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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.

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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

New advancements in charge-coupled device technology - Sub-electron noise and 4096 x 4096 pixel CCDs

This paper reports on two new advancements in CCD technology. The first area of development has produced a special purpose CCD designed for ultra low-signal level imaging and spectroscopy applications that require sub-electron read noise floors. A nondestructive output circuit operating near its 1/f noise regime is clocked in a special manner to read a single pixel multiple times. Off-chip electronics average the multiple values, reducing the random noise by the square-root of the number of samples taken. Noise floors below 0.5 electrons rms are reported. The second development involves the design and performance of a high resolution imager of 4096 x 4096 pixels, the largest CCD manufactured in terms of pixel count. The device utilizes a 7.5-micron pixel fabricated with three-level poly-silicon to achieve high yield.

Janesick, James R.↗
NASA NTRS1993

Ultra low-noise charge coupled device

Special purpose CCD designed for ultra low-noise imaging and spectroscopy applications that require subelectron read noise floors, wherein a non-destructive output circuit operating near its 1/f noise regime is clocked in a special manner to read a single pixel multiple times. Off-chip electronics average the multiple values, reducing the random noise by the square-root of the number of samples taken. Noise floors below 0.5 electrons rms are possible in this manner. In a preferred embodiment of the invention, a three-phase CCD horizontal register is used to bring a pixel charge packet to an input gate adjacent a floating gate amplifier. The charge is then repeatedly clocked back and forth between the input gate and the floating gate. Each time the charge is injected into the potential well of the floating gate, it is sensed non-destructively. The floating gate amplifier is provided with a reference voltage of a fixed value and a pre-charge gate for resetting the amplifier between charge samples to a constant gain. After the charge is repeatedly sampled a selected number of times, it is transferred by means of output gates, back into the horizontal register, where it is clocked in a conventional manner to a diffusion MOSFET amplifier. It can then be either sampled (destructively) one more time or otherwise discarded.

Janesick, James R.↗
NASA NTRS2016

Characterization of Evidence for Human System Risk Assessment

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Steinberg, S. L.↗
NASA NTRSDate not supplied

The Integrated Impact of Diet on Human Immune Response, the Gut Microbiota, and Nutritional Status During Adaptation to Spaceflight

Long-duration spaceflight impacts human physiology, including well documented immune system dysregulation. Diet, the microbiome, and immune system function are interlinked, but diet is the only one of these factors that we have the ability to easily, and significantly, alter on Earth or during flight. As we better understand dietary impacts on physiology, we may then improve the spaceflight diet to improve crew health and potentially reduce spaceflight-associated physiological decrements. Increasing the consumption of fruits and vegetables and bioactive compounds (e.g., omega-3 fatty acids, lycopene, flavonoids) and therefore enhancing overall nutritional intake from the nominal shelf-stable, fully-processed, space food system is expected to serve as a countermeasure to detrimental impacts to human physiology, including dysregulation in immunological profiles, the taxonomic profile of the gut microbiota, and nutritional status during spaceflight. In this study, first we sought to determine the effect of the nominal shelf-stable spaceflight diet compared to an "enhanced" shelf-stable spaceflight diet on human biochemistry, immunology, and the microbiome in a ground-based, simulated space mission. The ground analog portion of this study was conducted in the NASA Human Exploration Research Analog (HERA) Campaign 4 missions, which consisted of four 45-day missions with closed chamber confinement and realistic mission simulation to study effects on crew health and performance. As reported previously, analyses indicate beneficial associations between diet and markers of nutritional status, stress, the microbiome, and cognitive performance. Intake and beneficial associations varied by subject. This data will be used as a ground-based control for spaceflight, where the spaceflight environment (e.g., radiation, microgravity) will have additional impacts and the potential to evaluate effects of the diet will be greater. The second phase of this study is to occur on the International Space Station, where it is currently being implemented. The test plan is similar to that used in the HERA missions. The enhanced diet is intended to provide 25% of the crews’ diet with foods rich in omega-3 fatty acids, lycopene, and flavonoids, along with more fruits and vegetables in general (the other 75% of the diet will be obtained from standard and crew preference items available on the ISS). Biological samples (blood, urine, stool, and saliva) are being collected from participants at selected time points before, during, and after the mission. Data collection also includes dietary intake recording and body mass measurement. Currently, 6 of 9 planned astronauts have completed data collection. Analysis of immune markers, latent herpes virus reactivation, the taxonomic and metatranscriptomic profile of the gut microbiome, and nutritional status biomarkers and biochemical metabolites will occur in batch to minimize sample handling variations. Mixed models statistical analyses will be used, incorporating random effects to account for repeated measures within individuals to assess the impact of diet on physiological outcomes. We expect this study to provide evidence of beneficial impact of this enhanced diet on crew health and adaptation to spaceflight. These data will aid in evidence-based mass-risk trades for food system design and development of targeted dietary interventions for future exploration-class space missions.

