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This study examines the feasibility of broadening the fuel capabilities of a direct-injected two-stroke engine with stratified combustion. A three cylinder, direct-injected two-stroke engine was modified to operate on JP-5, a kerosene-based jet fuel that is heavier, more viscous, and less volatile than gasoline. Demonstration of engine operation with such a fuel after appropriate design modifications would significantly enhance the utilization of this engine in a variety of applications. Results have indicated that the performance characteristics of this engine with jet fuel are similar to that of gasoline with respect to torque and power output at low speeds and loads, but the engine's performance is hampered at the higher speeds and loads by the occurrence of knock.

A mathematical model is presented for analysis and optimization of the adsorbents in the multifiltration beds contained in the International Space Station (ISS) water processor. The model consists of a physical properties database, an equilibrium description for single and multicomponent adsorption, and a kinetic description for adsorption beds in the water processor. The model is verified on a surrogate mixture designed to mimic the adsorption potential of the ISS shower/handwash waste stream.

The destruction of organic contaminants in waste water for closed systems, such as that of the International Space Station, is crucial due to the need for recycling the waste water. A cocurrent upflow bubble column using oxygen as the gas phase oxidant and packed with catalyst particles consisting of a noble metal on an alumina substrate is being developed for this process. This paper addresses the development of a plug-flow model that will predict the performance of this three phase reactor system in destroying a multicomponent mixture of organic contaminants in water. Mass balances on a series of contaminants and oxygen in both the liquid and gas phases are used to develop this model. These mass balances incorporate the gas-to-liquid and liquid-to-particle mass transfer coefficients, the catalyst effectiveness factor, and intrinsic reaction rate.

A mathematical model is presented for analysis and optimization of the ion exchange beds in the International Space Station (ISS) Water Processor. The model consists of a physical properties database, an equilibrium description for binary and multicomponent ion exchange, and a kinetic description for ion exchange beds in the Water Processor. The ion exchange model will be verified for an Ersatz water designed to mimic the ISS shower/handwash waste stream.

A three phase catalytic mathematical model was developed for analysis and optimization of the volatile reactor assembly (VRA) used on International Space Station (ISS) Water Processor. The Langmuir-Hinshelwood Hougen-Watson (L-H) expression was used to describe the surface reaction rate. Small column experiments were used to determine the L-H rate parameters. The test components used in the experiments were acetic acid, acetone, ethanol, 1-propanol, 2-propanol and propionic acid. These compounds are the most prevalent ones found in the influent to the VRA reactor. The VRA model was able to predict performance of small column data and experimental data from the VRA flight experiment.

Future lunar missions will utilize a Lunar DC microgrid (LDCMG) to construct the infrastructure for distributing, storing, and utilizing electrical energy. The LDCMG’s energy management, of which energy storage systems (ESS) are crucial components, will be essential to the success of the missions. Standard system design currently employs a rule-of-thumb approach in which design methodologies rely on heuristics that may only evaluate local power balancing requirements. The Hamiltonian surface shaping and power flow control (HSSPFC) method can also be utilized to analyze and design the lunar LDCMG power distribution network and ESS. In this research, the HSSPFC method will be utilized to determine the ideal energy storage requirements for ESS and the optimally distributed control architecture.