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The importance of precise values for the parameters used in heat and mass transfer models has been demonstrated by many research studies. Thermal conductivity values used in previous models are usually empirical and fluctuate. Theoretical analysis and estimations of wood thermal conductivities in the radial and tangential directions were conducted with the geometric models built up from the macro- and micro-structure observations. Theoretically, thermal conductivity in the radial direction is about 1.5 to 2.5 times of the tangential direction for softwood species with moisture content (MC) below Fiber Saturation Point (FSP). When MC is over the FSP, tangential radial thermal conductivity both increase dramatically and are linear function of MC. The two thermal conductivity values are close with a ratio of near one estimated by the model for MC above the FPS. In hardwood species, radial thermal conductivity estimated by the model is 1.5 times of the tangential thermal conductivity. Validation tests for model estimations of thermal conductivities in the radial and tangential directions for three wood species showed the reliability of the geometric models developed in this project. Correlations between the wood thermal conductivity and structure parameters, such as latewood percentage and cell wall percentage, were examined. Linear relationships for the thermal conductivity and average temperature in wood were established in both radial and tangential directions of three wood species. A two-dimensional transient heat conduction model was developed utilizing thermal conductivity values derived from geometric models. The anisotropic material property affect on heat transport in radial and tangential directions was discussed using an assumed situation. The simulation run showed slightly faster heat flow in the radial direction than in the tangential direction due to higher thermal conductivity in the radial direction. Validation tests on practical wood blocks showed the 2D model with the use of theoretical thermal conductivity values can predict good temperature distribution in wood during the heating process. However, in the practical wood samples with curved rings on the cross section, no significant difference was found in the two transverse directions. Mathematica software was introduced in this study for the intense and complicated math calculations and model programming. Mathematica was found to be a powerful technique for solving sophisticated math problems. It had abundant and flexible plotting options for providing optimized presentations for the results. These advantages make Mathematica popular for engineering modeling research. / Ph. D.

yes / The coupling between natural convection and conduction within rectangular enclosure was investigated numerically. Three separate heat sources flush mounted on a vertical wall and an isoflux condition was applied at the back of heat sources. Continuity, momentum and energy conservation equations were solved by using control volume formulation and the coupling of velocity and pressure was treated by using the “SIMPLE” algorithm. The modified Rayleigh number and the substrate/fluid thermal conductivity ratio were used in the range 𝑹𝒂𝒍𝒛∗=𝟏𝟎^𝟒−𝟏𝟎^𝟕 and 𝑹𝒔=𝟏𝟎−𝟏𝟎𝟎𝟎 respectively. The investigation was extended to compare results of FC-77 with Air and also for high values of 𝑹𝒔>𝟏𝟎𝟎𝟎. The results illustrated that, when the modified Rayleigh number increases, dimensionless heat flux and local Nusselt number increases for both fluids. Opposite behaviour for the thermal spreading in the substrate and the dimensionless temperature 𝜽, they were decreased when 𝑹𝒂𝒍𝒛∗ is increased. Also with increasing the substrate/fluid thermal conductivity ratio for a given value of the modified Rayleigh number the thermal spreading in the substrate increased which is the reason of the decrease in the maximum temperature value. The present study concluded that, for high values of 𝑹𝒔>𝟏𝟓𝟎𝟎, the effect of the substrate is negligible.

Gaseous phase is a critical state of matter around us. It mediates between the solid crust on earth and inter-stellar vacuum. Apart from the atmosphere surrounding us where compounds are present, natively, in a gaseous phase, they are also trapped within soil and dissolved in oceanic water. Further, those that are less volatile do enter the gaseous phase at high temperatures. It is this gaseous phase that we inhale every second. It is thus critical that we possess the tools to analyze a mixture of gaseous compounds. One such method is to separate the components in time and then identify, primarily based on the retention times, also known as gas chromatography. This research focuses on the development of gas detectors and their integration, in different styles, primarily for gas chromatography. Utilizing fabrication techniques used in semiconductor industry and exploiting scaling laws we investigate the ability to improve on conventional gas separation and identification techniques. Specifically, we have provided a new spin to the age-old thermal conductivity detector enabling its monolithic integration with a separation column. A reference-less, two-port integration architecture and a one-of-its-kind released resistor on glass are some of its salient features. The operation of this integrated device with a preconcentrator and in a matrix array was investigated. The more unique contribution of this research lies in the innovative discharge ionization detector. An ultra-low power, sensitive, easy to fabricate detector, it requires more investigation for a thorough understanding and will likely mature to replace the thermal conductivity detector, as the detector of choice for universal detection, in time to come. / Ph. D.

