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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 199 records · Page 11

Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of the GLAS is a full acquisition of the surface return pulse, which has important application to the atmospheric transmission retrieval.

Spinhirne, James D.↗

The Effects of Blade Count on Boundary Layer Development in a Low-Pressure Turbine

Experimental data from jet-engine tests have indicated that turbine efficiencies at takeoff can be as much as two points higher than those at cruise conditions. Recent studies have shown that Reynolds number effects contribute to the lower efficiencies at cruise conditions. In the current study numerical simulations have been performed to study the boundary layer development in a two-stage low-pressure turbine, and to evaluate the models available for low Reynolds number flows in turbomachinery. In a previous study using the same geometry the predicted time-averaged boundary layer quantities showed excellent agreement with the experimental data, but the predicted unsteady results showed only fair agreement with the experimental data. It was surmised that the blade count approximation used in the numerical simulations generated more unsteadiness than was observed in the experiments. In this study a more accurate blade approximation has been used to model the turbine, and the method of post-processing the boundary layer information has been modified to more closely resemble the process used in the experiments. The predicted results show improved agreement with the unsteady experimental data.

Dorney, Daniel J.↗

High intensity surge and seasonal effects in the dark current of the Nimbus-4 BUV experiment

Seasonal global maps of the dark current produced by corpuscular radiation contributing to the background level of the Nimbus-4 Backscattered Ultraviolet (BUV) instrument were developed, using BUV monochrometer nighttime data in the pulse counting mode during solar and magnetically quiet periods. The existence of high intensity surges has been discovered which occur on a sporadic basis and which cause sufficient enhancements of dark current within the subauroral regions to produce background levels similar to those within the South Atlantic anomaly. Examples are provided of the nominal quiet dark current intensity maps, and the variability and implications of the surge data are discussed.

Stassinopoulos, E. G.↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

LDEF contaminants analysis data

Modification of surface texture for Ram Facing FEP Teflon on the Long Duration Exposure Facility (LDEF) satellite is documented. Photos of changes in surface texture if thermal blanket material with position on tray C-08 are presented. Infrared spectra and photographic documentation of molecular film deposits on LDEF surfaces by location is reported. Results of a survey of the functional groups and elemental composition of the brown film found widely distributed on the surface of LDEF is shown. A partial photographic catalog of LDEF particulate contaminants is included. A set of photos of particles collected or photographed in place on the surface of LDEF is shown. Particle counts and surface obscuration data for the LDEF satellite are reported. The surface data in tables and charts is presented for the LDEF satellite by location.

Crutcher, E. Russ↗

Icy Satellites of Saturn: Impact Cratering and Age Determination

Saturn is the first giant planet to be visited by an orbiting spacecraft that can transmit large amounts of data to Earth. Crater counts on satellites from Phoebe inward to the regular satellites and ring moons are providing unprecedented insights into the origin and time histories of the impacting populations. Many Voyager-era scientists concluded that the satellites had been struck by at least two populations of impactors. In this view, the Population I impactors, which were generally judged to be comets orbiting the Sun, formed most of the larger and older craters, while Population II impactors, interpreted as Saturn-orbiting ejecta from impacts on satellites, produced most of the smaller and younger craters. Voyager data also implied that all of the ring moons, and probably some of the midsized classical moons, had been catastrophically disrupted and reaccreted since they formed. We examine models of the primary impactor populations in the Saturn system. At the present time, ecliptic comets, which likely originate in the Kuiper belt/scattered disk, are predicted to dominate impacts on the regular satellites and ring moons, but the models require extrapolations in size (from the observed Kuiper belt objects to the much smaller bodies that produce the craters) or in distance (from the known active Jupiter family comets to 9.5 AU). Phoebe, Iapetus, and perhaps even moons closer to Saturn have been struck by irregular satellites as well. We describe the Nice model, which provides a plausible mechanism by which the entire Solar System might have experienced an era of heavy bombardment long after the planets formed. We then discuss the three cratering chronologies, including one based upon the Nice model, that have been used to infer surface ages from crater densities on the saturnian satellites. After reviewing scaling relations between the properties of impactors and the craters they produce, we provide model estimates of the present-day rate at which comets impact, and catastrophically disrupt, the saturnian moons. Finally, we present crater counts on the satellites from two different groups. Many of the heavily cratered terrains appear to be nearly saturated, so it is difficult to infer the provenance of the impactors from crater counts alone. More large craters have been found on Iapetus than on any other satellite. Enceladus displays an enormous range of surface ages, ranging from the old mid-latitude plains to the extremely young South Polar Terrain. Cassini images provide some evidence for the reality of Population II. Most of the observed craters may have formed in one or more cataclysms, but more work is needed to determine the roles of heliocentric and planetocentric bodies in creating the craters.

