SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
In this study, we have extensively tested various cleaning protocols. The variant parameters included the type and concentration of solvent, type of wipe, pretreatment conditions, and various rinsing systems. Taguchi statistical method was used to design and evaluate various cleaning conditions on ten common spacecraft materials.
The Diode-laser Array Working Group (DAWG) is a national-level consumer/provider forum for discussion of engineering and manufacturing issues which influence the reliability and survivability of high-power broad-area laser diode devices in space, with an emphasis on laser diode arrays (LDAs) for optical pumping of solid-state laser media. The goals of the group are to formulate and validate standardized test and qualification protocols, operational control recommendations, and consensus manufacturing and certification standards. The group is using reliability and lifetime data collected by laser diode manufacturers and the user community to develop a set of standardized guidelines for specifying and qualifying laser diodes for long-duration operation in space, the ultimate goal being to promote an informed U.S. Government investment and procurement strategy for assuring the availability and durability of space-qualified LDAs. The group is also working to establish effective implementation of statistical design techniques at the supplier design, development, and manufacturing levels to help reduce product performance variability and improve product reliability for diodes employed in space applications
The advent of the Space Shuttle era elevated cardiovascular deconditioning from a research topic in gravitational physiology to a concern with operational consequences during critical space mission phases. NASA has identified three primary cardiovascular risks associate with short-duration (less than 18 d) spaceflight: orthostatic intolerance; decreased maximal oxygen uptake; and cardiac arrhythmias. Orthostatic hypotension (OH) was observed postflight in Mercury astronauts, studied in Gemini and Apollo astronauts, and tracked as it developed in-flight during Skylab missions. A putative hypotensive episode in the pilot during an early shuttle landing, and well documented postflight hypotension in a quarter of crewmembers, catalyzed NASA's research effort to understand its mechanisms and develop countermeasures. Shuttle investigations documented the onset of OH, tested mechanistic hypotheses, and demonstrated countermeasures both simple and complex. Similarly, decreased aerobic capacity in-flight threatened both extravehicular activity and post-landing emergency egress. In one study, peak oxygen uptake and peak power were significantly decreased following flights. Other studies tested hardware and protocols for aerobic conditioning that undergird both current practice on long-duration International Space Station (ISS) missions and plans for interplanetary expeditions. Finally, several studies suggest that cardiac arrhythmias are of less concern during short-duration spaceflight than during long-duration spaceflight. Duration of the QT interval was unchanged and the frequency of premature atrial and ventricular contractions was actually shown to decrease during extravehicular activity. These investigations on short-duration Shuttle flights have paved the way for research aboard long-duration ISS missions and beyond. Efforts are already underway to study the effects of exploration class missions to asteroids and Mars.
Providing web-based data of complex and sensitive astromaterials (including meteorites and lunar samples) in novel formats enhances existing preliminary examination data on these samples and supports targeted sample requests and analyses. We have developed and tested a rigorous protocol for collecting highly detailed imagery of meteorites and complex lunar samples in non-contaminating environments. These data are reduced to create interactive 3D models of the samples. We intend to provide these data as they are acquired on NASA's Astromaterials Acquisition and Curation website at http://curator.jsc.nasa.gov/.
The limitations placed upon human explorers on the surface of Mars will necessitate a methodology for scientific exploration that is different from standard approaches to terrestrial fieldwork and prior crewed exploration of the Moon. In particular, the data transmission limitations and communication latency between Earth and Mars create a unique situation for surface crew in contact with a terrestrial science team. The BASALT research program simulated a series of extravehicular activities (EVAs) in Mars analog terrains under various Mars-relevant bandwidth and latency conditions to investigate how best to approach this problem. Here we discuss tactical decision-making under these conditions, that is, how the crew on Mars interacts with a team of scientists and support personnel on Earth to collect samples of maximum scientific interest. We describe the strategies, protocols, and tools tested in BASALT EVAs and give recommendations on how best to conduct human exploration of Mars with support from Earth-based scientists. We find that even with scientists supporting them, the crew performing the exploration must be trained in the appropriate scientific disciplines in order to provide the terrestrial scientists with enough information to make decisions, but that with appropriate planning and structure, and tools such as a ‘‘dynamic leaderboard,’’ terrestrial scientists can add scientific value to an EVA, even under Mars communication latency
In order for distributed systems to communicate reliably engineers standardize on communication rules (or protocols). Unforeseen behavior in communication protocols can push faults up to applications resulting in uncontrollable systems and should not be tolerated. However, while most modern protocols undergo extensive testing, rigorous formal methods, such as model checking,are rarely used due to complexity and massive incomputable state spaces.
