Current techniques of hydrogen production (primarily reformation of fossil fuels) are unsustainable, releasing CO2 into the atmosphere, as well as consuming limited reserves of fossil fuels. The copper-chlorine cycle is a promising thermochemical process which can cost-effectively produce hydrogen with less environmental impact. In this thesis, new predictive formulations and experimental data are presented to improve the conversion extent and reaction rates of the hydrolysis reactor in the Cu-Cl cycle. This reactor has critical implications for the design, operation, and efficiency of the Cu-Cl cycle and hydrogen production. The relatively high temperature needed to drive the reaction requires a significant input of thermal energy. This thesis focuses on methods and analysis to reduce the unreacted steam in the hydrolysis reactor, in order to reduce the thermal energy input and improve the cycle’s thermal efficiency. A key outcome from this thesis is the experimental verification of reducing the steam to copper chloride ratio from 16:1 (past studies) to about 3:1. The results of this thesis provide key new data to design a more efficient hydrolysis reactor that can be effectively integrated within the Cu-Cl cycle. / UOIT

In recent history, the area of physics-based engineering simulation has seen rapid increases in both computer workstation performance as well as common model complexity, both driven largely in part by advances in memory density and availability of clusters and multi-core processors. While the increase in computation time due to model complexity has been largely offset by the increased performance of modern workstations, the increase in model setup time due to model complexity has continued to rise. As such, the major time requirement for solving an engineering model has transitioned from computation time to problem setup time. This is due to the fact that developing the required mesh for complex geometry can be an extremely complicated and time consuming task. Consequently, new solution techniques which are capable of reducing the required amount of human interaction are desirable. The subject of this thesis is the development of a novel meshless method that promises to eliminate the need for structured meshes, and thus, the need for complicated meshing procedures. Although the savings gain due to eliminating the meshing process would be more than sufficient to warrant further study, the proposed method is also capable of reducing the computation time and memory footprint compared to similar models solved using more traditional finite element, finite difference, finite volume, or boundary element methods. In particular, this thesis will outline the development of an interactive, meshless, physically accurate modeling environment that provides an extensible framework which can be applied to a multitude of governing equations encountered in computational mechanics and thermofluids. Additionally, through the development of tailored preprocessing routines, efficiency and accuracy of the proposed meshless algorithms can be tested in a more realistic and flexible environment. Examples are provided in the areas of elasticity, heat transfer and computational fluid dynamics.