none

No description available.

Water alternating gas (WAG) injection is a proven technique to enhance oil recovery. It has been successfully implemented in the field since 1957 with recovery increase in the range of 5-10% of oil-initially-in-place (OIIP). In 2004, Herbert L. Stone presented a simultaneous water and gas injection technique. Gas is injected near the bottom of the reservoir and water is injected directly on top at high rates to prevent upward channeling of the gas. Stone's mathematical model indicated the new technique can increase vertical sweep efficiency by 3-4 folds over WAG. In this study, a commercial reservoir simulator was used to predict the performance of Stone's technique and compare it to WAG and other EOR injection strategies. Two sets of relative permeability data were considered. Multiple combinations of total injection rates (water plus gas) and water/gas ratios as well as injection schedules were investigated to find the optimum design parameters for an 80 acre 5-spot pattern unit. Results show that injecting water above gas may result in better oil recovery than WAG injection though not as indicated by Stone. Increase in oil recovery with SSWAG injection is a function of the gas critical saturation. The more gas is trapped in the formation, the higher oil recovery is obtained. This is probably due to the fact that areal sweep efficiency is a more dominant factor in a 5-spot pattern. Periodic shut-off of the water injector has little effect on oil recovery. Water/gas injection ratio optimization may result in a slight increase in oil recovery. SSWAG injection results in a steady injection pressure and less fluctuation in gas production rate compared to WAG injection.

In high-speed digital circuits, in order to utilize the space of printed circuit boards efficiently, the signal via is a heavily used interconnection structure to communicate different signal layers. However, the interconnection discontinuities will result in the degradation of the signal integrity and become a crucial issue for IC designers. To analyze the problems accurately and fast using the hybrid physical equivalent model which combining the transmission line model, slot model, via model, and decoupling capacitor model, etc. Based on the method, we can get a good result of simulation and compute faster than Ansoft HFSS. In addition, by the hybrid physical model method, we simulate and discuss several interesting issues such as resonance in power/ground planes, and the effect of the simultaneous switching noise, we also improve the bad effect of the printed circuit boards existing vias by some ways.

Thesis (doctoral)--Universität St. Gallen, 2001.

The purpose of this thesis was to compare ethinylestradiol (EE2) and nitrogen removal in a conventional membrane bioreactor (C-MBR) and a simultaneous nitrification-denitrification membrane bioreactor (SND-MBR). Two MBRs were operated in parallel for 450 days; various MBR operating parameters, total nitrogen removal, and estrogenic activity removal (EA) were measured. The SND-MBR was able to remove 59% of influent TN with an additional 21% removed via sludge wasting; the C-MBR had a TN removal efficiency of only 31%. The C-MBR and SND-MBR removed 57% and 58% of influent EA, respectively. Biodegradation was the dominant removal mechanism for both reactors with KBIO coefficients of 1.5 ± 0.6 and 1.6 ± 0.4 days-1 for the C-MBR and the SND-MBR, respectively. Adsorption removed approximately 1% of influent EA in each reactor. This indicates that SND was able remove greater amounts of TN with no observable impact on EA reduction and membrane operations.

Due to the depletion of petroleum reserves and environmental concerns, bioethanol has been identified as an alternative fuel to petrol. Bioethanol is a fuel of bio-origin derived from renewable biomass. Starch and sugar containing materials are the primary sources of carbon for bioethanol production. Starch is firstly hydrolysed into simple sugars which are later fermented to bioethanol using Saccharomyces cerevisiae (S. cerevisiae). The fermentation of sugars to bioethanol is however limited by inhibition of S. cerevisiae by the major product of the process, bioethanol. The challenge is thus in keeping the bioethanol concentration at levels which are not harmful to the fermenting organism. Keeping bioethanol concentration low in the broth will provide a suitable environment for yeast to grow and thus increase the overall production. Currently bioethanol producers use high water dilution rates to keep the bioethanol concentrations in the broth low enough so that yeast is not harmed. This excess water has to be removed in the downstream process, which is expensive. The use of excessive amounts of water in the fermentation can be avoided by continual removal of bioethanol from the broth. During this investigation the experimental conditions for the hydrolysis process were determined. A pH of 5.5 was determined as the best pH for Termamyl SC at 95°C with a pH of 5.0 for Spirizyme Fuel at 55°C during the liquefaction and the saccharification step, respectively. During the fermentation process the influence of yeast concentration on bioethanol production was investigated by varying the yeast concentration between 2 g.L-1 and 7 g.L-1. A yeast concentration of 5 g.L-1 produced the highest bioethanol yield of 0.48 g.g-1 after 48 hours of fermentation using S. cerevisiae. Later during the investigation a coupled fermentation/pervaporation system was employed in a batch system for continual removal of bioethanol in the fermentation broth in a process called simultaneous fermentation and separation (SFS). Through the continuous removal of bioethanol from the fermentation broth, the bioethanol concentration in the broth was kept low enough so that it was not harmful to the fermenting organism but the overall fermentation yield was not improved. Pervaporation is a membrane separation process used to separate azeotropic mixtures such as bioethanol and water. It is highly efficient, cost effective and uses less energy than distillation. During the SFS process a bioethanol yield of 0.22 g.g-1 was obtained. The SFS process yield for bioethanol was low compared to 0.45 g.g-1 of the traditional batch fermentation process. The lower overall bioethanol yield obtained in the SFS process could be attributed to only the supernatant being used in the SFS process and not the entire fermentation broth as in the traditional process. The results from this study proved that the SFS process was less efficient compared to the traditional batch fermentation process with respect to the bioethanol yield, but that the fermentation could be carried out without the necessity for additional process water. / Thesis (M.Sc. Engineering Sciences (Chemical and Minerals Engineering))--North-West University, Potchefstroom Campus, 2010.

