A rock mass elastic modulus estimation using Mae Moh mine's large scale experiment data

Abstract

One of unknown rock mass properties in rock mechanics is the elastic modulus. Many researchers have proposed a variety of methods to estimate this rock mass property. One of the method is 3D numerical model calibration to obtain the key mechanical properties of the rock mass. At Mae Moh mine, Lampang, Thailand, engineers initiated a large scale field experiment of a undercut slope in northeast pit wall, named Area 4.1. The complexity of geologic structures, such as beddings and a series of normal faults, causes a number of mining and geotechnical difficulties. Inevitably, lignite exploitation could daylight a weak clay seam, called G1 seam, along the pit wall and possibly activates a massive failure of underburdened Claystone. The pit wall slope stability must not be jeopardized. The engineers planned and undercut the slope at a particular span width so that the G1 interface would be partly daylighted. Concurrently, three dimensional numerical models were constructed and analyzed as a preliminary study of the undercut slope. A number of assumptions such as the rock mass's physical properties and strength were added into the preliminary numerical models. So far, Area 4.1 was successfully undercut and stable as planned. During the field experiment, the water pressure and ground displacements were monitored. This slope monitoring data and the numerical analysis results were useful to make a better understanding of the undercut slope behavior at Mae Moh mine. To improve the accuracy of the numerical model analysis, the monitoring data was used for the rock mass elastic modulus determination and the numerical model calibration. After the numerical model calibration, the rock mass elastic modulus was determine and range 103.6-119.7MPa. If the undercut slope's failure and related information are available, it is possibly able to determine the rock mass strength with the same numerical calibration and finally improve the numerical model analysis accuracy. © 2014 Taylor & Francis Group, London.