Temperature rise due to Joule heating of on-chip interconnects can severely affect performance and reliability of next generation microprocessors. Thermal predictions become difficult due to large number of features, and the impact of electron size effects on electrical and thermal transport. It is thus necessary to develop efficient numerical approaches, and accurate metal and dielectric thermal characterization techniques. In this research, analytical, numerical, and experimental techniques were developed to enable accurate and efficient predictions of interconnect temperature rise. A finite element based compact thermal model was developed to obtain temperature rise with fewer elements and acceptable accuracy. Temperature drop across the interconnect cross-section was ignored. The compact model performed better than standard finite element model in two and three-dimensional case studies, and the predictions for a real world structure agreed closely with experimentally measured temperature rise. A numerical solution was developed for electron transport based on the Boltzmann Transport Equation (BTE). This deterministic technique, based on the path integral solution of BTE within the relaxation time approximation, free electron model, and linear response, was applied to a constriction in a finite size thin metallic film. A correlation for effective conductance was obtained for different constriction sizes. The Atomic Force Microscope (AFM) based Scanning Joule Expansion Microscopy (SJEM) was used to develop a new technique to measure thermal conductivity of thin metallic films in the size effect regime. This technique does not require suspended metal structures, and thus preserves the original electron interface scattering characteristics. The thermal conductivities of 43 nm and 131 nm gold films were extracted to be 82 W/mK and 162 W/mK respectively. These measurements were close to Wiedemann-Franz Law predictions and are significantly smaller than the bulk value of 318 W/mK due to electron size effects. The technique can potentially be applied to interconnects in the sub-100 nm regime. A semi-analytical solution for the 3-omega method was derived to account for thermal conduction within the metallic heater. It is shown that significant errors can result when the previous solution is applied for anisotropic thermal conductivity measurements.

Conduction based compact thermal modeling of DC/DC converters, which are electronic components commonly used in military applications, are investigated. Three carefully designed numerical case studies are carried out at component, board and system levels using ICEPAK software. Experiments are conducted to gather temperature data that can be used to study compact thermal models (CTMs) with different levels of simplification. In the first (component level) problem a series of conduction based CTMs are generated and used to study the thermal behavior of a Thin-Shrink Small Outline Package (TSSOP) type DC/DC converter under free convection conditions. In the second (board level) case study, CTM alternatives are produced and investigated for module type DC/DC converter components using a printed circuit board (PCB) of an electro-optic system. In the last case study, performance of the CTM alternatives generated for the first case are assessed at the system level using them on a PCB placed inside a realistic avionic box. v Detailed comparison of accuracy of simulations obtained using CTMs with various levels of simplification is made based on experimentally obtained temperature data. Effects of grid size and quality, choice of turbulence modeling and space discretization schemes on numerical solutions are discussed in detail. It is seen that simulations provide results that are in agreement with measurements when appropriate CTMs are used. It is also showed that remarkable reductions in modeling and simulation times can be achieved by the use of CTMs, especially in system level analysis.

This study has two main objectives: The performance evaluation of existing microchannel heat sinks using a CFD model, and the dimensional optimization of various heat sinks by minimizing the total thermal resistance. For the analyses, the geometric modeling is performed using the software GAMBIT while the thermal analysis is performed with FLUENT. The developed model compares very well with those available in the literature. Eight different metal-polymer microchannel heat sinks are analyzed using the model to find out how much heat could be provided to the systems while keeping the substrate temperatures below 85&deg / C under a constant pumping power requirement. Taking the objective function as the total thermal resistance, the optimum geometries have been obtained for the mentioned metal-polymer heat sinks as well as more conventional silicon ones. The results of the optimization code agreed very well with available ones in the literature. In the optimization study, the Intel Core i7-900 Desktop Processor Extreme Edition Series is considered as a reference processor which is reported to dissipate 130 W of heat and to have chip core dimensions of 1.891 cm &times / 1.44 cm. A dimensional optimization study has been performed for various copper and silicon microchannel heat sinks to cool down this processor. To the best of the author&rsquo / s knowledge, this study contributes to the literature in that, as opposed to the available analytical microchannel optimization studies considering constant thermophysical properties at the fluid inlet temperature, the properties are evaluated at the area weighted average of the fluid inlet and iteratively calculated outlet temperatures. Moreover, the effects of the thermal and hydrodynamic entrance regions on heat transfer and flow are also investigated.

