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Alloy nitrides (U,Zr), (U,Ce), and (U,Y) were prepared and exposed to vacuum at temperatures to 1700 C (1973 K) and compared with pure UN. Weight loss data and physical observations showed that the alloy samples were more stable than UN. In weight loss, (U,Zr)N was 3 times as stable as UN at 1600 C (1873 K) for 100 hr at 0.000002 torr (0.000266n/sq.m.).
NASA's future human exploration missions will require chemical processing plants to convert local resources into consumables to support astronaut activities. The thin and mostly carbon dioxide atmosphere of Mars is estimated to have 1 - 10 particles/cu.cm with diameters of 1 - 10 m and up to 1000 particles/cu.cm during storms. The dust in the Martian atmosphere can foul chemical reactors and pose a risk to life support systems. Electrostatic precipitation (ESP) removes dust particles from the Martian atmosphere. The Electrostatics and Surface Physics Laboratory at NASA's Kennedy Space Center has developed a COMSOL Multiphysics(Registered Trademark) model of an ESP for dust filtration on Mars. The fundamental principles of an ESP can be simulated by four physics modules: plasma, AC/DC electromagnetics, computational fluid dynamics (CFD), and particle tracing. In the ESP model presented here, the plasma module was solved to estimate particle charge. The AC/DC and CFD module were solved for the electrostatic force and fluid force. The particle-tracing module was solved for particle collection efficiency.
NASA is performing research related to a Nuclear-Thermal Propulsion (NTP) engine as a step toward future manned missions to Mars. BWX Technologies (BWXT), in conjunction with NASA, is developing the reactor subsystem for that NTP engine design. As a subset of the reactor subsystem, the fuel elements have continued to evolve in design, as well. A set of experiments within the Nuclear Thermal Reactor Element Environmental Simulator at NASA Marshall has been developed to compliment that design process, including a series of surrogate fuel elements. Before the experiments of each surrogate can be completed, they must be deemed safe using structural analysis, which itself requires thermal and conjugate heat transfer analyses of the articles. Therefore, conjugate heat transfer simulations of the hydrogen flow through the test article fuel element surrogates were developed to provide estimates of heating, as well as to provide assessments of the fluid flow through the elements. The set of simulations involved not only the separate test conditions, but also a sensitivity study to estimate the effect of physical parameter uncertainty on the selected quantities of interest. Additionally, the fluid flow through the fore section inner plenum dome to the entrances of the fuel elements, another section of the reactor subsystem still under active development, was simulated and analyzed. The simulations show the extent of non-uniformity in the mass flow distribution across the dome outlets. Furthermore, additional analyses estimate the effects of required flow blockages on the potential development of flow dynamics. These analyses were used in the design cycle to make improvements to the reactor subsystem design.
Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.
Lattice Confinement Fusion (LCF) 1 • Fusion of hydrogen isotopes into helium isotopes • No tokamak magnets or laser power supplies • Nuclear fuel is confined and triggered within lattice • Nuclear reactions enhanced by electron screening • Extended Electrodynamics (EED) role • NASA published results in Physical Review C 2,3 • Locally hot but globally cold • Commercialized in 2025 to produce medical radioisotopes 4 Lattice Confinement Fusion Fast-Fission Hybrid Reactor • Fusion neutrons fission uranium, spent fuel rods or thorium • No enriched uranium, cleaner fission! • Demonstrated with US Navy and GEC • Supported by NASA STMD (NIAC) and NSF Application • LEO, Deep Space Power and High I sp Propulsion • (Terrestrial)
Consideration is given to the following types of high energy physics instrumentation: drift chambers, multiwire proportional chambers, calorimeters, optical detectors, ionization and scintillation detectors, solid state detectors, and electronic and digital subsystems. Attention is also paid to reactor instrumentation, nuclear medicine instrumentation, data acquisition systems for nuclear instrumentation, microprocessor applications in nuclear science, environmental instrumentation, control and instrumentation of nuclear power generating stations, and radiation monitoring. Papers are also presented on instrumentation for the High Energy Astronomy Observatory.
In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for that particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor simulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for simulations.
In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for a particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor sim- ulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. In order to improve the agreement with flame temperatures, the thermal properties of the product species is adjusted to better match the mixture proper- ties of the full mechanism. The combustion model is then applied to the simulation of a representative scramjet flowpath, and the results compared to experimental data and other kinetic models. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for CFD simulations.
The topics are presented in viewgraph form and include the following: total engine system management critical to successful nuclear thermal rocket engine (NTRE) start up; NERVA type engine start windows; reactor power control; heterogeneous reactor cooling; propellant feed system dynamics; integrated NTRE start sequence; moderator cooling loop and efficient NTRE starting; analytical simulation and low risk engine development; accurate simulation through dynamic coupling of physical processes; and integrated NTRE and mission performance.
