• Multiphysics Modeling Of Gaseous Contaminant Transport In Deep Open Pit Mines Under Arctic Air Inversions

      Choudhury, Abhishek; Bandopadhyay, Sukumar (2011)
      Entrapment of pollutants in a deep open pit operating in a cold climate could occur due to atmospheric inversion. The process of air inversion is complex and requires thorough understanding in order to design a mine ventilation plan to remove trapped pollutants in open-pit mines operating in the arctic/sub-arctic regions. The objective of this dissertation is to develop a model using Computational Fluid Dynamics (CFD) tools for analysis of gaseous pollutant transport in deep, open pit mines under air inversion in arctic or subarctic regions. An Eulerian 3-D model was used for the development and validation of the CFD model of pollutant transport in an idealized open pit mine. No prior assumptions, turbulent or laminar, were considered for the nature of the flow. The 2-D model results indicated that air velocity, air temperature, diffusivity coefficient and slope angle were important controlling parameters in the inversion process. The flow regime was laminar at the origin, but as the flow progressed toward the center of the pit it changed to quasi-laminar and generated local eddies towards the pit bottom. The total energy of the quasi-laminar flow as well as the small local eddies was not enough to lift the inversion cap. However, a combination of quasi-turbulent flow and the local eddy transport resulted in removal of some of the pollutant mass from the pit bottom, either due to turbulent mixing, or due to advection. Presence of backflow may appear to be a logical mode of flow in deep open-pit mines in arctic regions. Next, the 3D model was validated using data from a selected open-pit mine. Influent air velocity, diffusivity coefficient, larger pit geometry were found to influence the retention and transport of pollutant out of the pit. The most important conclusion that was drawn from this research is that natural ventilation alone cannot remove the pollutants from an open pit or lift the inversion cap.
    • A novel low-cost autonomous 3D LIDAR system

      Dial, Ryker L.; Bogosyan, Seta; Hatfield, Michael; Lawlor, Orion (2018-05)
      To aid in humanity's efforts to colonize alien worlds, NASA's Robotic Mining Competition pits universities against one another to design autonomous mining robots that can extract the materials necessary for producing oxygen, water, fuel, and infrastructure. To mine autonomously on the uneven terrain, the robot must be able to produce a 3D map of its surroundings and navigate around obstacles. However, sensors that can be used for 3D mapping are typically expensive, have high computational requirements, and/or are designed primarily for indoor use. This thesis describes the creation of a novel low-cost 3D mapping system utilizing a pair of rotating LIDAR sensors, attached to a mobile testing platform. Also, the use of this system for 3D obstacle detection and navigation is shown. Finally, the use of deep learning to improve the scanning efficiency of the sensors is investigated.
    • Predictive Performance Of Machine Learning Algorithms For Ore Reserve Estimation In Sparse And Imprecise Data

      Dutta, Sridhar; Bandopadhyay, Sukumar (2006)
      Traditional geostatistical estimation techniques have been used predominantly in the mining industry for the purpose of ore reserve estimation. Determination of mineral reserve has always posed considerable challenge to mining engineers due to geological complexities that are generally associated with the phenomenon of ore body formation. Considerable research over the years has resulted in the development of a number of state-of-the-art methods for the task of predictive spatial mapping such as ore reserve estimation. Recent advances in the use of the machine learning algorithms (MLA) have provided a new approach to solve the age-old problem. Therefore, this thesis is focused on the use of two MLA, viz. the neural network (NN) and support vector machine (SVM), for the purpose of ore reserve estimation. Application of the MLA have been elaborated with two complex drill hole datasets. The first dataset is a placer gold drill hole data characterized by high degree of spatial variability, sparseness and noise while the second dataset is obtained from a continuous lode deposit. The application and success of the models developed using these MLA for the purpose of ore reserve estimation depends to a large extent on the data subsets on which they are trained and subsequently on the selection of the appropriate model parameters. The model data subsets obtained by random data division are not desirable in sparse data conditions as it usually results in statistically dissimilar subsets, thereby reducing their applicability. Therefore, an ideal technique for data subdivision has been suggested in the thesis. Additionally, issues pertaining to the optimum model development have also been discussed. To investigate the accuracy and the applicability of the MLA for ore reserve estimation, their generalization ability was compared with the geostatistical ordinary kriging (OK) method. The analysis of Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Error (ME) and the coefficient of determination (R2) as the indices of the model performance indicated that they may significantly improve the predictive ability and thereby reduce the inherent risk in ore reserve estimation.
    • Two dimensional computational fluid dynamics model of pollutant transport in an open pit mine under Arctic inversion

      Collingwood, William B. (2012-05)
      A better understanding of the microscale meteorology of deep, open pit mines is important for mineral exploitation in arctic and subarctic regions. During strong temperature inversions in the atmospheric boundary layer--which are common in arctic regions during the winter--the concentrations of gaseous pollutants in open pit mines can reach dangerous levels. In this research, a two dimensional computational fluid dynamics (CFD) model was used to study the atmosphere of an open pit mine. The natural airflow patterns in an open pit mine are strongly dependent on the geometry of the mine. Generally, mechanical turbulence created by the mine topography results in a recirculatory region at the bottom of the mine that is detached from the freestream. The presence of a temperature inversion further inhibits natural ventilation in open pit mines, and the air can quickly become contaminated if a source of pollution is present. Several different exhaust fan configurations were modeled to see if the pollution problem could be mitigated. The two dimensional model suggests that mitigation is possible, but the large quantity of ventilating air required would most likely beimpractical in an industrial setting.