Browsing College of Engineering and Mines (CEM) by Subject "Simulation methods"
Now showing items 1-2 of 2
Dynamic simulator for a grinding circuitThe grinding circuit is a primary and indispensable unit of a mineral processing plant. The product from a grinding circuit affects the recovery rate of minerals in subsequent downstream processes and governs the amount of concentrate produced. Because of the huge amount of energy required during the grinding operation, they contribute to a major portion of the concentrator cost. This makes grinding a crucial process to be considered for optimization and control. There are numerous process variables that are monitored and controlled during a grinding operation. The variables in a grinding circuit are highly inter-related and the intricate interaction among them makes the process difficult to understand from an operational viewpoint. Modeling and simulation of grinding circuits have been used by past researchers for circuit design and pre-flowsheet optimization in terms of processing capacity, recovery rate, and product size distribution. However, these models were solved under steady approximation and did not provide any information on the system in real time. Hence, they cannot be used for real time optimization and control purposes. Therefore, this research focuses on developing a dynamic simulator for a grinding circuit. The Matlab/Simulink environment was used to program the models of the process units that were interlinked to produce the flowsheet of a grinding circuit of a local gold mine operating in Alaska. The flowsheet was simulated under different operating conditions to understand the behavior of the circuit. The explanation for such changes has also been discussed. The dynamic simulator was then used in designing a neural network based controller for the semi-autogenous mill (SAG). A two-layer non-linear autoregressive (NARX) neural network with feed to the mill as exogenous input was designed using data generated by the simulator for a range of operating conditions. Levenberg-Marquardt (LM) and Bayesian Regularization (BR) training algorithms were used to train the network. Comparison of both algorithms showed LM performed better provided the number of parameters in the network were chosen in a prudent manner. Finally, the implementation of the controller for maintaining SAG mill power to a reference point is discussed.
Experimental and numerical simulation of hydraulic fracturingHydraulic Fracturing (HF) has many applications in different fields such as stimulation of oil and gas reservoirs, in situ stress measurements, stress relief for tunneling projects as well as in underground mining applications such as block caving mining. In the HF process, high pressure fluid is injected into a well to generate fractures in tight rock formations. This technique is particularly suitable for developing hydrocarbon energy resources in tight rock formations such as shale with very low permeability. An experimental setup was designed and developed to simulate the HF process in the laboratory. Cubic plaster specimens were molded and HF experiments were conducted with simulated plaster models. Five laboratory tests were performed on cubic specimens under different stress conditions. Because the uniaxial compressive strength of the plaster was about 1600 psi, in all experiments the applied vertical stress was 1000 psi to avoid breaking the specimens before injection of fluid. The differential horizontal stress varied from 100 to 500 psi. These stress levels are related to shallow formations in a real environment. It was observed that increasing the differential horizontal stress by 100 psi, the minimum pressure required to initiate HF decreases about 100 psi. These results were in agreement by 2D failure criterion of HF. All in all, the small scale HF experiments were conducted successfully in the rock mechanics lab. It was observed that vertical hydraulic fractures would propagate along maximum horizontal stress, which is in agreement with propagation of HF theory. Three-dimensional (3D) numerical models were developed and computer simulations were conducted with ABAQUS, a commercially available finite element analysis (FEA) software. The numerical simulation results compared favorably with those from the laboratory experiments, and verification and analysis were carried out. Since the results obtained from the numerical model were in agreement with the results of experiments and verified the correctness of the model, further investigation was carried out with developed computer models. Several scenarios with different vertical stresses and different levels of horizontal stress were simulated. A statistical software, R, was used to generate a 3D failure criterion for the HF in shallow formations.... It can be stated that in shallow formations, vertical stress has the least effect among stress components on the minimum pressure required to initiate HF.