FOST 2 is an integrated membrane system that incorporates a forward osmosis subsystem and a reverse osmosis subsystem working in series. It has been designed as a post treatment system to process the effluent from the Membrane Aerated Biological Reactor developed at NASA Johnson Space Center and Texas Tech University. Its function is to remove dissolved solids residual such as ammonia and suspended solids, as well as to provide a physical barrier to microbial and viral contamination. A tubular CTA membrane module from HTI and a flat-sheet lipid-base membrane module from Porifera were integrated and tested on FOST 2 in the past, using both a bioreactor's effluent and greywater as the feed solution. This paper documents the performance of FOST 2 after its upgrade with a hollow-fiber CTA membrane module from Toyobo, treating real black-water to generate the osmotic agent solution necessary to conduct growth studies of genetically engineered microorganism for the Synthetic Biological Membrane project.
Controlling carbon dioxide in spacecraft cabin air may be accomplished using algal photobioreactors (PBRs). The purpose of this project was to evaluate the use of a commercial microcontroller, the Arduino Mega 2560, for measuring key phot~ioreactor variables: dissolved oxygen, pH, temperature, light, and carbon dioxide. The Arduino platform is an opensource physical computing platform composed of a compact microcontroller board and a C++/C computer language (Arduino 1.0.5). The functionality of the Arduino platform can be expanded by the use of numerous add-ons or 'shields'. The Arduino Mega 2560 was equipped with the following shields: datalogger, BNC shield for reading pH sensor, a Mega Moto shield for controlling CO2 addition, as well as multiple sensors. The dissolved oxygen (DO) probe was calibrated using a nitrogen bubbling technique and the pH probe was calibrated via an Omega pH simulator. The PBR was constructed using a 2 L beaker, a 66 L box for addition of CO2, a micro porous membrane, a diaphragm pump, four 25 watt light bulbs, a MasterFiex speed controller, and a fan. The algae (wild type Synechocystis PCC6803) was grown in an aerated flask until the algae was dense enough to used in the main reactor. After the algae was grown, it was transferred to the 2 L beaker where CO2 consumption and O2 production was measured using the microcontroller sensor suite. The data was recorded via the datalogger and transferred to a computer for analysis.
Polycrystalline, thin-film photovoltaics represent one of the few (if not the only) renewable power sources which has the potential to satisfy the demanding technical requirements for future space applications. The demand in space is for deployable, flexible arrays with high power-to-weight ratios and long-term stability (15-20 years). In addition, there is also the demand that these arrays be produced by scalable, low-cost, high yield, processes. An approach to significantly reduce costs and increase reliability is to interconnect individual cells series via monolithic integration. Both CIS and CdTe semiconductor films are optimum absorber materials for thin-film n-p heterojunction solar cells, having band gaps between 0.9-1.5 ev and demonstrated small area efficiencies, with cadmium sulfide window layers, above 16.5 percent. Both CIS and CdTe polycrystalline thin-film cells have been produced on a laboratory scale by a variety of physical and chemical deposition methods, including evaporation, sputtering, and electrodeposition. Translating laboratory processes which yield these high efficiency, small area cells into the design of a manufacturing process capable of producing 1-sq ft modules, however, requires a quantitative understanding of each individual step in the process and its (each step) effect on overall module performance. With a proper quantification and understanding of material transport and reactivity for each individual step, manufacturing process can be designed that is not 'reactor-specific' and can be controlled intelligently with the design parameters of the process. The objective of this paper is to present an overview of the current efforts at MMC to develop large-scale manufacturing processes for both CIS and CdTe thin-film polycrystalline modules. CIS cells/modules are fabricated in a 'substrate configuration' by physical vapor deposition techniques and CdTe cells/modules are fabricated in a 'superstrate configuration' by wet chemical methods. Both laser and mechanical scribing operations are used to monolithically integrate (series interconnect) the individual cells into modules. Results will be presented at the cell and module development levels with a brief description of the test methods used to qualify these devices for space applications. The approach and development efforts are directed towards large-scale manufacturability of established thin-film, polycrystalline processing methods for large area modules with less emphasis on maximizing small area efficiencies.
The goal of this program is to demonstrate that a dichlorosilane-based reductive chemical vapor deposition (CVD) process is capable of producing, at low cost, high quality polycrystalline silicon. Physical form and purity of this material will be consistent with LSA material requirements for use in the manufacture of high efficiency solar cells. Four polysilicon deposition runs were completed in an intermediate size reactor using dichlorosilane fed from 250 pound cylinders. Results from the intermediate size reactor are consistent with those obtained earlier with a small experimental reactor. Modifications of two intermediate size reactors were completed to interface with the dichlorosilane process demonstration unit (PDU).
