GNGTS 2017 - 36° Convegno Nazionale

646 GNGTS 2017 S essione 3.2 λ b , which we note in Fig. 1b as λ d . Taking this behavior into consideration, we simulate models of sand having the estimated VS and VP gradients and various thicknesses in order to obtain the W/D curve that presents a deviation from linearity at wavelength equal to λ d and a break point at a wavelength equal to λ b . The depth coordinate of the break point gives us an accurate estimation of the sand bottom depth. The obtained value is 30.01 m, approximating the true one with an error of 1%. Another interesting point is the sensitivity of the W/D on the Poisson’s ratio. In Fig. 2a we present the effect of variation of the Poisson’s ratio. VS is kept constant and VP varies in the sand, corresponding to the increase in v from 0.18 to 0.38 in steps of 0.02 (Poisson’s ratio for dry sand usually ranges between 0.2 and 0.3). The corresponding W/Ds are plotted with the same color scale in Fig. 2b. We observe that the W/D presents a quasi linear sensitivity to Poisson’s ratio that increases with depth and can therefore be used, once the VS gradient parameters have been estimated, to estimate the Poisson’s ratio value in the sand, without the need of higher modes. Conclusions. We showed with synthetic modeling that it is possible to use SW to characterize loose soils in terms of VS and VP. By including in the inversion procedure the W/D relationship we are able to estimate with accuracy the thickness of the loose soil. This relationship presents also an important sensitivity to Poisson’s ratio which can be used to estimate VP using only the fundamental mode of the DC. References Bergamo P., and L.V. Socco, 2013, Estimation of P- and S-wave velocity of unconsolidated granular materials through surface wave multimodal inversion: SEGAnnual Meeting, Expanded Abstract, 1776-1781, doi: 10.1190/ segam2013-1061.1. Bergamo, P., L.V. Socco, 2016, P- and S-wave velocity models of shallow dry sand formations from surface wave multimodal inversion: GEOPHYSICS, 81, 4, R197–R209, doi: 10.1190/GEO2015-0542.1. Foti, S., and C. Strobbia, 2002, Some notes on model parameters for surface wave data inversion: Symposium on the Application of Geophysics to Engineering and Environmental Problems SAGEEP, SEI6; doi:10.4133/1.2927179. Gassmann, F., 1951, Elastic waves through a packing of spheres: Geophysics, 16, 673–685, doi: 10.1190/1.1437718. Gusev, V., V. Aleshin, and V. Tournat, 2006, Acoustic waves in an elastic channel near the free surface of granular media: Physical Review Letters, 96, 214301, doi: 10.1103/PhysRevLett.96.214301. Maraschini, M, 2008, A new approach for the inversion of Rayleigh and Scholte waves in site characterization, PhD dissertation, Politecnico di Torino. Nazarian, S., 1984, In situ determination of elastic moduli of soil deposits and pavement systems by Spectral-Analysis- of-Surface waves method: PhD dissertation University of Texas at Austin. Pelekis, P.C., and G.A. Athanasopoulos, 2011, “An overview of surface wave methods and a reliability study of a simplified inversion technique”, Soil Dynamics and Earthquake Engineering ,31, 1654–1668 Socco, L.V., C. Strobbia, 2004, Surface-wave method for near-surface characterization: a tutorial: Near Surface Geophysics 2,4 165-185 DOI:10.3997/1873-0604.2004015 Socco L.V., C. Comina, 2017a, Time-average velocity estimation through surface-wave analysis: Part 1 — S-wave velocity: GEOPHYSICS, 82, 3, U49–U59, doi: 10.1190/GEO2016-0367.1 Socco L.V., C. Comina, 2017b, Time-average velocity estimation through surface-wave analysis: Part 2 — P-wave velocity: GEOPHYSICS, 82, 3, U61–U73, doi: 10.1190/GEO2016-0368.1 Zimmer, M. A., M. Prasad, G. Mavko, and A. Nur, 2007, Seismic velocities of unconsolidated sands: Part 1 — Pressure trends from 0.1 to 20 MPa: Geophysics, 72, 1, E1–E13, doi: 10.1190/1.2399459.