Towards Extracting Absolute Roughness From Underground Mine Drift Profile Data

The purpose of this paper is to demonstrate a technique to utilize underground mine drift profile data for estimating absolute roughness of an underground mine drift in order to implement the Darcy-Weisbach equation for mine ventilation calculations. This technique could provide mine ventilation engineers with more accurate information upon which they might base their ventilation systems designs. This paper presents preliminary work suggesting that it is possible to estimate the absolute roughness of drift-like tunnels by analyzing profile data (e.g., collected using a scanning laser rangefinder). The absolute roughness is then used to estimate the friction factor employed in the Darcy-Weisbach equation. The presented technique is based on an analysis of the spectral characteristics of profile ranges. Simulations based on real mine data are provided to illustrate the potential viability of this method. It is shown that mining drift roughness profiles appear similar to Gaussian profiles

Stress Inversion Using LiDAR Tunnel Deformation Measurements

Far-field stresses are those present in a volume of rock prior to excavations being created. Estimates of the orientation and magnitude of far-field stresses, often used in mine design, are generally obtained by single-point measurements of stress, or large-scale, regional trends. Point measurements can be a poor representation of far-field stresses as a result of excavation-induced stresses and geological structures. For these reasons, far-field stress estimates can be associated with high levels of uncertainty. The purpose of this thesis is to investigate the practical feasibility, applications, and limitations of calibrating far-field stress estimates through tunnel deformation measurements captured using LiDAR imaging. A method that estimates the orientation and magnitude of excavation-induced principal stress changes through back-analysis of deformation measurements from LiDAR imaged tunnels was developed and tested using synthetic data. If excavation-induced stress change orientations and magnitudes can be accurately estimated, they can be used in the calibration of far-field stress input to numerical models. LiDAR point clouds have been proven to have a number of underground applications, thus it is desired to explore their use in numerical model calibration. The back-analysis method is founded on the superposition of stresses and requires a two-dimensional numerical model of the deforming tunnel. Principal stress changes of known orientation and magnitude are applied to the model to create calibration curves. Estimation can then be performed by minimizing squared differences between the measured tunnel and sets of calibration curve deformations. In addition to the back-analysis estimation method, a procedure consisting of previously existing techniques to measure tunnel deformation using LiDAR imaging was documented. Under ideal conditions, the back-analysis method estimated principal stress change orientations within ±5° and magnitudes within ±2 MPa. Results were comparable for four different tunnel profile shapes. Preliminary testing using plastic deformation, a rough tunnel profile, and profile occlusions suggests that the method can work under more realistic conditions. The results from this thesis set the groundwork for the continued development of a new, inexpensive, and efficient far-field stress estimate calibration method.