Dones, L.↗

Optical-communication systems for deep-space applications

The feasibility of using optical communication systems for data telemetry from deep space vehicles to Earth based receivers is evaluated. Performance analysis shows that practical, photon counting optical systems can transmit data reliably at 30 to 40 dB high rates than existing RF systems, or can be used to extend the communication range by 15 to 20 dB. The advantages of pulse-position modulation (PPM) formats are discussed, and photon counting receiver structures designed for PPM decoding are described. The effects of background interference and weather on receiver performance are evaluated. Some consideration is given to tracking and beam pointing operations, since system performance ultimately depends on the accuracy to which these operations can be carried out. An example of a tracking and pointing system utilizing an optical uplink beacon is presented, and it is shown that microradian beam pointing is within the capabilities of state-of-the-art technology. Recommendations for future theoretical studies and component development programs are presented.

Vilnrotter, V. A.↗

SEDS: The Spitzer Extended Deep Survey. Survey Design, Photometry, and Deep IRAC Source Counts

The Spitzer Extended Deep Survey (SEDS) is a very deep infrared survey within five well-known extragalactic science fields: the UKIDSS Ultra-Deep Survey, the Extended Chandra Deep Field South, COSMOS, the Hubble Deep Field North, and the Extended Groth Strip. SEDS covers a total area of 1.46 deg(exp 2) to a depth of 26 AB mag (3sigma) in both of the warm Infrared Array Camera (IRAC) bands at 3.6 and 4.5 micron. Because of its uniform depth of coverage in so many widely-separated fields, SEDS is subject to roughly 25% smaller errors due to cosmic variance than a single-field survey of the same size. SEDS was designed to detect and characterize galaxies from intermediate to high redshifts (z = 2-7) with a built-in means of assessing the impact of cosmic variance on the individual fields. Because the full SEDS depth was accumulated in at least three separate visits to each field, typically with six-month intervals between visits, SEDS also furnishes an opportunity to assess the infrared variability of faint objects. This paper describes the SEDS survey design, processing, and publicly-available data products. Deep IRAC counts for the more than 300,000 galaxies detected by SEDS are consistent with models based on known galaxy populations. Discrete IRAC sources contribute 5.6 +/- 1.0 and 4.4 +/- 0.8 nW / square m/sr at 3.6 and 4.5 micron to the diffuse cosmic infrared background (CIB). IRAC sources cannot contribute more than half of the total CIB flux estimated from DIRBE data. Barring an unexpected error in the DIRBE flux estimates, half the CIB flux must therefore come from a diffuse component.

