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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 109 records · Page 6

Thermal Imaging with Novel Infrared Focal Plane Arrays and Quantitative Analysis of Thermal Imagery

We have developed a single long-wavelength infrared (LWIR) quantum well infrared photodetector (QWIP) camera for thermography. This camera has been used to measure the temperature profile of patients. A pixel coregistered simultaneously reading mid-wavelength infrared (MWIR)/LWIR dual-band QWIP camera was developed to improve the accuracy of temperature measurements especially with objects with unknown emissivity. Even the dualband measurement can provide inaccurate results due to the fact that emissivity is a function of wavelength. Thus we have been developing a four-band QWIP camera for accurate temperature measurement of remote object.

Thermography↗

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗

A Quantitative Analysis of Systematic Differences in the Positions and Proper Motions of Gaia DR2 with Respect to VLBI

We have analysed the differences in positions of 9081 matched sources between the GaiaData Release 2 (DR2) and very long baseline interferometry (VLBI) catalogues. The medianposition uncertainty of matched sources in the VLBI catalogue is a factor of two larger thanthe median position uncertainty in Gaia DR2. There are 9 per cent matched sources withstatistically significant offsets between both catalogues. We found that the reported positionalerrors should be rescaled by a factor of 1.3 for VLBI and 1.06 for Gaia and, in addition, the Gaiaerrors should be multiplied by the square root of chi squared per degree of freedom in order tobest fit the normalized position differences to the Rayleigh distribution. We have establishedthat the major contributor to statistically significant position offsets is the presence of opticaljets. Among the sources for which the jet direction was determined, the position offsets areparallel to the jet directions for 62 per cent of the outliers. Among the matched sources withsignificant proper motion, the fraction of objects with proper motion directions parallel tojets is a factor of three greater than on average. Such sources have systematically higher chisquared per degree of freedom. We explain these proper motions as a manifestation of thesource position jitter caused by flares, which we predicted earlier. Therefore, the assumptionthat quasars are fixed points, and thus that differential proper motions determined with respectto quasar photocentres can be regarded as absolute proper motions, should be treated withgreat caution.

Petrov, L.↗

A Quantitative Analysis On the Use Of Supervised Machine Learning in Earth Science

Several recent papers have investigated different challenges in applying machine learning (ML) techniques to Earth science problems. The challenges listed range from interpretability of the results to computational demand to data issues. In this paper, we focus on specific challenges listed in the review papers that are centered around training data, as the size of training data is important in applying deep learning (DL) techniques. We are in the process of conducting a literature survey to better understand these challenges as well as to understand any trends. As part of this survey, our review has encompassed Earth science papers from AGU, AMS, IEEE and SPIE journals covering the last ten years and focused on papers that utilize supervised ML techniques.

Katrina S Virts↗

A Quantitative Analysis on the Use of Supervised Machine Learning in Earth Science

Recent review papers (Ball et al., 2017; Reichstein et al., 2019) have investigated the opportunities and challenges in applying supervised machine learning (ML) techniques to Earth science problems. A common challenge is the lack of training (or labeled) data. Supervised ML, and especially deep learning (DL), require large training datasets. While there are large, open access Earth science archives, the data typically require preprocessing in preparation for supervised ML, frequently including manual labeling. Our objective is to understand the landscape of supervised ML in the Earth sciences, including which research communities have most rapidly adopted supervised ML, which algorithms are applied, and what data are used to train these algorithms. We conducted a literature survey of Earth science papers published during the last 10 years in journals from the American Geophysical Union (AGU), American Meteorological Society (AMS), the Institute of Electrical and Electronics Engineers(IEEE), and the Society of Photo-Optical Instrumentation Engineers (SPIE). We identified papers containing the terms ML, DL, or the names of individual supervised ML algorithms. "Earth science" is an additional required search term for IEEE and SPIE. We investigate trends in supervised ML usage during the 10-year study period, and manually analyzed AGU papers from 2018-2019 to enable deep-dive statistics.

Katrina S Virts↗

Quantitative analysis of charge injection and discharging of Si nanocrystals and arrays by electrostatic force microscopy

NASA requirements for computing and memory for microspacecraft emphasizes high density, low power, small size, and radiation hardness. The distributed nature of a storage elements in nanocrystal floating-gate memories leads to instrinsic fault tolerance and radiation-hardness. Nanocrystal-based memories also offer the possibility of a faster, lower power operation.

atomic↗

Quantitative Analysis of Spaceflight Drug Stability Data to Support a Predictive Pharmaceutical Testing Strategy

To systematically quantify the time-dependent effect of spaceflight on active pharmaceutical ingredient (API) degradation, data were extracted from available published and unpublished spaceflight drug stability studies. Seven studies were identified that investigated the stability of individual medications following storage aboard crewed spacecraft. Medications stored for up to 2.4 years in low earth orbit (LEO) show limited change in API potency that, in all cases, falls within 10% of matched terrestrial controls, and within 5% of controls for the most drugs. This investigation shows that spaceflight is associated with a ~1.5-fold increase in the degradation rate relative to lot-matched terrestrial controls. Spaceflight is associated with an increased probability of drug failure over time; however, the incremental increase in degradation risk associated with spaceflight is minor compared to the baseline risk associated with terrestrial controls. Since most drugs across all NASA-supported studies were repackaged solid oral formulations that had been removed from protective manufacturer packaging, it is likely that prolonged exposure to atmospheric factors during both terrestrial and spaceflight treatments is a key contributor to degradation. Unique spaceflight environmental factors, particularly ionizing radiation and elevated CO2, may contribute to the additional cumulative effect of spaceflight. The results of this study show that the effect of spaceflight on drug stability is minor relative to the terrestrial baseline; however, the degradation rate and time-dependent failure of terrestrial controls highlights an extremely critical need to evaluate the effect of current repackaging methods and development of operationally appropriate methods to protected repackaged solid oral medications from environmental factors that mediate degradation.

