The combustion process of a fuel is a challenging subject when it comes to analyze its performance and resultant emissions. The main task of this study is to optimize the selection of a hydrogen-rich fuel based on its performance and emissions. Computational Fluid Dynamics analysis is performed to test the combustion performance and emissions from the vortex trapped combustor when natural gas fuel (methane) is replaced with renewable and alternative fuels such as hydrogen and synthesis gas. Correlation graphs for the trapped vortex combustor performance and NOx, CO, and CO2 emissions for various types of fuels with different compositions and heat of combustion values were established. Methane, Hydrogen and 10 different syngas fuels were analyzed in this study using computational fluid dynamics numerical method. The trapped vortex combustor that represents an efficient and compact combustor for flame stability was investigated. The TVC consists of a fore body and two after body disks . These components are all encircled with a Pyrex tube. The purpose of the after body disks is to create the vortex wakes that will enhance the combustion process and minimize the NOx emissions. The TVC CFD model was validated by comparing the CFD model results using propane fuel with existing experimental results that were established in Rome, Italy. The static temperature distribution and NOx, CO emissions, combustor efficiency and total pressure drop results of the three dimensional CFD model were similar to the experimental data. Effects of H2/CO and H2/CH4 ratios and the mass fraction of each constituent of syngas fuels and Hydrogen-Methane fuel mixture on the TVC performance and emissions were investigated. / Moreover, the fuel injector Reynolds number and Lower heating values for Methane, Hydrogen and 10 syngas fuels on the TVC performance and emissions were also investigated. Correlation plots for the NOx, CO and CO2 emissions versus the fuel injector Reynolds number and low heating value were established. These correlation curves can be used as a fair design diagram to optimize the fuel selection process for aerospace and electrical power plant applications. / by Khaled Zbeeb. / Thesis (Ph.D.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

This thesis proposes a Power Management Model (PMM) for optimization of several green power generation systems. A Photovoltaic/Fuel cell Hybrid Energy System (PFHES) consisting of solar cells, electrolyzer and fuel cell stack is utilized to meet a specific DC load bank for various applications. The Photovoltaic system is the primary power source to take advantage of renewable energy. The electrolyzer-fuel cell integration is used as a backup and as a hydrogen storage system with the different energy sources integrated through a DC link bus. An overall power management strategy is designed for the optimization of the power flows among the different energy sources. Extensive simulation experiments have been carried out to verify the system performance under PMM governing strategy. The simulation results indeed demonstrate the effectiveness of the proposed approach. / by Rosana Melendez. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Thermochemical processes for hydrogen production driven by nuclear energy are promising alternatives to existing technologies for large-scale commercial production of hydrogen, without dependence on fossil fuels. In the Copper-Chlorine (Cu-Cl) cycle, water is decomposed in a sequence of intermediate processes with a net input of water and heat, while hydrogen and oxygen gases are generated as the products. The Super Critical Water-cooled Reactor (SCWR) has been identified as a promising source of heat for these processes. In this thesis, the process analysis and simulation models are developed using the Aspen PlusTM chemical process simulation package, based on experimental work conducted at the Argonne National Laboratory (ANL) and Atomic Energy of Canada Limited (AECL). A successful simulation is performed with an Electrolyte Non Random Two Liquid (ElecNRTL) model of Aspen Plus. The efficiency of the cycle based on three and four step process routes is examined in this thesis. The thermal efficiency of the four step thermochemical process is calculated as 45%, while the three step hybrid thermochemical cycle is 42%, based on the lower heating value (LHV) of hydrogen. Sensitivity analyses are performed to study the effects of various operating parameters on the efficiency, yield, and thermodynamic properties. Possible efficiency improvements are discussed. The results will assist the development of a lab-scale cycle which is currently being conducted at the University of Ontario Institute of Technology (UOIT), in collaboration with its partners. / UOIT

Metal hydrides are promising candidates for H2 storage, but high stability and poor kinetics are the important challenges which have to be solved for vehicular applications. Most of recent experimental reports for improving thermodynamics of metal hydrides have been focused on lowering reaction enthalpies of a metal hydride by mixing other compounds. However, finding out metal hydride mixtures satisfying favorable thermodynamics among a large number of possible metal hydride mixtures is inefficient and thus a systematic approach is required for an efficient and rigorous solution. Our approaches introduced in this thesis allow a systematic screening of promising metal hydrides or their mixtures from all possible metal hydrides and their mixtures. Our approaches basically suggest two directions for improving metal hydride thermodynamics. First, our calculations for examining the relation between the particle size of simple metal hydrides and thermodynamics of their decomposition reactions provide that the relation would depend on the total surface energy difference between a metal and its hydride form. It ultimately suggests that we will be able to screen metal hydride nanoparticles having favorable thermodynamics from all possible metal hydrides by examining the total surface differences. Second, more importantly, we suggest that our thermodynamic calculations combined with the grand canonical linear programming method and updated database efficiently and rigorously screen potential promising bulk metal hydrides and their mixtures from a large collection of possible combinations. The screened promising metal hydrides and their mixtures can release H2 via single step or multi step. Our additional free energy calculations for a few selected promising single step reactions and their metastable paths show that we can identify the most stable free energy paths for any selected reactant mixtures. In this thesis, we also demonstrate that a total free energy minimization method can predict the possible evolution of impurity other than H2 for several specified mixtures. However, it is not ready to predict reaction thermodynamics from a large number of compounds.