• Geophysics and Geophysical Exploration
• /
• v.9 no.3
• /
• pp.207-224
• /
• 2006

It has been widely known that the seismic piezo-cone penetration test (SCPTu) is one of the most useful techniques for investigating the geotechnical characteristics such as static and dynamic soil properties. As practical applications in Korea, SCPTu was carried out at two sites in Busan and four sites in Incheon, which are mainly composed of alluvial or marine soil deposits. From the SCPTu waveform data obtained from the testing sites, the first arrival times of shear waves and the corresponding time differences with depth were determined using the cross-over method, and the shear wave velocity $(V_S)$ profiles with depth were derived based on the refracted ray path method based on Snell's law. Comparing the determined $V_S$ profile with the cone tip resistance $(q_t)$ profile, both trends of profiles with depth were similar. For the application of the conventional CPTu to earthquake engineering practices, the correlations between $V_S$ and CPTu data were deduced based on the SCPTu results. For the empirical evaluation of $V_S$ for all soils together with clays and sands which are classified unambiguously in this study by the soil behavior type classification index $(I_C)$, the authors suggested the $V_S-CPTu$ data correlations expressed as a function of four parameters, $q_t,\;f_s,\;\sigma'_{v0}$ and $B_q$, determined by multiple statistical regression modeling. Despite the incompatible strain levels of the downhole seismic test during SCPTu and the conventional CPTu, it is shown that the $V_S-CPTu$ data correlations for all soils, clays and sands suggested in this study is applicable to the preliminary estimation of $V_S$ for the soil deposits at a part in Korea and is more reliable than the previous correlations proposed by other researchers.

• Journal of the Korean Geotechnical Society
• /
• v.20 no.8
• /
• pp.77-87
• /
• 2004

In this paper a back-propagation neural network model is developed to estimate the preconsolidation pressure of Korean soft soils based on 176 oedometer tests and 63 piezocone test results, which were compiled from 11 sites - western and southern parts of Korea. Only 147 data were used for the training of the neural network and 29 data, which were not used during the training phase, were used for the verification of trained network. Empirical and theoretical models were compared with the developed neural network model. A simple 4-4-9-1 multi-layered neural network has been developed. The cone tip resistance $q_T$ penetration pore pressure $u_2$, total overburden pressure $\sigma_{vo}$ and effective overburden pressure $\sigma'_{vo}$ were selected as input variables. The developed neural network model was validated by comparing the prediction results of the proposed neural network model for the new data which were not used for the training of the model with the measured preconsolidation pressures. It can also predict more precise and reliable preconsolidation pressures than the analytical and empirical model. Furthermore, it can be carefully concluded that neural network model can be used as a generalized model for prediction of preconsolidation pressure throughout Korea since developed model shows good performance for the new data which were not used in both training and testing data.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.12
• /
• pp.67-76
• /
• 2006

The reasonable assessment of the shear stiffness of a dredged soft ground and soft clay is difficult due to the soil disturbance. This study addresses the development and application of a new in-situ shear wave measuring apparatus (field velocity probe: FVP), which overcomes several of the limitations of conventional methods. Design concerns of this new apparatus include the disturbance of soils, cross-talking between transducers, electromagnetic coupling between cables, self acoustic insulation, the constant travel distance of S-wave, the rotation of the transducer, directly transmitted wave through a frame from transducer to transducer, and protection of the transducer and the cable. These concerns are effectively eliminated by continuous improvements through performing field and laboratory tests. The shear wave velocity of the FVP is simply calculated, without any inversion process, by using the travel distance and the first arrival time. The developed FVP Is tested in soil up to 30m in depth. The experimental results show that the FVP can produce every detailed shear wave velocity profiles in sand and clay layers. In addition, the shear wave velocity at the tested site correlates well with the cone tip resistance. This study suggests that the FVP may be an effective technique for measuring the shear wave velocity in the field to assess dynamic soil properties in soft ground.