Design and Preliminary Results of an Atmospheric-Pressure Model Gas Turbine Combustor Utilizing Varying CO2 Doping Concentration in CH4 to Emulate Biogas Combustion

Utilization of biogas can provide a source of renewable energy in both heat and power generation. Combustion of biogas in land-based gas turbines for power generation is a promising approach to reducing greenhouse gases and US dependence on foreign-source fossil fuels. Biogas is a byproduct from the decomposition of organic matter and consists primarily of CH4 and large amounts of CO2. The focus of this research was to design a combustion device and investigate the effects of increasing levels of CO2 addition to the combustion of pure CH4 with air. Using an atmospheric-pressure, swirl-stabilized dump combustor, emissions data and flame stability limitations were measured and analyzed. In particular, CO2, CO, and NOx emissions were the main focus of the combustion products. Additionally, the occurrence of lean blowout and combustion pressure oscillations, which impose significant limitations in operation ranges for actual gas turbines, was observed. Preliminary kinetic and equilibrium modeling was performed using Cantera and CEA for the CH4/CO2/Air combustion systems to analyze the effect of CO2 upon adiabatic flame temperature and emission levels. The numerical and experimental results show similar dependence of emissions on equivalence ratio, CO2 addition, inlet air temperature, and combustor residence time. (C) 2014 Elsevier Ltd. All rights reserved.

Chemical Compatibility of Model Soil-Bentonite Backfill Containing Multiswellable Bentonite

The objective of this study was to evaluate the chemical compatibility of model soil-bentonite backfills containing multiswellable bentonite (MSB) relative to that of similar backfills containing untreated sodium (Na) bentonite or a commercially available, contaminant resistant bentonite (SW101). Flexible-wall tests were conducted on consolidated backfill specimens (effective stress =34.5 kPa) containing clean sand and 4.5–5.7% bentonite (by dry weight) using tap water and calcium chloride (CaCl2) solutions (10–1,000 mM) as the permeant liquids. Final values of hydraulic conductivity (k) and intrinsic permeability (K) to the CaCl2 solutions were determined after achieving both short-term termination criteria as defined by ASTM D5084 and long-term termination criteria for chemical equilibrium between the influent and effluent. Specimens containing MSB exhibited the smallest increases in k and K upon permeation with a given CaCl2 solution relative to specimens containing untreated Na bentonite or SW101. However, none of the specimens exhibited more than a five-fold increase in k or K, regardless of CaCl2 concentration or bentonite type. Final k values for specimens permeated with a given CaCl2 solution after permeation with tap water were similar to those for specimens of the same backfill permeated with only the CaCl2 solution, indicating that the order of permeation had no significant effect on k. Also, final k values for all specimens were within a factor of two of the k measured after achieving the ASTM D5084 termination criteria. Thus, use of only the ASTM D5084 criteria would have been sufficient to obtain reasonable estimates of long-term hydraulic conductivity for the specimens in this study.

Assessing the Validity of Brain Glucose Concentration Measurement Using Microdialysis

Brain functions, such as learning, orchestrating locomotion, memory recall, and processing information, all require glucose as a source of energy. During these functions, the glucose concentration decreases as the glucose is being consumed by brain cells. By measuring this drop in concentration, it is possible to determine which parts of the brain are used during specific functions and consequently, how much energy the brain requires to complete the function. One way to measure in vivo brain glucose levels is with a microdialysis probe. The drawback of this analytical procedure, as with many steadystate fluid flow systems, is that the probe fluid will not reach equilibrium with the brain fluid. Therefore, brain concentration is inferred by taking samples at multiple inlet glucose concentrations and finding a point of convergence. The goal of this thesis is to create a three-dimensional, time-dependent, finite element representation of the brainprobe system in COMSOL 4.2 that describes the diffusion and convection of glucose. Once validated with experimental results, this model can then be used to test parameters that experiments cannot access. When simulations were run using published values for physical constants (i.e. diffusivities, density and viscosity), the resulting glucose model concentrations were within the error of the experimental data. This verifies that the model is an accurate representation of the physical system. In addition to accurately describing the experimental brain-probe system, the model I created is able to show the validity of zero-net-flux for a given experiment. A useful discovery is that the slope of the zero-net-flux line is dependent on perfusate flow rate and diffusion coefficients, but it is independent of brain glucose concentrations. The model was simplified with the realization that the perfusate is at thermal equilibrium with the brain throughout the active region of the probe. This allowed for the assumption that all model parameters are temperature independent. The time to steady-state for the probe is approximately one minute. However, the signal degrades in the exit tubing due to Taylor dispersion, on the order of two minutes for two meters of tubing. Given an analytical instrument requiring a five μL aliquot, the smallest brain process measurable for this system is 13 minutes.