• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.2
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• pp.77-86
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• 2018

This study develops an empirical prediction equation of spectral acceleration responses of earthquakes which can induce structural damages. Ground motion records representing hazards of low-to-moderate seismic regions were selected and organized with several influential factors affecting the response spectra. The empirical equation and estimator coefficients for acceleration response spectra were then proposed using a robust nonlinear optimization coupled with a regression analysis. For analytical verification of the prediction equation, response spectra used for low-to-moderate seismic regions were estimated and the predicted results were comparatively evaluated with measured response spectra. As a result, the predicted shapes of response spectra can simulate the graphical shapes of measured data with high accuracy and most of predicted results are distributed inside range of correlation of variation (COV) of 30% from perfectly correlated lines.

• Earthquakes and Structures
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• v.14 no.6
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• pp.577-587
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• 2018

The quantitative assessment of the seismic collapse risk of a structure requires the usage of an optimal intensity measure (IM) which can adequately characterise the severity of the ground motion. Research suggests that the average spectral acceleration ($Sa_{avg}$) may be an efficient and sufficient alternate IM as compared to the more traditional first mode spectral acceleration, $Sa(T_1)$, particularly during seismic collapse risk estimation. This study primarily presents a comparative evaluation of the sufficiency of the average spectral acceleration with respect to ground motion duration, and secondarily assesses the impact of ground motion duration on collapse risk estimation. By assembling a suite of 100 historical ground motions, incremental dynamic analysis of 60 different inelastic single-degree-of-freedom (SDF) oscillators with varying periods and ductility capacities were analysed, and collapse risk estimates obtained. Linear regression models are used to comparatively quantify the sufficiency of $Sa_{avg}$ and $Sa(T_1)$ using four significant duration metrics. Results suggests that an improved sufficiency may exist for $Sa_{avg}$ when the period of the SDF system increases, particularly beyond 0.5, as compare to $Sa(T_1)$. In reference to the ground motion duration measures, results indicated that the sufficiency of $Sa_{avg}$ is more sensitive to significant duration definitions that consider almost the full wave train of an accelerogram ($SD_{a5-95}$ and $SD_{v5-95}$). In order to obtain a reduced variability of the collapse risk estimate, the 5-95% significant duration metric defined using the Arias integral ($SD_{a5-95}$) should be used for seismic collapse risk estimation in conjunction with $Sa_{avg}$.