Grace L. Douglas↗
DOE OSTI2019

A study of defect structures in Fe-alloyed ZnO: Morphology, magnetism, and hyperfine interactions

In order to study the effect of Fe cation substitution on the local structure, defect formation, and hyperfine interactions in ZnO, Mössbauer spectroscopy measurements of the microwave processed Zn 1 - x Fe x O (x = 0.05, 0.10, 0.15, and 0.20) nanoparticles, together with ab initio calculations, were performed. Complementary information on the distribution of particle size and morphology, as well as magnetic properties, were obtained by X-ray diffraction, transmission electron microscopy, and squid-magnetometry. The selected model for analyzing the Mössbauer spectra of our samples is a distribution of quadrupole splittings. The fitting model with two Lorentz doublets was rejected due to its failure to include larger doublets. The Fe 3 + ions do not yield magnetic ordering in the samples at room temperature. The results from first-principles calculations confirm that the major component of the Mössbauer spectra corresponds to the Fe-alloyed ZnO with Zn vacancy in the next nearest neighbor environment. The magnetic measurements are consistent with the description of the distribution of iron ions over the randomly formed clusters in the ZnO host lattice. While at room temperature all the samples are paramagnetic, magnetic interactions cause a transition into a cluster spin-glass state at low temperatures. © 2019 Author(s).

60 APPLIED LIFE SCIENCES↗
NASA NTRS2024

Cognitive Performance in ISS Astronauts on 6-Month Low Earth Orbit Missions

Introduction: Current and future astronauts will endure prolonged exposure to spaceflight hazards and environmental stressors that could compromise cognitive functioning, yet cognitive performance in current missions to the International Space Station remains critically under-characterized. We systematically assessed cognitive performance across 10 cognitive domains in astronauts on 6-month missions to the ISS. Methods: Twenty-five professional astronauts were administered the Cognition Battery as part of National Aeronautics and Space Administration (NASA) Human Research Program Standard Measures Cross-Cutting Project. Cognitive performance data were collected at five mission phases: pre-flight, early flight, late flight, early post-flight, and late post-flight. We calculated speed and accuracy scores, corrected for practice effects, and derived z-scores to represent deviations in cognitive performance across mission phases from the sample’s mean baseline (i.e., pre-flight) performance. Linear mixed models with random subject intercepts and pairwise comparisons examined the relationships between mission phase and cognitive performance. Results: Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. There was slowed performance observed in early flight on tasks of processing speed, visual working memory, and sustained attention. We observed a decrease in risk-taking propensity during late flight and post-flight mission phases. Beyond examining group differences, we inspected scores that represented a significant shift from the sample’s mean baseline score, revealing that 11.8% of all flight and post-flight scores were at or below 1.5 standard deviations below the sample’s baseline mean. Finally, exploratory analyses yielded no clear pattern of associations between cognitive performance and either sleep or ratings of alertness. Conclusions: There was no evidence for a systematic decline in cognitive performance for astronauts on a 6-month missions to the ISS. Some differences were observed for specific subtests at specific mission phases, suggesting that processing speed, visual working memory, sustained attention, and risk-taking propensity may be the cognitive domains most susceptible to change in Low Earth Orbit for high performing, professional astronauts. We provide descriptive statistics of pre-flight cognitive performance from 25 astronauts, the largest published preliminary normative database of its kind to date, to help identify significant performance decrements in future samples.

Data curation↗
DOE OSTI2017

APT malware static trace analysis through bigrams and graph edit distance

Research and business organizations are vulnerable to attack by malware, particularly advanced persistent threat malware tailored for a specific target. Malware identification is made more difficult because samples can be subtly altered to avoid detection by methods that check for an identical match to known code. Different versions of an original piece of malware form a malware family. And when new malicious software is identified, reverse engineers seek to identify its origin and purpose. Knowing whether new malware is from a known family or a previously unobserved family aids the efficiency of reverse engineers. Furthermore, this article presents a three-stage method to classify new malware into a family by comparing its similarity to existing static traces, and assigning it to the most similar family. First, a fast filtering method creates a shortlist of samples with some similarity to the new malware, using a simple bigram comparison of the instructions. The second stage takes the call graph view of the shortlisted static traces and uses simulated annealing to estimate the graph edit distance, a measure of dissimilarity between graphs. Finally, a random forest classifier combines the previous two results to predict the family to which a new sample belongs. Our paper also considers how to detect when malware is from a new family.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Statistical model for asperity-contact time fraction in elastohydrodynamic lubrication

Relations for the asperity contact time fraction during elastohydrodynamic (EHD) lubrication of a typical ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces were used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately 4 to 5. This thickness ratio is several times larger than reported in the literature where one-dimensional random surface models were used.

