An Investigation of the Application of Phase Change Materials in Practical Thermal Management Systems

This work investigates the application of alternative cooling techniques to thermal management. In the first section, this work presents models and extensive simulation studies on an alternative cooling strategy based upon phase change materials (PCMs) for the thermal management system of a LED headlight assembly. These studies have shown that properly chosen PCMs, when suspended in metal foam matrices, increased the thermal conductivity of the PCM. The increased thermal conductivity can enhance the cooling characteristics of a practical thermal management system for a LED headlight system. To further enhance the advantages of using PCMs, nanoparticle enhanced fluids (nanofluids) are desirable as an additional source of cooling. The use of nanofluids motivates the development of a new diagnostic tool for multiphase flows and a minimization algorithm for analyzing the data. For this purpose, the second section of this work develops a new technique that is based on wavelength-multiplexed laser extinction (WMLE) to measure particle sizes in multiphase flows. In the final section of this work, the simulated algorithm (SA) is investigated for analyzing the data collected in this work. Specifically, the parallelization of the SA technique is investigated to reduce the high computational cost associated with the SA algorithm

Laser Absorption Chemical Species Tomography

This thesis outlines two advancements in the field of limited data absorption tomography. First, a novel reconstruction algorithm integrating the use of level set methods is presented that incorporates the additional a priori knowledge of a distinct interface between the species of interest and co-flow. The added a priori further reduces the ill-posedness of the system to produce a final concentration distribution that explains the laser absorption measurements and is qualitatively consistent with advection/diffusion transport. The algorithm is demonstrated by solving a simulated laser tomography experiment on a turbulent methane plume, and is compared with the current state-of-the-art reconstruction algorithm. Given the limited number of attenuated measurements, accurate reconstructions are also highly dependent on the locations sampled by the measurement array. This thesis displays how the mathematical properties of the coefficient matrix, A, formed by the locations of the lasers, are related to the information content of the attenuation data using a Tikhonov reconstruction framework. This formulation, in turn, becomes a basis for a beam arrangement design algorithm that minimizes the reliance on additional assumed information about the concentration distribution. Using genetic algorithms, beam arrangements can be optimized for a given application by incorporating physical constraints of the beam locations. The algorithm is demonstrated by optimizing unconstrained and constrained arrangements of light sources and detectors. Simulated experiments are performed to validate the optimality of the arrangements

The conjugate gradient regularization method in Computed Tomography problems

In this work we solve inverse problems coming from the area of Computed Tomography by means of regularization methods based on conjugate gradient iterations. We develop a stopping criterion which is efficient for the computation of a regularized solution for the least-squares normal equations. The stopping rule can be suitably applied also to the Tikhonov regularization method. We report computational experiments based on different physical models and with different degrees of noise. We compare the results obtained with those computed by other currently used methods such as Algebraic Reconstruction Techniques (ART) and Backprojection