Media Filter MOXIE support: completed flow performance tests and initial dust loading tests of the MOXIE HEPA filter in the Mars Flow Loop Designed and fabricated prototype full-scale scroll filter for testing of renewable filter performance Mars Flow Loop upgrades: installed more sensitive instrumentation, improved imaging, and increased run duration capability Electrostatic Precipitator (ESP) Plasma-physics based model predicts particle charge and trajectory Characterizing dust environment from fluidized-bed injection dust environment using laser sheet visualization and Fine Particle Analyzer Sabatier Design Study Defined the Sabatier design space, including reactor type, thermal management, gas recycling/separation Modeled Sabatier systems with one or two reactors with different types of thermal management Adding thermal management schemes and recycling and gas separation to model Catalyst Screening Performing compression testing on new and used catalyst pellets Performing vibration testing on different catalyst pellet types under different load conditions Preparing to test catalysts for performance and degradation
The International Space Station (ISS) is currently equipped with a complex, heavy, and power consuming system that recovers approximately 50% of O2 from metabolic CO2. Future long duration missions will require a sustainable and highly efficient system capable of yielding a minimum of 75% O2 recovery. A Macrofluidic Electrochemical Reactor (MFECR) technology development effort is currently underway at NASA Marshall Space Flight Center (MSFC) to significantly increase current O2 recovery efficiency and reduce complexity of the system. This paper presents a comprehensive multi-physic 3D model developed at MSFC on CO2 conversion to O2 and C2H4 at standard conditions via MFECR. The 3D spatial domain of the model is a replica of the actual MFECR’s 3D drawing generated for the MFECR fabrication and operated to recover O2 from CO2 yielding C2H4 as byproduct. Electrochemical (EC) physics that includes EC multicomponent reaction mechanisms, mass transport, and current density distributions is coupled in the model with all the other physics phenomena involved in the process, such as free and porous fluid flow, multicomponent mass transfer, heat transfer, and DC electrical current generation along with Joule heating effect. The authors plan to use experimental results to validate this comprehensive and rigorous model and build a reliable simulator that will not only assist the authors on the MFECR design but also optimize its operation.
Work toward a self-consistent plasma simulation using the DSMC (Direct Simulation Monte Carlo) method for examination of the flowfields of low-pressure high density plasma reactors is presented. Presently, DSMC simulations for these applications involve either treating the electrons as a fluid or imposing experimentally determined values for the electron number density profile. In either approach, the electrons themselves are not physically simulated. Self-consistent plasma DSMC simulations have been conducted for aerospace applications but at a severe computational cost due in part to the scalar architectures on which the codes were employed. The present work attempts to conduct such simulations at a more reasonable cost using a plasma version of the object-oriented parallel Cornell DSMC code, MONACO, on an IBM SP-2. Due to availability of experimental data, the GEC reference cell is chosen to conduct preliminary investigations. An argon discharge is chosen to conduct preliminary investigations. An argon discharge is examined thus affording a simple chemistry set with eight gas-phase reactions and five species: Ar, Ar(+), Ar(*), Ar(sub 2), and e where Ar(*) is a metastable.
Flame resistant fibrous materials for space shuttle application were developed through chemical modification of commercially available aromatic polyamide fibrous products. The new surface treatment was achieved in the laboratory by ultraviolet activation of the fabric in the presence of fluoroolefin monomers and a diluent gas. The monomers grafted under these conditions provide the improved properties of the fabric in flame resistance, chemical inertness, and nonwettability without the sacrifice of color or physical properties. The laboratory reaction vessel was scaled-up to a batch continuous process, which treats ten yards of the commercial width textiles. The treated commercial width Nomex (HT-10-41) from the scaled-up reactor is self-extinguishing in an oxygen-enriched environment, water-repellent, soft, silky, and improved in chemical resistance. Unlike most textile processes, the grafting unit operates under dry conditions and no chemical by-products have to be washed out of the finished product.
The research goal was to achieve a fundamental understanding of the physical processes occurring at the surfaces and interfaces of epitaxially grown InGaAs/GaAs (100) heterostructures. This will facilitate the development of quantum well devices for infrared optical applications and provide quantitative descriptions of key phenomena which impact their performance. Devices impacted include high-speed laser diodes and modulators for fiber optic communications at 1.55 micron wavelengths and intersub-band lasers for longer infrared wavelengths. The phenomenon of interest studied was the migration of indium in InGaAs structures. This work centered on the molecular beam epitaxy reactor and characterization apparatus donated to CAU by AT&T Bell Laboratories. The material characterization tool employed was secondary ion mass spectrometry. The training of graduate and undergraduate students was an integral part of this program. The graduate students received a thorough exposure to state-of-the-art techniques and equipment for semiconductor materials analysis as part of the Master''s degree requirement in physics. The undergraduates were exposed to a minority scientist who has an excellent track record in this area. They also had the opportunity to explore surface physics as a career option. The results of the scientific work was published in a refereed journal and several talks were presented professional conferences and academic seminars.