Variability of one-dimensional soil amplification estimates at four sites of the French permanent accelerometer network (RAP)

Student: Régnier Julie
Supervisors: Dr Luis Fabian Bonilla


It is widely known that soft soils amplify the seismic ground motion compared to rock sites. Thus, an accurate quantification of soil amplification is important when assessing seismic hazard. In this study, we compute site amplification estimates and response spectral ratio for different acceleration time histories scaled to different PGA's by propagating them through 1D soil models with stochastic variation of their mechanical properties. We use three models of wave propagation: the widely known equivalent linear model (Schnabel et al., 1972), the frequencydependent equivalent linear model (Kausel and Assimaki, 2002), and the elastoplastic nonlinear model developed by Iwan (1967).

We have selected four sites from the French permanent accelerometer network (RAP) deployed in the city of Nice. This city located on the French Riviera coast, is characterized by local strong site amplification due to alluvial filling. Past work has collected geophysical and geotechnical data to construct a first order 3D soil model. In this way, we have extracted the information underneath the selected RAP stations. For the nonlinear computations, we use dynamic soil properties proposed in the literature for the same kind of material found in the region of study.

We present the variability of amplification estimates among the wave propagation models. We found that frequency-dependent equivalent linear results are close to those from the traditional equivalent linear model for PGA's larger than 0.7g. Conversely, for lower PGA values, the first model deamplifies the high frequencies much lower than the second one. Furthermore, the standard deviation of amplification estimates increases as PGA and frequency increase regardless of the utilized wave propagation model. Finally, we compute response spectral ratios as a function of PGA (rock input motion), which are useful in site-specific probabilistic seismic hazard assessment (Cramer, 2003).

You may download a digital version of this MSc dissertation here.