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At least 379 records · Page 21

Hubble Space Telescope solar cell module thermal cycle test

The Hubble Space Telescope (HST) solar array consists of two identical double roll-out wings designed after the Hughes flexible roll-up solar array (FRUSA) and was developed by the European Space Agency (ESA) to meet specified HST power output requirements at the end of 2 years, with a functional lifetime of 5 years. The requirement that the HST solar array remain functional both mechanically and electrically during its 5-year lifetime meant that the array must withstand 30,000 low Earth orbit (LEO) thermal cycles between approximately +100 and -100 C. In order to evaluate the ability of the array to meet this requirement, an accelerated thermal cycle test in vacuum was conducted at NASA's Marshall Space Flight Center (MSFC), using two 128-cell solar array modules which duplicated the flight HST solar array. Several other tests were performed on the modules. The thermal cycle test was interrupted after 2,577 cycles, and a 'cold-roll' test was performed on one of the modules in order to evaluate the ability of the flight array to survive an emergency deployment during the dark (cold) portion of an orbit. A posttest static shadow test was performed on one of the modules in order to analyze temperature gradients across the module. Finally, current in-flight electrical performance data from the actual HST flight solar array will be tested.

Douglas, Alexander↗

Antenna Measurements: Test & Analysis of the Radiated Emissions/Immunity of the NASA/Orion Spacecraft Dart Parachute Simulator & Prototype Capsule - The Crew Exploration Vehicle

For future NASA Manned Space Exploration of the Moon and Mars, a blunt body capsule, called the Orion Crew Exploration Vehicle (CEV), composed of a Crew Module (CM) and a Service Module (SM), with a parachute decent assembly is planned for reentry back to Earth. A Capsule Parachute Assembly System (CPAS) is being developed for preliminary prototype parachute drop tests at the Yuma Proving Ground (YPG) to simulate high-speed reentry to Earth from beyond Low-Earth-Orbit (LEO) and to provide measurements of position, velocity, acceleration, attitude, temperature, pressure, humidity, and parachute loads. The primary and secondary (backup) avionics systems on CPAS also provide mission critical firing events to deploy, reef, and release the parachutes in three stages (extraction, drogues, mains) using mortars and pressure cartridge assemblies. In addition, a Mid-Air Delivery System (MDS) is used to separate the capsule from the sled that is used to eject the capsule from the back of the drop plane. Also, high-speed and high-definition cameras in a Video Camera System (VCS) are used to film the drop plane extraction and parachute landing events. Intentional and unintentional radiation emitted from and received by antennas and electronic devices on/in the CEV capsule, the MDS sled, and the VCS system are being tested for radiated emissions/immunity (susceptibility) ~ (RE/RS). To verify Electromagnetic Compatibility (EMC) of the Orion capsule, Electromagnetic Interference (EMI) measurements are being made inside a semi-anechoic chamber at NASA/JSC on the components of the CPAS system. Measurements are made at 1m from the components-under-test (CUT). In addition, EMI measurements of the integrated CEV system are being made inside a hanger at YPG. These measurements are made in a complete circle, at 30◦ angles or less, around the Orion Capsule, the spacecraft system under-test (SUT). Near-field B-Dot probe measurements on the surface of the Orion capsule are being extrapolated outward to the 1m standard distance for comparison to the MIL-STD radiated emissions limit, and far-field hybrid antenna measurements at 3m are being extrapolated inward to the 1m distance for similar comparisons.

Norgard, John D.↗

A Theory for Rapid Charging Events on the International Space Station

The Floating Potential Measurement Unit (FPMU) has detected high negative amplitude rapid charging events (RCEs) on the International Space Station (ISS) at the morning terminator. These events are larger and more rapid than the ISS morning charging events first seen by the Floating Potential Probe (FPP) on ISS in 2001. In this paper, we describe a theory for the RCEs that further elucidates the nature of spacecraft charging in low Earth orbit (LEO) in a non-equilibrium situation. The model accounts for all essential aspects of the newly discovered phenomenon, and is amenable to testing on-orbit. Predictions of the model for the amplitude of the ISS RCEs for the full set of ISS solar arrays and for the coming solar cycle are given, and the results of modeling by the Environments WorkBench (EWB) are compared to the observed events to show that the phenomenon can be explained by solar array driven charging. The situation is unique because the coverglasses have not yet reached equilibrium with the surrounding plasma during the RCEs. Finally, a prescription for further use of the ISS for investigating fundamental plasma physics in LEO is given. Already, plasma and charging monitoring instruments on ISS have taught us much about spacecraft interactions with the dense LEO plasma, and we expect they will continue to yield more valuable science when the Japanese Experiment Module (JEM) is in place.