Big data transfer in next-generation scientific applications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application-level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher prediction accuracy in up to 90% of the cases with very noisy real-life performance measurements.
Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.
The purpose of this project is to develop a sterile water based rapid bioburden test. Contamination engineers use two tests to assess the level of biological contamination on hardware: the rapid five minute bioburden test, which is a molecular screening for Adenosine triphosphate (ATP), a molecule found in all cells on the hardware, and a slower colony growth test, which is used to give a more accurate representation of the amount of microbes on the hardware. However, the rapid bioburden test has limited application because it leaves a residue that can be detrimental to sensitive hardware. This can cause project delays while waiting for the results from the three day colony growth test. We address this problem by adapting the commercial germicide based ATP system to a sterile water based system. The test works by reacting ATP with D-Luciferin and Luciferase protein to yield light. The light is then detected by a luminometer that outputs a Relative Light Unit (RLU) amount depending on how much ATP is present. To analyze the effectiveness of the new test, we developed a correlation between amounts of ATP and the RLU produced using the germicide based system. From these experiments, we've generated a consistent relationship between the two in the form of a power curve. From there, we developed a correlation curve between the amount of colonies and the RLU they produced. Initial tests of the new protocol have shown that the water based system isn't as sensitive as the germicide based test.
Pilot's cognitive responses to critical in-flight events (CIFE's) were investigated, using pilots, who had on the average about 2540 flight hours each, in four experiments: (1) full-mission simulation in a general aviation trainer, (2) paper and pencil CIFE tests, (3) interactive computer-aided scenario testing, and (4) verbal protocols in fault diagnosis tasks. The results of both computer and paper and pencil tests showed only 50 percent efficiency in correct diagnosis of critical events. The efficiency in arriving at a diagnosis was also low: over 20 inquiries were made for 21 percent of the scenarios diagnosed. The information-seeking pattern was random, with frequent retracing over old inquiries. The measures for developing improved cognitive skills for CIFE's are discussed.
A publicly available and verified high-flow fueling protocol for H35 medium-duty (MD) and heavy-duty (HD) hydrogen-powered buses and trucks does not exist. This could lead to transit agencies needing to select suppliers for purchase of new fleet vehicles, and to multiple providers responding with incompatible vehicle designs in the future. With the expansion of MD/HD vehicles using 35 MPa storage, there will be a need for publicly accessible H35HF stations, and these will require the use of a standardized prescriptive fueling protocol. The development of a fully tested and validated H35 high-flow (H35HF) MC Formula fueling protocol for MD and HD buses and trucks can provide guidelines to design H35 stations and vehicles, enable other manufacturers and vehicle original equipment manufacturers (OEMs) to enter this space, and ultimately accelerate to popularize the hydrogen market.
Test results from an international round robin are presented. The single cantilever beam (SCB) test was used to characterize face sheet/core disbonding in sandwich components in an effort to help standardization. Each of the seven participating laboratories performed a set of five baseline tests using the same protocol, however, using their own specific equipment. In addition, each laboratory performed two sets of tests with altered tests conditions which included using a test fixture with a translating carriage and performing the tests with different loading and unloading speeds. The orientation of the disbond front with respect to the honeycomb core cells was varied and the effect on the fracture toughness was also studied. Additional factors that could influence test results were investigated, such as the use of a saw cut starter disbond as an alternative to Teflon® release film, and the effects of using a face sheet doubler to increase the bending stiffness. For each set of tests, summary results such as load/displacements plots, observed disbond growth location and calculated energy release rates are reported and a comparison of results between labs is presented. Critical strain energy release rate measurements from SCB tests are also compared with measurements made from an alternative test, namely the double cantilever beam with uneven bending moments (DCB-UBM) test, which has been studied extensively at the Technical University of Denmark and proposed as a mixed-mode test standard. A set of recommendations are made with respect to improving the SCB test and a path to standardization is presented.