Sidik, S. M.↗
NASA NTRS1979

Two-dimensional random surface model for asperity-contact in elastohydrodynamic lubrication

Relations for the asperity-contact time function during elastohydrodynamic lubrication of a ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces are used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately four to five. This thickness ratio is several times large than reported in the literature where one-dimensional random surface models were used. It is shown that low pass filtering of the statistical records will bring agreement between the present results and those in the literature.

Coy, J. J.↗
NASA NTRS1979

Two-dimensional random surface model for asperity-contact in elastohydrodynamic lubrication

Relations for the asperity-contact time fraction during elastohydrodynamic lubrication of a ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces are used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately four to five. This thickness ratio is several times larger than reported in the literature where one-dimensional random surface models were used. It is shown that low pass filtering of the statistical records will bring agreement between the present results and those in the literature.

Coy, J. J.↗
NASA NTRS1981

Correlation function studies for snow and ice

The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.

Vallese, F.↗
DOE OSTI2021

Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. Furthermore, the proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2024

Classifying Microwave Radiometer Observations Over the Netherlands Into Dry, Shallow-, and Non-Shallow Precipitation Using A Random Forest Model

Spaceborne microwave radiometers represent an important component of the Global Precipitation Measurement (GPM) mission due to their frequent sampling of rain systems. Microwave radiometers measure microwave radiation (brightness temperatures, Tb), which can be converted into precipitation estimates with appropriate assumptions. However, detecting shallow precipitation systems using space-borne radiometers is challenging, especially over land, as their weak signals are hard to differentiate from those associated with dry conditions. This study uses a random forest model (RF) to classify microwave radiometer observations as dry, shallow, or nonshallow over the Netherlands - a region with varying surface conditions and frequent occurrence of shallow precipitation. The RF is trained on five years of data (2016-2020) and tested with two independent years (2015, 2021). The observations are classified using ground-based weather radar echo top heights. Various RF models are assessed, such as using only GPM’s Microwave Imager (GMI) Tb values as input features or including spatially aligned ERA-5 2-meter temperature and freezing level reanalysis and/or Dual Precipitation Radar (DPR) observations. Independent of the input features, the model performs best in summer and worst in winter. The model classifies observations from high-frequency channels (≥85 GHz) with lower Tb-values as non-shallow, higher values as dry, and those in between as shallow. Misclassified footprints exhibit radiometric characteristics corresponding to their assigned class. Case studies reveal dry observations misclassified as shallow are associated with lower Tb-values, likely resulting from the presence of ice particles in non-precipitating clouds. Shallow footprints misclassified as dry are likely related to the absence of ice particles.

Linda Bogerd↗
DOE OSTI2017

Improving Estimation of Betweenness Centrality for Scale-Free Graphs

Betweenness centrality is a graph statistic used to nd vertices that are participants in a large number of shortest paths in a graph. This centrality measure is commonly used in path and network interdiction problems and its complete form requires the calculation of all-pairs shortest paths for each vertex. This leads to a time complexity of O(jV jjEj), which is impractical for large graphs. Estimation of betweenness centrality has focused on performing shortest-path calculations on a subset of randomly- selected vertices. This reduces the complexity of the centrality estimation to O(jSjjEj); jSj < jV j, which can be scaled appropriately based on the computing resources available. An estimation strategy that uses random selection of vertices for seed selection is fast and simple to implement, but may not provide optimal estimation of betweenness centrality when the number of samples is constrained. Our experimentation has identi ed a number of alternate seed-selection strategies that provide lower error than random selection in common scale-free graphs. These strategies are discussed and experimental results are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Note: Non-invasive optical method for rapid determination of alignment degree of oriented nanofibrous layers

This paper presents a rapid non-destructive method that provides information on the anisotropic internal structure of nanofibrous layers. A laser beam of a wavelength of 632.8 nm is directed at and passes through a nanofibrous layer prepared by electrostatic spinning. Information about the structural arrangement of nanofibers in the layer is directly visible in the form of a diffraction image formed on a projection screen or obtained from measured intensities of the laser beam passing through the sample which are determined by the dependency of the angle of the main direction of polarization of the laser beam on the axis of alignment of nanofibers in the sample. Both optical methods were verified on Polyvinyl alcohol (PVA) nanofibrous layers (fiber diameter of 470 nm) with random, single-axis aligned and crossed structures. The obtained results match the results of commonly used methods which apply the analysis of electron microscope images. The presented simple method not only allows samples to be analysed much more rapidly and without damaging them but it also makes possible the analysis of much larger areas, up to several square millimetres, at the same time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis

Abstract Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb‐makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave‐one‐out cross‐validation. Averaging the classification accuracies for the two LDA‐based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

Ommen, Danica M.↗
NASA NTRS1995

Genetic algorithms as global random search methods

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Peck, Charles C.↗
NASA NTRS1995

Genetic algorithms as global random search methods

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Peck, Charles C.↗