JOURNAL OF APPLIED GEOPHYSICS, cilt.171, 2019 (SCI-Expanded)
The pressuremeter (PMT) and standard penetration (SPT) tests are the most common in situ tests used for determining the engineering properties of soils and rocks. PMT method can be used to determine the deformation and strength properties of soil or very blocky rock masses. PMT procedure is time-consuming and expensive, and it requires advanced testing equipment. Both SPT and PMT methods also require drilling to be performed in the area. The shear wave velocity (V-s) is a parameter obtained using active and passive seismic methods and provides insight into the strength properties of the soil and rock. V-s is easy to obtain with these methods and can be determined in all kinds of field conditions. Due to the difficulties experienced during many types of in-situ tests, numerous empirical equations for the soil or rock units have been proposed in the literature that are based on V-s. In this paper, correlations of Menard Deformation Modules (E-M) with the corrected SPT blow counts (SPT-N-60) and shear wave velocity (V-s) data were conducted. For this purpose, parameters of the pressuremeter were defined as a function of two variables. In order to determine the relationship between the results of these field tests and the results obtained from high-consolidated clayey soils with high and low plasticity properties, 10 boreholes with a depth of 15 m were drilled and in-situ tests were carried out at diverse depths. In addition, seismic measurements were performed at the same locations and depth-based V-s velocity data was obtained. It was concluded that E-M could be predicted as a function of SPT-N60 and V-s values, and the predictions had relatively high R-2 values of 0.77 and 0.75, respectively. This study thereby introduces to the literature empirical equations between E-M and V-s for the first time. As soil properties are heterogeneous and anisotropic, it has been shown that it is more appropriate to use the equations produced from logarithmic and exponential relations in both single and multiple statistical analysis. (C) 2019 Elsevier B.V. All rights reserved.