Historical, well developed, procedures for RF design have minimal emphasis on exploring the third dimension due to the difficulty of fabrication. Recent material advancements applicable to 3D printing have brought about low-loss thermoplastics with excellent mechanical properties. Research into depositing conductive inks onto arbitrary 3D shapes has achieved resolutions better than 50 μm with conductivity values approaching that of copper cladding. The advancements in additive manufacturing have improved reliability and repeatability of three dimensional designs while decreasing fabrication time. With this design approach other considerations, such as stability and strength, can be concentrated on during the structure design to realize new shapes. The next step in the future of RF research will encompass designing and further understanding the benefits and consequences of using all three dimensions. This could include meandering an antenna element around other electronic components to make the overall package size smaller or integrating an antenna array into a wing. The design and analysis of the periodic spiral antenna (PSA) takes a look at a specific case of full volume utilization. In this application meandering in the z-dimension allowed the design to become smaller and more efficient than what is achievable with planar methods. This thesis will go into detail on the characterization of the periodic spiral antenna. To exemplify the benefits of meandering in the z-dimension a loop antenna is presented and benchmarked against other miniaturization techniques. Measured results of two different PSA models are presented and remarks on improving fabrication are given. When an antenna is used as a transmitter incident power will cause thermal generation so a study was conducted to understand how material properties can govern the amount of heat generated.

Lithium ion batteries have become one of the most popular types of battery in consumer electronics as well as aerospace and automotive applications. The efficient use of Li-ion batteries in automotive applications requires well designed battery management systems. Low order Li-ion battery models that are fast and accurate are key to well- designed BMS. The control oriented low order physics based model developed previously cannot predict the temperature and predicts inaccurate voltage dynamics. This thesis focuses on two things: (1) the development of a thermal component to the isothermal model and (2) the development of a hybrid neural net and physics based battery model that corrects the output of the physics based model. A simple first law based thermal component to predict the temperature model is implemented. The thermal model offers a reasonable approximation of the temperature dynamics of the battery discharge over a wide operating range, for both a well-ventilated battery as well as an insulated battery. The model gives an accurate prediction of temperature at higher SOC, but the accuracy drops sharply at lower SOCs. This possibly is due to a local heat generation term that dominates heat generation at lower SOCs. A neural net based modeling approach is used to compensate for the lack of knowledge of material parameters of the battery cell in the existing physics based model. This model implements a neural net that corrects the voltage output of the model and adds a temperature prediction sub-network. Given the knowledge of the physics of the battery, sparse neural nets are used. Multiple types of standalone neural nets as well as hybrid neural net and physics based battery models are developed and tested to determine the appropriate configuration for optimal performance. The prediction of the neural nets in ventilated, insulated and stressed conditions was compared to the actual outputs of the batteries. The modeling approach presented here is able to accurately predict voltage output of the battery for multiple current profiles. The temperature prediction of the neural nets in the case of the ventilated batteries was harder to predict since the environment of the battery was not controlled. The temperature predictions in the insulated cases were quite accurate. The neural nets are trained, tested and validated using test data from a 4.4Ah Boston Power lithium ion battery cell. / text

In serial manufacturing processes, localized energy sources (e.g. plasma cutters, arc welders or water jets) induce material geometry transformations that yield a desired product. Simple parameter control of these energy sources does not necessarily ensure an optimal or successful part because of disturbances in the manufacturing process (material and temperature variations, etc). Currently, control in manufacturing is based on statistical process control where large databases for the manufacturing of a fixed process are available and have been compiled over several manufacturing runs. In the absence of a statistical database, and with the increased need for improved monitoring and throughput, there is need for active process control in manufacturing. In this work, Gas Metal Arc Braze-Welding (GMABW) will serve as a test-bed for the implementation of model predictive control (MPC) for a serial manufacturing process. This dissertation investigates the integration of real time modeling of the temperature field with control algorithms to control the evolving temperature field in the ix braze-welded base metal. Fundamental problems involving MPC that are addressed are modeling techniques to calculate temperature fields with reduced computational requirements and control algorithms that utilize the thermal models directly to inform the controller. The dissertation first outlines and compares analytical and computational thermal models and comparison with experimental data are obtained. A thermal model based on a metamodeling approach is used as the plant model for a classical control system and control parameters are found. Various techniques for dealing with signal noise encountered during experimentation are investigated. A proportional controller is implemented in the experimental setup that applies feedback control of the braze –welding process using thermal signals. A novel approach to MPC is explored by using a metamodel as the plant model for the braze-welding process and having the temperature trajectory dictated by the metamodel in the steady state region of the weld. Lastly, future work and extensions of this research are outlined. / text