J F Reichard↗

Applying Qualitative Hazard Analysis to Support Quantitative Safety Analysis for Proposed Reduced Wake Separation Conops

This paper describes a scenario-driven hazard analysis process to identify, eliminate, and control safety-related risks. Within this process, we develop selective criteria to determine the applicability of applying engineering modeling to hypothesized hazard scenarios. This provides a basis for evaluating and prioritizing the scenarios as candidates for further quantitative analysis. We have applied this methodology to proposed concepts of operations for reduced wake separation for closely spaced parallel runways. For arrivals, the process identified 43 core hazard scenarios. Of these, we classified 12 as appropriate for further quantitative modeling, 24 that should be mitigated through controls, recommendations, and / or procedures (that is, scenarios not appropriate for quantitative modeling), and 7 that have the lowest priority for further analysis.

Shortle, John F.↗

Hypergravity exposure decreases gamma-aminobutyric acid immunoreactivity in axon terminals contacting pyramidal cells in the rat somatosensory cortex: a quantitative immunocytochemical image analysis

Quantitative evaluation of gamma-aminobutyric acid immunoreactivity (GABA-IR) in the hindlimb representation of the rat somatosensory cortex after 14 days of exposure to hypergravity (hyper-G) was conducted by using computer-assisted image processing. The area of GABA-IR axosomatic terminals apposed to pyramidal cells of cortical layer V was reduced in rats exposed to hyper-G compared with control rats, which were exposed either to rotation alone or to vivarium conditions. Based on previous immunocytochemical and behavioral studies, we suggest that this reduction is due to changes in sensory feedback information from muscle receptors. Consequently, priorities for muscle recruitment are altered at the cortical level, and a new pattern of muscle activity is thus generated. It is proposed that the reduction observed in GABA-IR of the terminal area around pyramidal neurons is the immunocytochemical expression of changes in the activity of GABAergic cells that participate in reprogramming motor outputs to achieve effective movement control in response to alterations in the afferent information.

Non-NASA Center↗

Multivariate Quantitative Chemical Analysis

Technique of multivariate quantitative chemical analysis devised for use in determining relative proportions of two components mixed and sprayed together onto object to form thermally insulating foam. Potentially adaptable to other materials, especially in process-monitoring applications in which necessary to know and control critical properties of products via quantitative chemical analyses of products. In addition to chemical composition, also used to determine such physical properties as densities and strengths.

Kinchen, David G.↗

Neurofilament protein defines regional patterns of cortical organization in the macaque monkey visual system: a quantitative immunohistochemical analysis

Visual function in monkeys is subserved at the cortical level by a large number of areas defined by their specific physiological properties and connectivity patterns. For most of these cortical fields, a precise index of their degree of anatomical specialization has not yet been defined, although many regional patterns have been described using Nissl or myelin stains. In the present study, an attempt has been made to elucidate the regional characteristics, and to varying degrees boundaries, of several visual cortical areas in the macaque monkey using an antibody to neurofilament protein (SMI32). This antibody labels a subset of pyramidal neurons with highly specific regional and laminar distribution patterns in the cerebral cortex. Based on the staining patterns and regional quantitative analysis, as many as 28 cortical fields were reliably identified. Each field had a homogeneous distribution of labeled neurons, except area V1, where increases in layer IVB cell and in Meynert cell counts paralleled the increase in the degree of eccentricity in the visual field representation. Within the occipitotemporal pathway, areas V3 and V4 and fields in the inferior temporal cortex were characterized by a distinct population of neurofilament-rich neurons in layers II-IIIa, whereas areas located in the parietal cortex and part of the occipitoparietal pathway had a consistent population of large labeled neurons in layer Va. The mediotemporal areas MT and MST displayed a distinct population of densely labeled neurons in layer VI. Quantitative analysis of the laminar distribution of the labeled neurons demonstrated that the visual cortical areas could be grouped in four hierarchical levels based on the ratio of neuron counts between infragranular and supragranular layers, with the first (areas V1, V2, V3, and V3A) and third (temporal and parietal regions) levels characterized by low ratios and the second (areas MT, MST, and V4) and fourth (frontal regions) levels characterized by high to very high ratios. Such density trends may correspond to differential representation of corticocortically (and corticosubcortically) projecting neurons at several functional steps in the integration of the visual stimuli. In this context, it is possible that neurofilament protein is crucial for the unique capacity of certain subsets of neurons to perform the highly precise mapping functions of the monkey visual system.

Non-NASA Center↗

Quantitative multielement analysis using high energy particle bombardment

Charged particles ranging in energy from 0.8 to 4.0 MeV are used to induce resonant nuclear reactions, Coulomb excitation (gamma-rays), and X-ray emission in both thick and thin targets. Quantitative analysis is possible for elements from Li to Pb in complex environmental samples, although the matrix can severely reduce the sensitivity. It is necessary to use a comparator technique for the gamma-rays while for X-rays an internal standard can be used. A USGS standard rock is analyzed for a total of 28 elements. Water samples can be analyzed either by nebulizing the sample doped with Cs or Y a thin Formvar film or by extracting the sample onto ion exchange resin which is pressed into a pellet.

Clark, P. J.↗