Assessment of saturation triggered slope failure by using self-potential measurements and FLAC3D numerical model

• Main Authors: Chin-Wei Lin, 林芷薇
• Other Authors: Chuen-Fa Ni
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/80767481369016020815

碩士 === 國立中央大學 === 應用地質研究所 === 104 === The changes of pore pressure in slopes is recognized to be the main reason to trigger slope failure events. Pore pressure monitoring are the typical means in providing early warnings for such slope disasters. Comparing with other geophysical measuring methods, self-potential technique is an efficient, convenient, labor-saving and non-invasive method for site characterization. To assess the variations of self-potential signal induced by pore pressure variations and slope failure events, this study employed the technique of self-potential measurements for monitoring saturation process and the associated slope failure processes in a two-dimensional sandbox experiment. In the experiment, the distribution of self-potential were measured associated with monitoring of slope failure events and pore pressure variations in the sandbox. The study also employed numerical models to simulate the soil saturation and slope failure processes in the sandbox. The Hydrus2D numerical model was employed to estimate soil hydraulic conductivity based on the distribution of pressure head near and below the developed slope in the sandbox. This study then used FLAC3D software to simulate and calibrate the slope failure in the sandbox. The pore pressure variations and slope failure events from FLAC3D software are the basis to develop relationship between pore pressure and self-potential variations. Experiment results showed that the increase of soil saturation can lead to increase of self-potential voltage differences. However, significant drops of signals are obtained associated with the slope failure events. The pore pressure (or saturation) is positive correlated with the self-potential variations. However, the negative correlation was obtained right before a slope failure event (few seconds before the first slope failure event). Such behavior can be one of the precursor to predict slope failure evens for practical applications.