Infrared (IR) imaging is a key technology in a variety of military and civilian applications, especially for night vision and remote sensing. Compared with cryogenically cooled IR sensors, uncooled infrared imaging devices have the advantages of being low cost, light weight, and superior reliability. The electro-thermal analysis of a microbolometer pixel is critical to determine both device performance and reliability. To date, most microbolometer analysis research has focused on performance optimization and computation of thermal conductance directly from the geometry. However, modeling of the thermal distribution across the microbolometer pixel is critical for the comprehensive analysis of system performance and reliability. Therefore, this thesis investigates the electro-thermo-mechanical characteristics of a microbolometer pixel considering the effects of joule heating and incoming IR energy. The contributions of the present research include the electro-thermal models for microbolometer and methods of validating thermal distribution using experimental results. The electro-thermal models explain the effect of microbolometer material properties and geometry on device performance and reliability. The research also contributes methods of estimating the thermal conductivity of microbolometer, which take into account different heat transfer mechanisms, including radiation and convection. Previous approaches for estimating the thermal conductance of uncooled microbolometer consider heat conduction via legs from the geometry of the pixel structure and material properties [2]. This approach assumes linear temperature distribution in the pixel legs structure. It also leaves out the various electro-thermal effects existing for multilayer structures. In the present research, a different approach is used to develop the thermal conductance of microbolometer pixel structure. The temperature distribution in the pixel is computed from an electro-thermal model. Then, the average temperature in the pixel microplate and the total heat energy generated by joule heating is utilized to compute the thermal conductance of the structure. The thesis discusses electro-thermal and thermo-mechanical modeling, simulation and testing of Polysilicon Multi-User MEMS Process (PolyMUMPs®) test devices as the groundwork for the investigation of microbolometer performance and reliability in space applications. An electro-thermal analytical and numerical model was developed to predict the temperature distribution across the microbolometer pixel by solving the second order differential heat equation. To provide a qualitative insight of the effect of different parameters in the thermal distribution, including material properties and device geometry, first an explicit formulation for the solution of the electro-thermal coupling is obtained using the analytical method. In addition, the electro-thermal model, which accounts for the effect of IR energy and radiation heat transfer, spreading resistance and transient conditions, was studied using numerical methods. In addition, an analytical model has been developed to compute the IR absorption coefficient of a Thin Single Stage (TSS) microbolometer pixel. The simulation result of this model was used to compute absorbed IR energy for the numerical model. Subsequently, the temperature distribution calculated from the analytical model is used to obtain the deflections that the structure undergoes, which will be fundamental for the reliability analysis of the device. Finite element analysis (FEA) has been simulated for the selected device using commercial software, ANSYS® multiphysics. Finite element simulation shows that the electro-thermal models predict the temperature distribution across a microbolometer pixel at steady-state conditions within 2.3% difference from the analytical model. The analytical and numerical models are also simulated and results for a temperature distribution within 1.6% difference. In addition, to validate the analytical and numerical electro-thermal and thermo-mechanical models, a PolyMUMPs® test device has been used. The test results showed a close agreement with the FEM simulation deflection of the test device.

No description available.

Study of pseudotachylytes (PT) (frictional melts) can provide information on the physical and chemical conditions at the earthquake source. This study examines the influence of asperityscale fault dynamics on asperity temperature distribution, and therefore, the potential for frictional melting to occur. Frictional melting occurs adiabatically, and is initiated between opposing asperity tips during fault slip. Our model considers 2-D heat conduction in elastic, isotropic, hemispherical asperities, with temperature dependent thermal properties. The only heat source is a point heat flux pulse at the asperity tip. The non-linear problem was solved using the -form of Newton-Kantorovich procedure coupled with the -form of Douglas-Gunn two level finite difference scheme, while the linear problem required only the latter method. Results for quartz and feldspar indicate that peak temperatures can reach melting point values for typical asperity sizes (1-100 mm), provided that contact (frictional) shear stress is sufficiently high. For any asperity size, the temperature distribution peak becomes insignificant by the time it reaches the asperity center. These results imply that much of asperity scale melting is highly localized, which may explain why most PT veins in the field are usually very thin. However, in some cases, successive asperity encounters may generate temperature increases large enough to trigger the massive melting inferred from typical PT exposures. Significant differences were observed between the results of the linear and nonlinear models.

Thermal modeling is an important aspect of electric motor design. Numerous techniques exist to predict the temperatures in a motor, and they can be incorporated in the design of a thermal model for a new type of electric motor. This work discusses the available modeling techniques and determines which methods are applicable for medium-sized motors with either natural convection or forced convective cooling over irregular geometry. A time-dependant thermal model, with thermal transport parameters based upon geometric and simplified air flow information, is developed based on a discrete lumped parameter model with several modifications to improve accuracy. The model was completed with the aid of nine experiments, and the result is a thermal model that exhibits an absolute error of less than 6.1??C for the nine test runs at three different currents between 8.4 A rms and 28.2 A rms and three cooling levels, natural, 10.7 CFM and 24.4 CFM.