Carbon nanotubes (CNTs) and graphite nanoplatelets (GNPs) are carrying great promise as two important constituents of future multifunctional materials. Originating from their minimal defect confined nanostructure, exceptional thermal and electrical properties have been reported for these two allotropic forms of carbon. However, a brief survey of the literature reveals the fact that the incorporation of these species into a polymer matrix enhances its effective properties usually not to the degree predicted by the composite\\textquoteright s upper bound rule. To exploit their full potential, a proper understanding of the physical laws characterizing their behavior is an essential step. With emphasis on the electrical and thermal properties, the following study is an attempt to provide more realistic physical and computational models for studying the transport properties of these nanomaterials. Originated from quantum confinement effects, electron tunneling is believed to be an important phenomenon in determining the electrical properties of nanocomposites comprising CNTs and GNPs. To assess its importance, in this dissertation this phenomenon is incorporated into simulations by utilizing tools from statistical physics. A qualitative parametric study was carried out to demonstrate its dominating importance. Furthermore, a model is adopted from the literature and extended to quantify the electrical conductivity of these nanocomposite. To establish its validity, the model predictions were compared with relevant published findings in the literature. The applicability of the proposed model is confirmed for both CNTs and GNPs. To predict the thermal properties, a statistical continuum based model, originally developed for two-phase composites, is adopted and extended to describe multiphase nanocomposites with high contrast between the transport properties of the constituents. The adopted model is a third order strong-contrast expansion which directly links the thermal properties of the composite to the thermal properties of its constituents by considering the microstructural effects. In this approach, a specimen of the composite is assumed to be confined into a reference medium with known properties subjected to a temperature field in the infinity to predict its effective thermal properties. It was noticed that such approach is highly sensitive to the properties of the reference medium. To overcome this shortcoming, a technique to properly select the reference medium properties was developed. For verification purpose the proposed model predictions were compared with the corresponding finite element calculations for nanocomposites comprising cylindrical and disk-shaped nanoparticles. To shed more light on some conflicting reports about the performance of the hybrid CNT/GNP/polymer nanocomposites, an experimental study was conducted to study a hybrid ternary system. CNT/polymer, GNP/polymer and CNT/GNP/polymer nanocomposite specimens were processed and tested to evaluate their thermal and electrical conductivities. It was observed that the hybrid CNT/GNP/polymer composites outperform polymer composites loaded solely with CNTs or GNPs. Finally, the experimental findings were utilized to serve as basis to validate the models developed in this dissertation. The experimental study was utilized to reduce the modeling uncertainties and the computational predictions of the proposed models were compared with the experimental measurements. Acceptable agreements between the model predictions and experimental data were observed and explained in light of the experimental observations. The work proposed herein will enable significant advancement in understanding the physical phenomena behind the enhanced electrical and thermal conductivities of polymer nanocomposites specifically CNT/GNP/polymer nanocomposites. The dissertation results offer means to tune-up the electrical and thermal properties of the polymer nanocomposite materials to further enhance their performance. / Ph. D.

One emerging application of additive manufacturing is building parts with embedded electronics, but the thermal management of these assemblies is a potential issue. Electrical components have efficiency losses, and a significant portion of that lost energy is converted into heat. Embedding electronics in PolyJet parts is of particular interest since material jetting additive manufacturing has the ability to deposit multiple, functionally graded materials on a pixel by pixel basis. Although there is existing literature on other PolyJet material properties, there is limited research on their thermal characterization. The goal of this work is to determine the thermal conductivities of select PolyJet photopolymers (VeroWhitePlus, TangoBlackPlus, and Grey60) by using the heat flow meter method. The resulting thermal conductivities are then applied in finite element analysis (FEA) simulations to model the thermal distribution of heated PolyJet parts. Two FEA models of one-dimensional conduction in PolyJet parts are defined and compared to a corresponding physical model to verify the thermal conductivity measurements; one simulation expresses thermal conductivity as a function of temperature and the other uses an average value of thermal conductivity. The thermal conductivities were determined for a range of temperatures, and the average values were 0.2376 W/(m•K), 0.2307 W/(m•K), and 0.2272 W/(m•K) for VeroWhitePlus, TangoBlackPlus, and Grey60, respectively. When applying the thermal conductivity results to an FEA model, it was concluded that defining thermal conductivity as a function of temperature (as opposed to a constant value), reduced the average error in the predicted temperatures by less than 1%. / Master of Science

The ability of uniquely functional thermoelectric materials to convert waste heat directly into electricity is critical considering the global energy economy. Profitable, energy-efficient thermoelectrics possess thermoelectric figures of merit ZT ≥ 1. We examined the effect of metal nanoparticle – oxide film interfaces on the thermal conductivity κ and Seebeck coefficient α in bilayer and multilayer thin film oxide thermoelectrics in an effort to improve the dimensionless figure of merit ZT. Since a thermoelectric's figure of merit ZT is inversely proportional to κ and directly proportional to α, reducing κ and increasing α are key strategies to optimize ZT. We aim to reduce κ by phonon scattering due to the inclusion of metal nanoparticles in the bulk of thermoelectric thin films deposited by Pulsed Laser Deposition. XRD, AFM, XPS, and TEM analyses were carried out for structural and compositional characterization. The electrical conductivities of the samples were measured by a four-point probe apparatus. The Seebeck coefficients were measured in-plane, varying the temperature from 100K to 310K. The thermal conductivities were measured at room temperature using Time Domain Thermoreflectance. / Master of Science

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.

Electric motors for vehicle applications are required to have high efficiency and small size and weight. Accurately modeling the thermal properties of an electric motor is critical to properly sizing the motor. Improving the cooling of the motor windings allows for a more efficient and power-dense motor. There are a variety of methods for predicting motor temperatures, however this paper discusses the advantages and accuracy of using a nodal lumped thermal model. Both commercially available and proprietary motor thermal modeling software are evaluated and compared. Thermal improvements based on the model in both contact interfaces and winding encapsulant are evaluated, showing motor improvements in the ability to handle heat losses of approximately forty percent greater than the baseline, resulting in either higher power or lower motor temperatures for the same package size. / Master of Science