Shear wave velocity ( \(V_{s}\) ) plays an important role in determining the dynamic response of a soil medium and in the soil-structure interaction effect. The determination of \(V_{s}\) will always be associated with some degree of uncertainty, which can lead to substantial variation in the outcomes of ground response analysis (GRA). To account the effect of this uncertainty associated with \(V_{s}\) , statistical randomization can be adopted. In this study, random \(V_{s}\) samples of different layers are generated considering correlated random variables and then randomized \(V_{s}\) profiles are produced. Now to study the effect of different levels of uncertainty in \(V_{s}\) , three different values of log standard deviations, 0.075, 0.15, and 0.3, have been considered in the randomization. The standard deviation of 0.075 signifies the least variation, whereas, a maximum variation of 0.3 is used in the \(V_{s}\) randomization. The study is conducted for a site located in Ultadanga, Kolkata, and the site belongs to the normal Kolkata soil deposit. For each case of log standard deviation, 500 randomized \(V_{s}\) profiles are generated and a total 1500 analyses are performed. To simulate this, a MATLAB program has been developed to carry out equivalent linear GRA repeatedly for different generated randomized realizations. The study reveals a substantial effect of \(V_{s}\) uncertainty on GRA. As the \(V_{s}\) uncertainty increases, the computed standard deviations of transfer functions, spectral accelerations, and PGA variations also get increased, whereas the mean values get reduced. Finally, the surface PGA values are fitted with the probability density function and the respective cumulative distribution function is proposed for the study area.

Seismic Site Response Analysis Considering Uncertainty in Shear Wave Velocity

会议论文
发表日期：

2025年

查看全文

Narayan Roy,
Rajesh Prasad Shukla

摘要

Shear wave velocity ( \(V_{s}\) ) plays an important role in determining the dynamic response of a soil medium and in the soil-structure interaction effect. The determination of \(V_{s}\) will always be associated with some degree of uncertainty, which can lead to substantial variation in the outcomes of ground response analysis (GRA). To account the effect of this uncertainty associated with \(V_{s}\) , statistical randomization can be adopted. In this study, random \(V_{s}\) samples of different layers are generated considering correlated random variables and then randomized \(V_{s}\) profiles are produced. Now to study the effect of different levels of uncertainty in \(V_{s}\) , three different values of log standard deviations, 0.075, 0.15, and 0.3, have been considered in the randomization. The standard deviation of 0.075 signifies the least variation, whereas, a maximum variation of 0.3 is used in the \(V_{s}\) randomization. The study is conducted for a site located in Ultadanga, Kolkata, and the site belongs to the normal Kolkata soil deposit. For each case of log standard deviation, 500 randomized \(V_{s}\) profiles are generated and a total 1500 analyses are performed. To simulate this, a MATLAB program has been developed to carry out equivalent linear GRA repeatedly for different generated randomized realizations. The study reveals a substantial effect of \(V_{s}\) uncertainty on GRA. As the \(V_{s}\) uncertainty increases, the computed standard deviations of transfer functions, spectral accelerations, and PGA variations also get increased, whereas the mean values get reduced. Finally, the surface PGA values are fitted with the probability density function and the respective cumulative distribution function is proposed for the study area.