Solid oxide fuel cells with graded electrodes consisting of multiple composite layers yield generally lower polarization resistances than single layer composite electrodes. Optimization of the performance of solid oxide fuel cells with graded electrode composition and/or microstructure requires an evaluation of both the three phase boundary length per unit volume and the effective diffusion coefficient in order to provide insight into how these properties vary over the design space. A numerical methodology for studying the three phase boundary length and effective diffusivity in composite electrode layers with controlled properties is developed. A three dimensional solid model of a sintered composite electrode is generated for which the mean particle diameter, composition, and total porosity may be specified as independent variables. The total three phase boundary length for the modeled electrode is calculated and tomographic methods are used to estimate the fraction of this length over which the electrochemical reactions can theoretically occur. Furthermore, the open porosity of the modeled electrode is identified and the effective diffusion coefficient is extracted from the solution of the concentration of the diffusing species within the open porosity. Selected example electrode models are used to illustrate the application of the methods developed, and the resulting connected three phase boundary length and diffusion coefficients are compared. A significant result is the need for thickness-specific effective diffusivity to be determined, rather than the general volume averaged property, for electrodes with porosity between the upper and lower percolation thresholds. As the demand for current increases, more of the connected three phase boundaries become active, and therefore a greater fraction of the electrode layer is utilized for a given geometry, resulting in a higher apparent effective diffusivity compared to the same electrode geometry operating at a lower current. The methods developed in this work may be used within a macroscopic electrode performance model to investigate optimal designs for solid oxide fuel cell electrodes with stepwise graded composition and/or microstructure. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate

A graphite foam was developed at Oak Ridge National Laboratory (ORNL) by Dr. James Klett and license was granted to POCO Graphite, Inc. to manufacture and market the product as PocoFoam™. Unlike many processes currently used to manufacture carbon foams, this process yields a highly graphitic structure and overcomes many limitations, such as oxidation stabilization, that are routinely encountered in the development of carbon foam materials. The structure, thermal properties, electrical resistivity, isotropy, and density uniformity of PocoFoam™ were evaluated. These properties and characteristics of PocoFoam™ are compared with natural and synthetic graphite in order to show that, albeit similar, it is unique. Thermal diffusivity and thermal conductivity were derived from Fourier's energy equation. It was determined that PocoFoam™ has the equivalent thermal conductivity of metals routinely used as heat sinks and that thermal diffusivity is as much as four times greater than pure copper and pure aluminum. SEM and XRD results indicate that PocoFoam™ has a high degree of crystalline alignment and near theoretical d spacing that is more typical of natural flake graphite than synthetic graphite. PocoFoam™ is anisotropic, indicating an isotropy factor of 0.5, and may yield higher thermal conductivity at cryogenic temperatures than is observed in polycrystalline graphite.

The purposes of this study were to determine as a function of temperature the thermal diffusivity and/or thermal conductivity of SiC-Mullite and SiC-SiC, and to explain the observed behavior in terms of changes in temperature, microstructure, composition, and/or orientation. Materials used in the SiC-Mullite study consisted of single crystal SiC whiskers (prepared from rice hulls or by the vapor-liquid-solid process) dispersed within a polycrystalline mullite matrix. During measurement of thermal diffusivity, the samples were heated to l500°C and cooled back to room temperature. No hysteresis occurred. However, both thermal diffusivity and conductivity exhibited maximum values at room temperatures, perpendicular to the hot pressing direction, at high volume percentages of SiC whiskers, and when VLS whiskers were employed. The SiC-SiC samples consisted of a crossweave of polycrystalline SiC fibers that were coated with phenolic resin and surrounded by a chemically-vapor-deposited matrix of SiC. The two types of samples examined were prepared with different amounts of resin. The matrices of the high resin samples were found to be dominated by the presence of char. Samples were cycled to 1000, 1400, and l800°C; hysteresis occurred on some of the cycles. Thermal diffusivity was highest parallel to one set of fibers. These results allow the qualitative tailoring of the heat flow properties of these ceramic composites, for particular applications, and set forth limitations on the use of the SiC-SiC composites at high temperatures. / Master of Science

<p> A diffusion cell of the "shearing type" was used to diminish the effect of convection which is always present when two liquid phases are brought into contact with each other in a diffusion cell. Also a special optical arrangement was used to photograph the refractive index distribution of the system. For those systems with refractive index changing linearly with concentration, the concentration profiles were obtained and diffusion coefficients were calculated at different concentrations. </p> <p> This optical method gave only fair reproducibility- the deviation among diffusivities found for systems investigated varying from 3 to 10%- however, it permitted rapid analysis and on this basis is recommended for situations where speed is essential and high accuracy is not required. </p> / Thesis / Master of Engineering (ME)

The Fluorescence Scanning Thermal Microscope (FSTM v3.0), was designed to create an inexpensive, and easily manufactured, device for measuring the diffusivity of samples with microscopic locational precision. This was accomplished by using a Blu-ray device known as a PHR-803T, referred to in this work as a PHR. The optics in the PHR are nearly identical in function to conventional devices used in thermoreflectance microscopy, making the PHR extremely useful to integrate into the FSTM design. The focus of this thesis is the application of the FSTM as a confocal microscope using 3D printed components and various low-cost devices to operate with comparable sampling accuracy to existing confocal microscopes. The electronics and optical filters were then adapted to enable the measurement of thermal waves, particularly by detecting a linear relationship between phase delay and the spacing between heating and sensing lasers, as predicted by previous work on the FSTM.

