http://hdl.handle.net/10294/2901 Master's level Theses Sun, 09 Jul 2017 21:39:13 GMT 2017-07-09T21:39:13Z http://hdl.handle.net/10294/7781 Modeling, Simulation and Experimental Validation of a New Rigorous Desorber Model for Low Temperature Catalytic Desorption of CO2-Loaded Amine Solvents over Solid Acid Catalysts Decardi-Nelson, Benjamin Carbon Capture and Storage (CCS) have gained tremendous attention amongst policy makers, researchers and engineers in response to the increasing fears for climate change which is caused by increased amounts of greenhouse gases (GHGs) being emitted into the atmosphere. This is in an effort to decarbonize fossil fuels, especially coal, in order to make them environmentally sustainable while allowing these fuels to contribute to the global energy mix. Due to its maturity, post-combustion capture by chemical absorption, has been the technology focus to capture carbon dioxide (CO2) from combustion flue gases emanating from fossil fuel-based power plants. In this work, a numerical model for catalyst-aided CO2 desorption from CO2-loaded aqueous amines solution has been developed. The model includes a hot water-heater and considers phase separation at the top of the desorption column. The model was validated with experimental data obtained from an integrated post-combustion CO2 capture pilot plant which used 5 M monoethanolamine (MEA), and 5 M MEA mixed with 2 M N-Methyldiethanolamine (MDEA) solutions with two industrial catalysts, namely, HZSM-5 and γ-Al2O3. The model considers the presence of electrolytes and multi-component mass transfer as well as both the physical and chemical contribution of the catalyst in aiding the process. The data obtained from model simulation were in good agreement with the experimental data in terms of CO2 production rates with an absolute average deviation of approximately ±8.9 % for MEA and ±7.7 % for MDEA. The simulation slightly over-predicted the CO2 production rate at the low temperature regime (75 °C) and under-predicted the CO2 production rate at the high temperature regime (95 °C) in both cases. Also, the temperature profiles predicted by the model was in close agreement with the experimental temperature profiles even though it under-predicted them. Based on the simulation as well as the experimental data, HZSM-5 was seen to have greater effect in aiding CO2 desorption than γ-Al2O3 for both solvents. However, the extent of aiding desorption of CO2 from loaded MEA was higher than that of MEA-MDEA. Also, the concentration of CO2 in the gas phase was seen to be quite high and can greatly decrease the driving force for mass transfer. Furthermore, it was interesting to observe that that the presence of maldistribution in the column be shown based on the simulation results. A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering, University of Regina. xvii, 168 p. Thu, 01 Dec 2016 00:00:00 GMT http://hdl.handle.net/10294/7781 2016-12-01T00:00:00Z http://hdl.handle.net/10294/7768 A New Steam Assisted Gravity Drainage Process Utilizing Vertical Wells Shirif, Mohamed Ezeddin A novel process utilizing vertical wells to enhance heavy oil recovery during steam assisted gravity drainage has been developed. In the vertical well steam assisted gravity drainage (VWSAGD) process, the vertical well includes two production strings which are separated by three packers (one dual and two single packers): the short injection string (SIS) is attached to the bottom of the annulus and completed in the top quarter of the perforated formation, while the long production string (LPS) is attached to the bottom of the production tubing and completed in the bottom quarter of the perforated formation. The new process (VWSAGD) requires an initial start-up period (warm-up stage) where the steam is injected into both of the injection strings and production string for a specified period of time of about 14-30 days; then both strings are closed to injection for a specified time period of approximately 7-10 days (soaking period). After the initial warm-up and the soaking period, the long production string is opened for production, and the short injection string is opened to continuous steam injection for the rest of the specified simulation time. A numerical simulation study using the CMG-STAR Simulator was performed to compare the performance of the new VWSAGD process against the conventional steam assisted gravity drainage (HWSAGD) process under the same operating conditions. Two identical reservoir models were simulated for the two processes using 3-Dimensional, black heavy oil model (14°API). Each reservoir type consists of 49x49x20 grid blocks on a 5 Acre model which incorporated a typical heavy oil reservoir rock and fluid