Ferguson, Dale C.↗

Structural Heat Intercept, Insulation and Vibration Evaluation Rig (SHIIVER)

The Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) is a large scale cryogenic fluid management (CFM) test bed designed to scale CFM technologies for inclusion on large, in-space stages. A part of the evolvable Cryogenics (eCryo) project, SHIIVER is a technology development task that is supportive of future exploration propulsion needs. Technologies developed under the eCryo Project will play a critical role in enabling increasingly longer duration in-space missions beyond Low Earth Orbit (LEO).

Vapor cooling↗

Characterization of Orbital Debris Via Hyper-Velocity Ground-Based Tests

To replicate a hyper-velocity fragmentation event using modern-day spacecraft materials and construction techniques to better improve the existing DoD and NASA breakup models. DebriSat is intended to be representative of modern LEO satellites.Major design decisions were reviewed and approved by Aerospace subject matter experts from different disciplines. DebriSat includes 7 major subsystems. Attitude determination and control system (ADCS), command and data handling (C&DH), electrical power system (EPS), payload, propulsion, telemetry tracking and command (TT&C), and thermal management. To reduce cost, most components are emulated based on existing design of flight hardware and fabricated with the same materials. A key laboratory-based test, Satellite Orbital debris Characterization Impact Test (SOCIT), supporting the development of the DoD and NASA satellite breakup models was conducted at AEDC in 1992 .Breakup models based on SOCIT have supported many applications and matched on-orbit events reasonably well over the years.

Cowardin, Heather↗

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

Infalling ultra-faint dwarfs as emissaries of the Axiverse

Recent discoveries of ultra-faint dwarf galaxies (UFDs) infalling onto the Milky Way, namely Leo K & M at r ≃ 450 kpc, considerably strengthens the case that UFDs constitute a distinct galaxy class that is inherently smaller and fainter, and metal-poorer than the classical dwarf spheroidals (dSph). This distinction is at odds with the inherent continuity of galaxy halo masses formed under scale-free gravity for any standard dark-matter (DM) model. Here, we show that distinct galaxy classes do evolve in cosmological simulations of multiple light bosons representing the “Axiverse” proposal of string theory, where a discrete mass spectrum of axions is generically predicted to span many decades in mass. In this context, the observed UFD class we show corresponds to a relatively heavy boson of 3 × 10 −21 eV, including Leo K & M, whereas a lighter axion of 10 −22 eV comprises the bulk of DM in all larger galaxies including the dSphs. Although Leo M is larger in size than Leo K, we predict its velocity dispersion to be smaller ( ≃ 1.7 km/s) than that of Leo K ( ≃ 4.5 km/s) because of the inverse de Broglie scale dependence on momentum. This scenario can be definitively tested using millisecond pulsars close to the Galactic center, where the Compton frequencies of the heavy and light bosons imprint monotone timing residuals that may be detected by the Square Kilometre Array (SKA) on timescales of approximately one week and four months, respectively.

dark matter↗

Vehicle for Space Transfer and Recovery (VSTAR), volume 1

The Vehicle Space Transfer and Recovery (VSTAR) system is designed as a manned orbital transfer vehicle (MOTV) with the primary mission of Satellite Launch and Repair (SLR). VSTAR will provide for economic use of high altitude spaceflight for both the public and private sector. VSTAR components will be built and tested using earth based facilities. These components will then be launched using the space shuttle, into low earth orbit (LEO) where it will be constructed on a U.S. built space station. Once in LEO the vehicle components will be assembled in modules which can then be arranged in various configurations to perform the required missions.

Source record↗

Design of a power management and distribution system for a thermionic-diode powered spacecraft

The Electrical Systems Development Branch of the Power Technology Division at the NASA Lewis Research Center in Cleveland, Ohio is designing a Power Management and Distribution (PMAD) System for the Air Force's Integrated Solar Upper Stage (ISUS) Engine Ground Test Demonstration (EGD). The ISUS program uses solar-thermal propulsion to perform orbit transfers from Low Earth Orbit (LEO) to Geosynchronous Orbit (GEO) and from LEO to Molnya. The ISUS uses the same energy conversion receiver to perform the LEO to High Earth Orbit (HEO) transfer and to generate on-orbit electric power for the payloads. On-orbit power generation is accomplished via two solar concentrators heating a dual-cavity graphite-core which has Thermionic Diodes (TMD's) encircling each cavity. The graphite core and concentrators together are called the Receiver and Concentrator (RAC). The TDM-emitters reach peak temperatures of approximately 2200K, and the TID-collectors are run at approximately 1000K. Because of the high Specific Impulse (I(sup sp)) of solar thermal propulsion relative to chemical propulsion, and because a common bus is used for communications, GN&C, power, etc., a substantial increase in payload weight is possible. This potentially allows for a stepdown in the required launch vehicle size or class for similar payload weight using conventional chemical propulsion and a separate spacecraft bus. The ISUS power system is to provide 1000W(sub e) at 28+/-6V(sub dc) to the payload/spacecraft from a maximum TID generation capability of 1070W(sub e) at 2200K. Producing power with this quality, protecting the spacecraft from electrical faults and accommodating operational constraints of the TID's are the responsibilities of the PMAD system. The design strategy and system options examined along with the proposed designs for the Flight and EGD configurations are discussed herein.