An experimental study of turbulent air flow in a pipe is reported in this paper. A determination was made of the mean velocity distribution and longitudinal mean turbulent velocity distribution, both in the turbulent core and boundary layer for four different Reynolds numbers from 7300 to 58300. A traversing mechanism was designed in order to measure the turbulence correlations between two points. The variation of the macro scale length, one of the fundamental quantities in recent statistical turbulence theory across the pipe diameter was calculated for Reynolds number equal to 58300, by integrating the correlation curves. The turbulent momentum diffusivity at the center of a pipe was calculated from the correlation study and the dimension less value was found to be 0.111. Ethylene gas was injected into the center of the pipe, and in order to investigate the turbulent mass diffusivity, the concentration distribution curves of ethylene were measured at different test positions downstream from the injection point, for the same series of Reynolds numbers used in the turbulence measurement. A numerical method for calculating the diffusivity was developed. The values of diffusivity obtained. in these experiments show that the assumptions which were used by most of the authors, that of (turbulent mass diffusivity/turbulent momentum diffusivity) has a value between 1.0 to 1.6 is correct. / Thesis / Master of Engineering (ME)

No description available.

CO2 injection has demonstrated significant potential for enhanced oil recovery techniques in unconventional reservoirs, but there exists many challenges in optimizing its operations due to the limited understanding of CO2-oil transport mechanisms in these systems. This dissertation addresses these challenges using molecular dynamics (MD) simulations by investigating the gas and oil transport behaviors and properties within single nanopores under reservoir conditions. The first study examines the exchange dynamics of decane with CO2 and CH4 in a 4 nm-wide calcite nanopore. It is shown that both gases form distinct adsorbed and free molecular populations upon entering the pores, leading to different extraction dynamics. Notably, CO2-decane exchange is initially driven by adsorbed populations, with a transition to free populations later; whereas CH4 -decane exchange follows the opposite pattern. Despite these differences, the transport of both gases apparently follows the same diffusive behavior, with CH4 exhibiting higher effective diffusivities. By calculating self-diffusivities at various relevant compositions, it is found they do not always align well with their effective diffusivities. The second study therefore focuses on Maxwell-Stefan (M-S) diffusivities as a more comprehensive framework to describe the diffusion of CO2-decane mixtures in the first study. It is found that D12 (CO2-decane interactions) remains relatively constant across compositions, unlike bulk mixtures, while D1,s (CO2-wall interactions) increases sharply with CO2 loading. In contrast, D2,s (decane-wall interactions) shows a nonmonotonic trend and, unexpectedly, becomes negative under certain compositions. These phenomena are linked to the strong adsorption of CO2, causing significant density heterogeneity and reduced mobility. Using a multi-task Gaussian process regression model, the M−S diffusivities can be predicted with a relative root mean square error below 10%, significantly reducing computational demand for their practical usage. The third study examines concentration gradient driven diffusio-osmosis of oil-CO2 mixtures within silica and calcite nanopores. Despite higher CO2 enrichment near calcite walls, diffusio-osmotic is only marginally stronger than in silica pores, which is attributed to the variations in interfacial fluid structures and hydrodynamic properties in different pores. Continuum simulations suggest that diffusio-osmosis becomes increasingly significant compared to Poiseuille flow as pore width decreases. The fourth study investigates the oil mixture (C10+C19) recovery from a 4 nm-wide calcite dead-end pore with and without CO2 injection. It was found that CO2 accelerates oil recovery and reduces selectivity for lighter components (e.g., C10) compared to the recovery without CO2. Such improvements are influenced by interfacial and bulk phenomena, including adsorption competition and solubilization effects. Together, these studies provide quantitative insights into CO2-oil transport mechanisms and properties in nanopores. Such insights can help develop better reservoir simulators to guide the optimization of CO2 injection-based enhanced oil recovery in unconventional reservoirs. / Doctor of Philosophy / Recovering oil from unconventional reservoirs—types of underground rock formations that trap oil in extremely tiny pores, much smaller than the thickness of a strand of hair—is one of the biggest challenges in the petroleum industry. The narrow pore size greatly increases the fraction of the oil flow, and many pores are not even connected, which stops oil to flow out on its own, making it much harder to extract from these reservoirs. Injecting gases into the reservoirs, like carbon dioxide (CO2), has become a promising solution. This method not only helps to push the oil out but also allows part of the injected CO2 to be stored underground, reducing its impact on the atmosphere. To make this process work better, we need in depth understandings of how oil and gas move in these tiny rock spaces. Four studies have been conducted to elucidate the transport phenomena in CO2 injection-based enhanced oil recovery. The first study finds that the exchange between trapped oil and CO2 is significantly influenced by how oil and CO2 stick to the walls of these tiny pores. However, it is observed that commonly used characterization methods do not always work well in the prediction of recovery behavior, indicating the need for a better framework to describe this process. To address this problem, we have brought up a new framework in the second study, which considers both the interactions between oil and CO2 and the interactions with the pore wall. Given the high computational costs, a machine learning model is trained with the data collected to make future predictions faster and cheaper. The third study quantifies the strength of a new type of flow. This flow can be comparable in magnitude to pressure difference-driven flow in tiny pores. Lastly, the recovery of an oil mixture composed of light and heavy hydrocarbons is explored. It was discovered that gas injection not only increases the overall oil recovery rate but also decreases the selectivity toward lighter hydrocarbons. These discoveries pave the way for improved models and strategies to optimize the gas injection process to recover oil from these challenging reservoirs, ultimately meeting the energy needs while supporting efforts to reduce atmospheric CO2 levels.