properties taken from the SPE case study, stspe001.dat (CMG 2014 release). A sensitivity analysis for both processes was performed for the grid density, soaking time, steam quality, bottom hole producing pressure, steam injection rate, reservoir thickness, reservoir area, and horizontal to vertical permeability anisotropy. More preferable reservoir conditions are those such as high horizontal to vertical permeability ratio, thick reservoir oil zones, as well as improved reservoir recovery for the VWSAGD process. Under unfavorable conditions such as thin reservoir oil zones, an improved reservoir recovery response was limited for the VWSAGD process and could be uneconomical in real field cases. Finally, the simulation results from this study include cumulative recoveries, Steam oil ratios, produced water-oil ratios, pressure and temperature distributions, and production rates. Also, the results from this study have shown that the new VWSAGD process is more favorable than the conventional HWSAGD process. A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering, University of Regina. xxi, 151 p. Tue, 01 Mar 2016 00:00:00 GMT http://hdl.handle.net/10294/7768 2016-03-01T00:00:00Z http://hdl.handle.net/10294/7766 Dynamic Modeling and Vision-Based Mobile-Target Tracking in UAVs Using Wide FOV Cameras Majnoon, Mohsen Control of unmanned aerial vehicles is a very active topic in research with lots of applications ranging from civilian to military. To control a UAV, its attitude is often controlled using gyroscopes, but to control its position, inertial sensors together with GPS are often used. However, obtaining accurate current position is difficult using inertial sensors because of the integration drift. GPS on the other hand is not functional in indoor applications since it cannot connect to GPS satellites. Since vision has been proved to be an inexpensive and consistent source of relative position information, vision-based control is getting more popular in UAVs recently, but then again, using vision in outdoor applications is challenging as the target can move fast and out of the vision sensor field of view. So, in order to keep the target inside the field of view, two algorithms are being developed and tested via simulation in this research. Using pan/tilt/zoom cameras or multi camera systems, the target is guaranteed to stay in vision system field of view and hence, the vision based pose estimation can provide the control system with proper relative position. Two case studies - vision-based mobile-target tracking of a quadrotor using a multi-camera vision sensor and vision-based mobile-target tracking of a tilting rotor aircraft equipped with a zooming camera - are presented in this research to show the applicability of these methods in UAV control. A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Industrial Systems Engineering, University of Regina. xvii, 115 p. Mon, 01 Feb 2016 00:00:00 GMT http://hdl.handle.net/10294/7766 2016-02-01T00:00:00Z http://hdl.handle.net/10294/7765 A Knowledge Acquisition System for Price Change Rules Jahan, Moslema Knowledge acquisition is the process of extracting and organizing knowledge from one source and storing it in some other location such as a knowledge base. Our research developed a new approach to knowledge acquisition concerning motor fuel pricing and implemented it in the Knowledge Acquisition System for Price ChangE Rules (KASPER) software system. Store managers want to understand the pricing strategies at competing stores or brands. The main goal of our research is to provide decision rules with high predictive accuracy on unseen data that may explain why a store or brand made a price change in a speci c category. These decision rules should relate prices at one store to those at other stores or brands in the same city. Our approach is able to generate directional and categorical price change rules. The approach can use brand-based or distance-based store-to-store relations or use brand- to-brand relations. KASPER was applied to data from four cities to generate decision rules from these relations. We tested the decision rules on unseen data and found that most decision rules had high predictive accuracy in cases where the price changes tend to uctuate more. Our approach was more e ective in the two cities where price changes of varied sizes occur than in the two cities where price changes are of consistent, small sizes. We found that high variability of price changes allows the system to match corresponding behaviours more e ectively. A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science, University of Regina. xvi , 126 p. Fri, 01 Jan 2016 00:00:00 GMT http://hdl.handle.net/10294/7765 2016-01-01T00:00:00Z