Kimnach, Greg L.↗

NASA's J-2X Engine Builds on the Apollo Program for Lunar Return Missions

In January 2006, NASA streamlined its U.S. Vision for Space Exploration hardware development approach for replacing the Space Shuttle after it is retired in 2010. The revised CLV upper stage will use the J-2X engine, a derivative of NASA s Apollo Program Saturn V s S-II and S-IVB main propulsion, which will also serve as the Earth Departure Stage (EDS) engine. This paper gives details of how the J- 2X engine effort mitigates risk by building on the Apollo Program and other lessons learned to deliver a human-rated engine that is on an aggressive development schedule, with first demonstration flight in 2010 and human test flights in 2012. It is well documented that propulsion is historically a high-risk area. NASA s risk reduction strategy for the J-2X engine design, development, test, and evaluation is to build upon heritage hardware and apply valuable experience gained from past development efforts. In addition, NASA and its industry partner, Rocketdyne, which originally built the J-2, have tapped into their extensive databases and are applying lessons conveyed firsthand by Apollo-era veterans of America s first round of Moon missions in the 1960s and 1970s. NASA s development approach for the J-2X engine includes early requirements definition and management; designing-in lessons learned from the 5-2 heritage programs; initiating long-lead procurement items before Preliminary Desi& Review; incorporating design features for anticipated EDS requirements; identifying facilities for sea-level and altitude testing; and starting ground support equipment and logistics planning at an early stage. Other risk reduction strategies include utilizing a proven gas generator cycle with recent development experience; utilizing existing turbomachinery ; applying current and recent main combustion chamber (Integrated Powerhead Demonstrator) and channel wall nozzle (COBRA) advances; and performing rigorous development, qualification, and certification testing of the engine system, with a philosophy of "test what you fly, and fly what you test". These and other active risk management strategies are in place to deliver the J-2X engine for LEO and lunar return missions as outlined in the U.S. Vision for Space Exploration.

Snoddy, Jimmy R.↗

An Update to a Conformal Ablative Thermal Protection System for Planetary and Human Exploration Missions

As described at IPPW-10, in FY12, the CA-TPS element focused on establishing materials requirements based on MSL-type and COTS Low Earth orbit (LEO) conditions (q 250 Wcm2) to develop and deliver a conformal ablative TPS. This involved down selecting, manufacturing and testing two of the best candidate materials, demonstrating uniform infiltration of resins into baseline 2-cm thick carbon felt, selecting a primary conformal material formulation based on novel arc jet and basic material properties testing, developing and demonstrating instrumentation for felt-based materials and, based on the data, developing a low fidelity material response model so that the conformal ablator TPS thickness for missions could be established. In addition, the project began to develop Industry Partnerships. Since the nominal thickness of baseline carbon felts was only 2-cm, a partnership with a rayon felt developer was made in order to upgrade equipment, establish the processes required and attempt to manufacture 10-cm thick white goods. A partnership with a processing house was made to develop the methodology to carbonize large pieces of the white goods into 7.5-cm thick carbon felt. In FY13, more advanced testing and modeling of the down selected conformal material was performed. Material thermal properties tests and structural properties tests were performed. The first 3 and 4-point bend tests were performed on the conformal ablator as well as PICA for comparison and the conformal ablator had outstanding behavior compared to PICA. Arc jet testing was performed with instrumented samples of both the conformal ablator and standard PICA at heating rates ranging from 40 to 400 Wcm2 and shear as high as 600 Pa. The results from these tests showed a remarkable improvement in the thermal penetration through the conformal ablator when compared to PICAs response. The data from these tests were used to develop a mid-fidelity thermal response model. Additional arc jet testing in the same conditions on various seam designs were very successful in showing that the material could be joined with a minimum of adhesive and required no complicated gap and gap filler design for installation. In addition, the partnership with industry to manufacture thicker rayon felt was very successful. The vendor made a 2-m wide by 30-m long sample of 10-cm thick rayon felt. When carbonized, the resulting thickness was over 7.5-cm thick, nearly 4 times the thickest off-the-shelf carbon felt. In FY14, the project has initiated a partnership with another vendor to begin the scale-up manufacturing effort. This year, the vendor will duplicate the process and manufacture at the current scale for comparison with NASA-processed materials. Properties testing and arc jet testing will be performed on the vendor-processed materials. Planning for manufacturing large, 1-m x 1-m, panels will begin as well. In FY15, the vendor will then manufacture large panels and the project will build a 2-m x 2-m Manufacturing Demonstration Unit (MDU).

