Evaluation of a ToF Camera for Remote Surveying of Underground Cavities Excavated by Jet Boring

Cigar Lake is a high-grade uranium deposit, located in northern Saskatchewan, Canada. In order to extract the uranium ore remotely, thus ensuring minimal radiation dose to workers and also to access the ore from stable ground, the Jet Boring System (JBS) was developed by Cameco Corporation. This system uses a high-powered water jet to remotely excavate cavities. Survey data is required to determine the final shape, volume, and location of the cavity for mine planning purposes and construction. This paper provides an overview of the challenges involved in remotely surveying a JBS-mined cavity and studies the potential use of a time-of-flight (ToF) camera for remote cavity surveying. It reports on data collected and analyzed from inside an experimental environment as well as on real data acquired on site from the Cigar Lake and Rabbit Lake mines.

Admittance Control for Robotic Loading: Design and Experiments with a 1-Tonne Loader and a 14-Tonne LHD

This paper describes the design, tuning, and extensive field testing of an admittance-based Autonomous Loading Controller (ALC) for robotic excavation. Several iterations of the ALC were tuned and tested in fragmented rock piles—similar to those found in operating mines—by using both a robotic 1-tonne capacity Kubota R520S diesel-hydraulic surface loader and a 14-tonne capacity Atlas Copco ST14 underground load-haul-dump (LHD) machine. On the R520S loader, the ALC increased payload by 18 % with greater consistency, although with more energy expended and longer dig times when compared with digging at maximum actuator velocity. On the ST14 LHD, the ALC took 61 % less time to load 39 % more payload when compared to a single manual operator. The manual operator made 28 dig attempts by using three different digging strategies, and had one failed dig. The tuned ALC made 26 dig attempts at 10 and 11 MN target force levels. All 10 11 MN digs succeeded while 6 of the 16 10 MN digs failed. The results presented in this paper suggest that the admittance-based ALC is more productive and consistent than manual operators, but that care should be taken when detecting entry into the muck pile

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.

Analysis of Cosmogenic Impurities in Tellurium and Development of Tellurium Loading for the SNO+ Experiment

For the SNO+ neutrinoless double beta decay search, various backgrounds, ranging from impurities present naturally to those produced cosmogenically, must be understood and reduced. Cosmogenic backgrounds are particularly difficult to reduce as they are continually regenerated while exposed to high energy cosmic rays. To reduce these cosmogenics as much as possible the tellurium used for the neutrinoless double beta decay search will be purified underground. An analysis of the purification factors achievable for insoluble cosmogenic impurities found a reduction factor of $>$20.4 at 50\% C.L.. During the purification process the tellurium will come into contact with ultra pure water and nitric acid. These liquids both carry some cosmogenic impurities with them that could be potentially transferred to the tellurium. A conservative limit is set at $<$18 events in the SNO+ region of interest (ROI) per year as a result of contaminants from these liquids. In addition to cosmogenics brought underground, muons can produce radioactive isotopes while the tellurium is stored underground. A study on the rate at which muons produce these backgrounds finds an additional 1 event per year. In order to load the tellurium into the detector, it will be combined with 1,2-butanediol to form an organometallic complex. The complex was found to have minimal effect on the SNO+ acrylic vessel for 154 years.

The Economic Case for Electric Mining Equipment and Technical Considerations Relating to their Implementation

Underground hardrock mining can be very energy intensive and in large part this can be attributed to the power consumption of underground ventilation systems. In general, the power consumed by a mine’s ventilation system and its overall scale are closely related to the amount of diesel power in operation. This is because diesel exhaust is a major source of underground air pollution, including diesel particulate matter (DPM), NO2 and heat, and because regulations tie air volumes to diesel engines. Furthermore, assuming the size of airways remains constant, the power consumption of the main system increases exponentially with the volume of air supplied to the mine. Therefore large diesel fleets lead to increased energy consumption and can also necessitate large capital expenditures on ventilation infrastructure in order to manage power requirements. Meeting ventilation requirements for equipment in a heading can result in a similar scenario with the biggest pieces leading to higher energy consumption and potentially necessitating larger ventilation tubing and taller drifts. Depending on the climate where the mine is located, large volumes of air can have a third impact on ventilation costs if heating or cooling the air is necessary. Annual heating and cooling costs, as well as the cost of the associated infrastructure, are directly related to the volume of air sent underground. This thesis considers electric mining equipment as a means for reducing the intensity and cost of energy consumption at underground, hardrock mines. Potentially, electric equipment could greatly reduce the volume of air needed to ventilate an entire mine as well as individual headings because they do not emit many of the contaminants found in diesel exhaust and because regulations do not connect air volumes to electric motors. Because of the exponential relationship between power consumption and air volumes, this could greatly reduce the amount of power required for mine ventilation as well as the capital cost of ventilation infrastructure. As heating and cooling costs are also directly linked to air volumes, the cost and energy intensity of heating and cooling the air would also be significantly reduced. A further incentive is that powering equipment from the grid is substantially cheaper than fuelling them with diesel and can also produce far fewer GHGs. Therefore, by eliminating diesel from the underground workers will enjoy safer working conditions and operators and society at large will gain from a smaller impact on the environment. Despite their significant potential, in order to produce a credible economic assessment of electric mining equipment their impact on underground systems must be understood and considered in their evaluation. Accordingly, a good deal of this thesis reviews technical considerations related to the use of electric mining equipment, especially ones that impact the economics of their implementation. The goal of this thesis will then be to present the economic potential of implementing the equipment, as well as to outline the key inputs which are necessary to support an evaluation and to provide a model and an approach which can be used by others if the relevant information is available and acceptable assumptions can be made.

Towards Mapping of Rock Walls Using a UAV-Mounted 2D Laser Scanner in GPS Denied Environments

In geotechnical engineering, the stability of rock excavations and walls is estimated by using tools that include a map of the orientations of exposed rock faces. However, measuring these orientations by using conventional methods can be time consuming, sometimes dangerous, and is limited to regions of the exposed rock that are reachable by a human. This thesis introduces a 2D, simulated, quadcopter-based rock wall mapping algorithm for GPS denied environments such as underground mines or near high walls on surface. The proposed algorithm employs techniques from the field of robotics known as simultaneous localization and mapping (SLAM) and is a step towards 3D rock wall mapping. Not only are quadcopters agile, but they can hover. This is very useful for confined spaces such as underground or near rock walls. The quadcopter requires sensors to enable self localization and mapping in dark, confined and GPS denied environments. However, these sensors are limited by the quadcopter payload and power restrictions. Because of these restrictions, a light weight 2D laser scanner is proposed. As a first step towards a 3D mapping algorithm, this thesis proposes a simplified scenario in which a simulated 1D laser range finder and 2D IMU are mounted on a quadcopter that is moving on a plane. Because the 1D laser does not provide enough information to map the 2D world from a single measurement, many measurements are combined over the trajectory of the quadcopter. Least Squares Optimization (LSO) is used to optimize the estimated trajectory and rock face for all data collected over the length of a light. Simulation results show that the mapping algorithm developed is a good first step. It shows that by combining measurements over a trajectory, the scanned rock face can be estimated using a lower-dimensional range sensor. A swathing manoeuvre is introduced as a way to promote loop closures within a short time period, thus reducing accumulated error. Some suggestions on how to improve the algorithm are also provided.