Estimating shear wave velocity of soil deposits using polynomial neural networks: Application to liquefaction

Geophysical and geotechnical field investigations have introduced several techniques to measure in-situ shear wave velocity of soils. However, there are some difficulties for the easy and economical use of these techniques in the routine geotechnical engineering works. For the soil deposits, researchers have developed correlations between shear wave velocity and SPT-N values. In the present study, a new database containing the measured shear wave velocity of soil deposits have been compiled from the previously published studies. Using polynomial neural network (PNN), a new correlation has been subsequently developed for the prediction of shear wave velocity. The developed relationship shows an acceptable performance compared with the available relationships. Three examples are then presented to confirm accuracy and applicability of the proposed equation in the field of liquefaction potential assessment.

► We have developed an equation to predict shear wave velocity of soil deposits. ► The equation is a function of corrected SPT blow counts and effective overburden stress. ► Polynomial neural network was employed to train a newly compiled database of field measurements. ► The developed equation was verified via three examples of soil liquefaction potential assessment.