Recent global efforts have focused on developing new lightweight alloys specifically designed for high-pressure die casting (HPDC) processes, aiming to achieve the lightweight of electrified vehicles. HPDC offers a distinct advantage by allowing the production of neat-net-shape automotive components, minimizing the need for further processing. An inherent characteristic of HPDC is its rapid cooling rates, making the understanding and characterization of the thermophysical properties of these newly developed lightweight alloys under high cooling rates a must. These properties have a significant effect on controlling the HPDC process and developing suitable filling and solidification models to simulate the HPDC process intricacies for commercial production adaptation. The thermophysical properties of these alloys are shown to exhibit considerable variability with temperature, particularly under rapid solidification conditions, like in HPDC. Hence, an essential step in developing such alloys is to thoroughly investigate the variation of their thermophysical properties with temperature under high cooling rates. To fulfill such a need, an experimental setup has been developed to allow the solidification of molten metal samples under varying cooling rates using a set of impinging water jets. An inverse heat transfer algorithm has been developed to estimate the thermal conductivity and thermal diffusivity as a function of the temperature of the solidifying samples under high cooling rates. To validate the accuracy of the inverse heat transfer algorithm and the experimental methodology, a set of experiments has been carried out using pure Tin, which is a well-characterized material. Its thermal diffusivity and thermal conductivity are readily available in the literature. The estimated thermal diffusivity and thermal conductivity of Tin have been compared with the published data. The estimated thermal diffusivity and conductivity of the solid phase were in good agreement with the published values. A maximum deviation ranging from +10.1% to -3.47% was observed in the estimated thermal diffusivity. The maximum deviation in the estimated thermal conductivity was between +7.8% and -13.6%. Higher deviations have been observed in the estimated thermal diffusivity and conductivity of the liquid phase with deviations in the range of +33.71% to -4.86% and +0.76% to 26.53%, respectively. The higher deviations observed for the liquid phase might be attributed due to the natural convection that developed in the tested liquid sample. The effect of natural convection was examined using a set of numerical simulations that confirmed the existence of a convection-induced movement within the liquid phase. A sensitivity analysis was carried out to examine the impact of the accuracy of thermocouple positions and the effect of temperature sensing accuracy on the estimated thermal properties. / Thesis / Master of Applied Science (MASc) / An inverse heat transfer algorithm along with an experimental setup has been developed to estimate the temperature-dependant thermophysical properties during solidification of metallic alloys under high cooling rates. To verify the accuracy of the developed algorithm and the experimental setup the estimated thermal conductivity and diffusivity of pure Tin have been compared with data available in the literature. The results showed reasonable agreement.

The purpose of this investigation was to develop an apparatus to measure the thermal conductivity of polymer melts, and to use the apparatus to measure the thermal conductivity of selected melts as a function of melt temperature. The steady-state, coaxial cylinder method with guard heaters was used and the annular gap was 0.075 inch. The polymer was melted in a cylindrical melt chamber, then metered to the thermal conductivity measuring apparatus. Cartridge heaters provided heat input and temperature measurements were made with calibrated, differential, iron-constantan thermocouples. The thermal conductivity of polyethylene, polystyrene and nylon melts tested increased with increased temperature. The thermal conductivity of the polypropylene sample was temperature independent. Complexity of molecular structure lowered melt thermal conductivity. Radiation losses were accounted for and convection was determined to be absent. The results were shown to be within a 3 percent experimental measurement error. Meaningful confidence limits cannot be calculated because of the limited number of data points. / Master of Science