The Space Data Link Security (SDLS) Protocol is a Consultative Committee for Space Data Systems (CCSDS) standard which extends the known Data Link protocols to secure data being sent over a space link by providing confidentiality and integrity services. This plan outlines the approach by National Aeronautics Space Administration (NASA) in performing testing of the SDLS protocol using a prototype based on an existing NASA missions simulator.
Not Available
Organic decontamination of sampling and storage devices are crucial steps for life-detection, habitability, and ecological investigations of extremophiles living in the most inhospitable niches of Earth, Mars and elsewhere. However, one of the main stumbling blocks for Mars-analogue life-detection studies in terrestrial remote field-sites is the capability to clean instruments and sampling devices to organic levels consistent with null values. Here we present a new seven-step, multi-reagent cleaning and decontamination protocol that was adapted and tested on a glacial ice-coring device and on a rover-guided scoop used for sediment sampling both deployed multiple times during two field seasons of the Arctic Mars Analog Svalbard Expedition AMASE). The effectiveness of the protocols for both devices was tested by (1)in situ metabolic measurements via APT, (2)in situ lipopolysacchride (LPS) quantifications via low-level endotoxin assays, and(3) laboratory-based molecular detection via gas chromatography-mass spectrometry. Our results show that the combination and step-wise application of disinfectants with oxidative and solvation properties for sterilization are effective at removing cellular remnants and other organic traces to levels necessary for molecular organic- and life-detection studies. The validation of this seven-step protocol - specifically for ice sampling - allows us to proceed with confidence in kmskia4 analogue investigations of icy environments. However, results from a rover scoop test showed that this protocol is also suitable for null-level decontamination of sample acquisition devices. Thus, this protocol may be applicable to a variety of sampling devices and analytical instrumentation used for future astrobiology missions to Enceladus, and Europa, as well as for sample-return missions.
BACKGROUND: Several previous studies indicated that exercise during prebreathe with 100% O2 decreased the incidence of hypobaric decompression sickness (DCS). We report a meta-analysis of these investigations combined with a new study in our laboratory to develop a statistical model as a predictive tool for DCS. HYPOTHESIS: Exercise during prebreathe increases N2 elimination in a theoretical 360-min half-time compartment decreasing the incidence of DCS. METHODS: A dose-response probability tissue ratio (TR) model with 95% confidence limits was created for two groups, prebreathe with exercise (n = 113) and resting prebreathe (n = 113), using nonlinear regression analysis with maximum likelihood optimization. RESULTS: The model predicted that prebreathe exercise would reduce the residual N2 in a 360-min half-time compartment to a level analogous to that in a 180-min compartment. This finding supported the hypothesis. The incidence of DCS for the exercise prebreathe group was significantly decreased (Chi-Square = 17.1, p < 0.0001) from the resting prebreathe group. CONCLUSIONS: The results suggested that exercise during prebreathe increases tissue perfusion and N2 elimination approximately 2-fold and markedly lowers the risk of DCS. Based on the model, the prebreathe duration may be reduced from 240 min to a predicted 91 min for the protocol in our study, but this remains to be verified. The model provides a useful planning tool to develop and test appropriate prebreathe exercise protocols and to predict DCS risks for astronauts.
Dunfield et al. discuss various options for satisfying the ISOS light stability series (ISOS-L-#) of tests, a homebuilt testing apparatus and software suite for such tests, and a case study.
The slide presentation reviews actions taken at Goddard Space Flight Center (GSFC) to eliminate contamination by silicone in clean rooms. Background information includes facilities and hardware affected by silicon contamination, a discussion of the negative aspects of silicone contamination, clean room garments, and how the problem was identified at GSFC. Actions taken by the GSFC Contamination Engineering Group and lessons learned are detailed. Results include: awareness of the silicone issue in laundry, increase in infrastructure and support of the testing lab, establishment of protocols for garment verification, closer relationship established with laundry and converter, specifications for laundry services and garments were strengthened, all consumables are tested before use in clean rooms, and established procedures were used to identify and treat silicone found on face masks.