Influence of ground motion selection on computed seismic sliding block displacement

Seismic slope stability is often evaluated via permanent displacement analyses, which quantify the cumulative, downslope displacement of a sliding mass subjected to earthquake loading. Seismic sliding block displacements provide a useful index as to the seismic performance of a slope. Seismic sliding block displacements can be computed for a suite of acceleration-time histories selected to fit a design event. This thesis explores the effect of ground motion selection on computed seismic sliding block displacements through two approaches. First, rigid sliding block displacements were computed for ground motion suites developed to fit uniform hazard spectra (UHS), conditional mean spectra (CMS), and conditional probability distributions for peak ground velocity (PGV) and Arias Intensity (Ia). Evaluation of the suites in terms of their PGV and Ia distributions provided useful insight into the relative displacements computed for the suites. The PGV and Ia distributions of the suite selected to fit the UHS exceed the theoretical distributions of these ground motion parameters. In fact, the scaled Ia values of motions in the UHS suite are greater than the largest Ia values in the Next Generation Attenuation (NGA) ground motion database. As such, the displacements computed for the UHS suite exceed the displacements computed for any other suite. If only two ground motion parameters are to be considered in ground motion selection we recommend those parameters be PGA and PGV. However, it is important to consider PGA, PGV, and Ia when developing ground motion suites for permanent displacement analyses.
Next, the use of simulated ground motions for permanent displacement analyses was addressed by comparing displacements computed for simulated ground motions to displacements computed for the corresponding recorded ground motion. Simulated ground motions generated via four seismological models were considered: the deterministic Composite Source Model (CSM), the stochastic model EXSIM, the deterministic-stochastic hybrid model by Graves and Pitarka (GP), and the deterministic-stochastic hybrid model developed at San Deigo State University (SDSU). The displacements computed for the SDSU simulations were the most similar to those computed using the recorded motions, with the average displacement of the SDSU simulations exceeding that of the corresponding recorded ground motion by about 6%. Additionally, the displacements from the SDSU simulations provided the smallest variability about the displacements computed for the recorded motions.