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No description available.

Thermal systems often feature composite regions that are mechanically mated. In general, there exists a significant temperature drop across the interface between such regions which may be composed of similar or different materials. The parameter characterizing this temperature drop is the thermal contact resistance, which is defined as the ratio of the temperature drop to the heat flux normal to the interface. The thermal contact resistance is due to roughness effects between mating surfaces which cause certain regions of the mating surfaces to loose contact thereby creating gaps. In these gap regions, the principal modes of heat transfer are conduction across the contacting regions of the interface, conduction or natural convection in the fluid filling the gap regions of the interface, and radiation across the gap surfaces. Moreover, the contact resistance is a function of contact pressure as this can significantly alter the topology of the contact region. The thermal contact resistance is a phenomenologically complex function and can significantly alter prediction of thermal models of complex multi-component structures. Accurate estimates of thermal contact resistances are important in engineering calculations and find application in thermal analysis ranging from relatively simple layered and composite materials to more complex biomaterials. There have been many studies devoted to the theoretical predictions of thermal contact resistance and although general theories have been somewhat successful in predicting thermal contact resistances, most reliable results have been obtained experimentally. This is due to the fact that the nature of thermal contact resistance is quite complex and depends on many parameters including types of mating materials, surface characteristics of the interfacial region such as roughness and hardness, and contact pressure distribution. In experiments, temperatures are measured at a certain number of locations, usually close to the contact surface, and these measurements are used as inputs to a parameter estimation procedure to arrive at the sought-after thermal contact resistance. Most studies seek a single value for the contact resistance, while the resistance may in fact also vary spatially. In this thesis, an inverse problem (IP) is formulated to estimate the spatial variation of the thermal contact resistance along an interface in a two-dimensional configuration. Temperatures measured at discrete locations using embedded sensors appropriately placed in proximity to the interface provide the additional information required to solve the inverse problem. A superposition method serves to determine sensitivity coefficients and provides guidance in the location of the measuring points. Temperature measurements are then used to define a regularized quadratic functional that is minimized to yield the contact resistance between the two mating surfaces. A boundary element method analysis (BEM) provides the temperature field under current estimates of the contact resistance in the solution of the inverse problem when the geometry of interest is not regular, while an analytical solution can be used for regular geometries. Minimization of the IP functional is carried out by the Levenberg-Marquadt method or by a Genetic Algorithm depending on the problem under consideration. The L-curve method of Hansen is used to choose the optimal regularization parameter. A series of numerical examples are provided to demonstrate and validate the approach.

The goal of this research is to show the feasibility of detecting density variations in green-state powder metallurgy (P/M) compacts from surface voltage measurements. By monitoring a steady electric current flow through the sample and recording the voltages over the surface, valu-able information is gathered leading to the prediction of the structural health of the compacts. Unlike prior research that concentrated on the detection of surface-breaking and subsurface de-fects, the results presented in this thesis target the density prediction throughout the volume of the sample. The detection of density variations is achieved by establishing a correlation between the conductivity and their respective density. The data obtained from the surface measurements is used as part of an inversion algorithm, calculating the conductivity distribution, and subse-quently the density within the compact. In a first step, the relationship between conductivity and density of green-state P/M com-pacts was investigated. Tests were conducted for a number of parts of various powder mixtures. In all cases a clear correlation between conductivity and density could be established, indicating that measurements of electric conductivity could indeed be exploited in an effort to render valid information about the density of the sample under test. We found a linear correlation for non-lubricated parts and a non-linear behavior for lubricated samples. Specifically, it was found that the conductivity increases with increasing density only up to a maximum value obtained at ap-proximately 6.9g/cm3. Interestingly, any additional density increase leads to a reduction of the conductivity. This behavior was confirmed to be inherent in all powder mixtures with lubricants. The thesis research is able to provide a physical model and a mathematical formulation describ-ing this counter-intuitive phenomenon. A finite element solver in conjunction with an inversion algorithm was then implemented to study arbitrarily shaped part geometries. Based on the principles of electric impedance imag-ing, the developed algorithm faithfully reconstructs the density distribution from surface voltage measurements. The feasibility of the instrumentation approach for both simple and complex parts can be demonstrated using a new sensor concept and measurement arrangement. Measurements were performed on both geometrically simple and complex parts.