Ablative materials↗

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗

Impact of Solar Array Designs on High Voltage Operations

As power levels of advanced spacecraft climb above 25 kW, higher solar array operating voltages become attractive. Even in today s satellites, operating spacecraft buses at 100 V and above has led to arcing in GEO communications satellites, so the issue of spacecraft charging and solar array arcing remains a design problem. In addition, micrometeoroid impacts on all of these arrays can also lead to arcing if the spacecraft is at an elevated potential. For example, tests on space station hardware disclosed arcing at 75V on anodized A1 structures that were struck with hypervelocity particles in Low Earth Orbit (LEO) plasmas. Thus an understanding of these effects is necessary to design reliable high voltage solar arrays of the future, especially in light of the Vision for Space Exploration of NASA. In the future, large GEO communication satellites, lunar bases, solar electric propulsion missions, high power communication systems around Mars can lead to power levels well above 100 kW. As noted above, it will be essential to increase operating voltages of the solar arrays well above 80 V to keep the mass of cabling needed to carry the high currents to an acceptable level. Thus, the purpose of this paper is to discuss various solar array approaches, to discuss the results of testing them at high voltages, in the presence of simulated space plasma and under hypervelocity impact. Three different types of arrays will be considered. One will be a planar array using thin film cells, the second will use planar single or multijunction cells and the last will use the Stretched Lens Array (SLA - 8-fold concentration). Each of these has different approaches for protection from the space environment. The thin film cell based arrays have minimal covering due to their inherent radiation tolerance, conventional GaAs and multijunction cells have the traditional cerium-doped microsheet glasses (of appropriate thickness) that are usually attached with Dow Corning DC 93-500 silicone adhesive. In practice, these cover glasses and adhesive do not cover the cell edges. Finally, in the SLA, the entire cell and cell edges are fully encapsulated by a cover glass that overhangs the cell perimeter and the silicone adhesive covers the cell edges providing a sealed environment. These three types of blanket technology have been tested at GRC and Auburn. The results of these tests will be described. For example, 15 modules composed of four state-of-the-art 2x4 cm GaAs solar cells with 150 pm cover glasses connected in two-cell series strings were tested at high voltage, in plasma under hypervelocity impact. A picture of one of the modules is shown in figure 1. These were prepared by standard industry practice from a major supplier and had efficiencies above 18%. The test results and other fabrication factors that influenced the tests will be presented. In addition, results for SLA segments tested under the same conditions will be presented. Testing of thin film blankets at GRC will also be presented. Figure 1 : Typical GaAs Solar Cell Module These results will show significant differences in resistance to arcing that are directly related to array design and manufacturing procedures. Finally, the approaches for mitigating the problems uncovered by these tests will be described. These will lay the foundation for future higher voltage array operation, even including voltages above 300-600 V for direct drive SEP applications.

Brandhorst, Henry W., Jr.↗

Spacecraft Materials in the Space Flight Environment: International Space Station - May 2002 to May 2007

The performance of ISS spacecraft materials and systems on prolonged exposure to the low-Earth orbit (LEO) space flight is reported in this paper. In-flight data, flight crew observations, and the results of ground-based test and analysis directly supporting programmatic and operational decision-making are presented. The space flight environments definitions (both natural and induced) used for ISS design, material selection, and verification testing are shown, in most cases, to be more severe than the actual flight environment accounting for the outstanding performance of ISS as a long mission duration spacecraft. No significant ISS material or system failures have been attributed to spacecraft-environments interactions. Nonetheless, ISS materials and systems performance data is contributing to our understanding of spacecraft material interactions in the spaceflight environment so as to reduce cost and risk for future spaceflight projects and programs. Orbital inclination (51.6o) and altitude (nominally near 360 km) determine the set of natural environment factors affecting the functional life of materials and systems on ISS. ISS operates in an electrically conducting environment (the F2 region of Earth s ionosphere) with well-defined fluxes of atomic oxygen, other charged and neutral ionospheric plasma species, solar UV, VUV, and x-ray radiation as well as galactic cosmic rays, trapped radiation, and solar cosmic rays (1-4). The LEO micrometeoroid and orbital debris environment is an especially important determinant of spacecraft design and operations (5, 6). The magnitude of several environmental factors varies dramatically with latitude and longitude as ISS orbits the Earth (1-4). The high latitude orbital environment also exposes ISS to higher fluences of trapped energetic electrons, auroral electrons, solar cosmic rays, and galactic cosmic rays (1-4) than would be the case in lower inclination orbits, largely as a result of the overall shape and magnitude of the geomagnetic field (1-4). As a result, ISS exposure to many environmental factors can vary dramatically along a particular orbital ground track, and from one ground track to the next, during any 24-hour period.

Golden, John↗