaled earthquake records. Various central tendency measures, as well as coefficients of variation to quantify dispersions, are evaluated for the resulting displacement ratios. It has been noted that the dispersion in the values of the displacement ratios that is explained by randomness in system parameters is much smaller than the dispersion due to Record-to-Record variability. Estimates for such dispersions have been reported for potential implementation in emerging probabilistic performance-based seismic design and evaluation methods. It has been also demonstrated that the resulting dispersion in displacement ratios due to uncertainty in system parameters is less than the intrinsic dispersion in the system parameters themselves except at a very few situations and for short periods only.
S. S. Mehanny and A. S. Ayoub, "Variability in Inelastic Displacement Demands: Uncertainty in System Parameters versus Randomness in Ground Records," Engineering Structures, vol. 30, no. 4, pp. 1002-1013, Elsevier, Apr 2008.
The definitive version is available at https://doi.org/10.1016/j.engstruct.2007.06.009
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Inelastic Displacement Ratio; Lateral Strength; Randomness; Uncertainty; Variability; Damping (Mechanics)
International Standard Serial Number (ISSN)
Article - Journal
© 2008 Elsevier, All rights reserved.
01 Apr 2008