The purpose of this thesis was to compare ethinylestradiol (EE2) and nitrogen removal in a conventional membrane bioreactor (C-MBR) and a simultaneous nitrification-denitrification membrane bioreactor (SND-MBR). Two MBRs were operated in parallel for 450 days; various MBR operating parameters, total nitrogen removal, and estrogenic activity removal (EA) were measured. The SND-MBR was able to remove 59% of influent TN with an additional 21% removed via sludge wasting; the C-MBR had a TN removal efficiency of only 31%. The C-MBR and SND-MBR removed 57% and 58% of influent EA, respectively. Biodegradation was the dominant removal mechanism for both reactors with KBIO coefficients of 1.5 ± 0.6 and 1.6 ± 0.4 days-1 for the C-MBR and the SND-MBR, respectively. Adsorption removed approximately 1% of influent EA in each reactor. This indicates that SND was able remove greater amounts of TN with no observable impact on EA reduction and membrane operations.

Due to the depletion of petroleum reserves and environmental concerns, bioethanol has been identified as an alternative fuel to petrol. Bioethanol is a fuel of bio-origin derived from renewable biomass. Starch and sugar containing materials are the primary sources of carbon for bioethanol production. Starch is firstly hydrolysed into simple sugars which are later fermented to bioethanol using Saccharomyces cerevisiae (S. cerevisiae). The fermentation of sugars to bioethanol is however limited by inhibition of S. cerevisiae by the major product of the process, bioethanol. The challenge is thus in keeping the bioethanol concentration at levels which are not harmful to the fermenting organism. Keeping bioethanol concentration low in the broth will provide a suitable environment for yeast to grow and thus increase the overall production. Currently bioethanol producers use high water dilution rates to keep the bioethanol concentrations in the broth low enough so that yeast is not harmed. This excess water has to be removed in the downstream process, which is expensive. The use of excessive amounts of water in the fermentation can be avoided by continual removal of bioethanol from the broth. During this investigation the experimental conditions for the hydrolysis process were determined. A pH of 5.5 was determined as the best pH for Termamyl SC at 95°C with a pH of 5.0 for Spirizyme Fuel at 55°C during the liquefaction and the saccharification step, respectively. During the fermentation process the influence of yeast concentration on bioethanol production was investigated by varying the yeast concentration between 2 g.L-1 and 7 g.L-1. A yeast concentration of 5 g.L-1 produced the highest bioethanol yield of 0.48 g.g-1 after 48 hours of fermentation using S. cerevisiae. Later during the investigation a coupled fermentation/pervaporation system was employed in a batch system for continual removal of bioethanol in the fermentation broth in a process called simultaneous fermentation and separation (SFS). Through the continuous removal of bioethanol from the fermentation broth, the bioethanol concentration in the broth was kept low enough so that it was not harmful to the fermenting organism but the overall fermentation yield was not improved. Pervaporation is a membrane separation process used to separate azeotropic mixtures such as bioethanol and water. It is highly efficient, cost effective and uses less energy than distillation. During the SFS process a bioethanol yield of 0.22 g.g-1 was obtained. The SFS process yield for bioethanol was low compared to 0.45 g.g-1 of the traditional batch fermentation process. The lower overall bioethanol yield obtained in the SFS process could be attributed to only the supernatant being used in the SFS process and not the entire fermentation broth as in the traditional process. The results from this study proved that the SFS process was less efficient compared to the traditional batch fermentation process with respect to the bioethanol yield, but that the fermentation could be carried out without the necessity for additional process water. / Thesis (M.Sc. Engineering Sciences (Chemical and Minerals Engineering))--North-West University, Potchefstroom Campus, 2010.

Although the theory of Simultaneous Localization and Map Building (SLAM) is well developed, there are many challenges to overcome when incorporating vision sensors into SLAM systems. Visual sensors have different properties when compared to range finding sensors and therefore require different considerations. Existing vision-based SLAM algorithms extract point landmarks, which are required for SLAM algorithms such as the Kalman filter. Under this restriction, the types of image features that can be used are limited and the full advantages of vision not realized. This thesis examines the theoretical formulation of the SLAM problem and the characteristics of visual information in the SLAM domain. It also examines different representations of uncertainty, features and environments. It identifies the necessity to develop a suitable framework for vision-based SLAM systems and proposes a framework called VisionSLAM, which utilizes an appearance-based landmark representation and topological map structure to model metric relations between landmarks. A set of Haar feature filters are used to extract image structure statistics, which are robust against illumination changes, have good uniqueness property and can be computed in real time. The algorithm is able to resolve and correct false data associations and is robust against random correlation resulting from perceptual aliasing. The algorithm has been tested extensively in a natural outdoor environment.