Spitzer↗

Eight-Channel Continuous Timer

A custom laboratory electronic timer circuit measures the durations of successive cycles of nominally highly stable input clock signals in as many as eight channels, for the purpose of statistically quantifying the small instabilities of these signals. The measurement data generated by this timer are sent to a personal computer running software that integrates the measurements to form a phase residual for each channel and uses the phase residuals to compute Allan variances for each channel. (The Allan variance is a standard statistical measure of instability of a clock signal.) Like other laboratory clock-cycle-measuring circuits, this timer utilizes an externally generated reference clock signal having a known frequency (100 MHz) much higher than the frequencies of the input clock signals (between 100 and 120 Hz). It counts the number of reference-clock cycles that occur between successive rising edges of each input clock signal of interest, thereby affording a measurement of the input clock-signal period to within the duration (10 ns) of one reference clock cycle. Unlike typical prior laboratory clock-cycle-measuring circuits, this timer does not skip some cycles of the input clock signals. The non-cycle-skipping feature is an important advantage because in applications that involve integration of measurements over long times for characterizing nominally highly stable clock signals, skipping cycles can degrade accuracy. The timer includes a field-programmable gate array that functions as a 20-bit counter running at the reference clock rate of 100 MHz. The timer also includes eight 20-bit latching circuits - one for each channel - at the output terminals of the counter. Each transition of an input signal from low to high causes the corresponding latching circuit to latch the count at that instant. Each such transition also sets a status flip-flop circuit to indicate the presence of the latched count. A microcontroller reads the values of all eight status flipflops and then reads the latched count for each channel for which the flip-flop indicates the presence of a count. Reading the count for each channel automatically causes the flipflop of that channel to be reset. The microcontroller places the counts in time order, identifies the channel number for each count, and transmits these data to the personal computer.

Cole, Steven↗

Performance Assessment of Different Pulse Reconstruction Algorithms for the ATHENA X-Ray Integral Field Unit

The X-ray Integral Field Unit (X-IFU) microcalorimeter, on-board Athena, with its focal plane comprising 3840 Transition Edge Sensors (TESs) operating at 90 mK, will provide unprecedented spectral-imaging capability in the 0.2-12 keV energy range. It will rely on the on-board digital processing of current pulses induced by the heat deposited in the TES absorber, as to recover the energy of each individual events. Assessing the capabilities of the pulse reconstruction is required to understand the overall scientific performance of the X-IFU, notably in terms of energy resolution degradation with both increasing energies and count rates. Using synthetic data streams generated by the X-IFU End-to-End simulator, we present here a comprehensive benchmark of various pulse reconstruction techniques, ranging from standard optimal filtering to more advanced algorithms based on noise covariance matrices. Beside deriving the spectral resolution achieved by the different algorithms, a first assessment of the computing power and ground calibration needs is presented. Overall, all methods show similar performances, with the reconstruction based on noise covariance matrices showing the best improvement with respect to the standard optimal filtering technique. Due to prohibitive calibration needs, this method might however not be applicable to the X-IFU and the best compromise currently appears to be the so-called resistance space analysis which also features very promising high count rate capabilities.

microcalorimeters↗

Comparison of Computational Aeroacoustics Prediction of Acoustic Transmission Through a 3D Stator With Experiment

In this paper, numerical predictions of acoustic transmission through a 3D stator obtained using the NASA BASS code are compared with experimentally measured data. The influence of vane count and stagger as well as frequency and mode order on the transmission loss is investigated. The data-theory comparisons indicate that BASS can predict all the important trends observed in the experimental data.

Hixon, Ray↗

Comparison of Computational Aeroacoustics Prediction of Acoustic Transmission Through a 3D Stator with Experiment

In this paper, numerical predictions of acoustic transmission through a 3D stator obtained using the NASA BASS code are compared with experimentally measured data. The influence of vane count and stagger as well as frequency and mode order on the transmission loss is investigated. The data-theory comparisons indicate that BASS can predict all the important trends observed in the experimental data.

Hixon, Ray↗

Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty

This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help domain scientists analyze potential positions of sources (positive divergence) and sinks (negative divergence) in the flow. However, uncertainty inherent in vector field data can lead to erroneous divergence computations, adversely impacting downstream analysis. While Monte Carlo (MC) sampling is a classical approach for estimating divergence uncertainty, it suffers from slow convergence and poor scalability with increasing data size and sample counts. Thus, we present a two-fold contribution that tackles the challenges of slow convergence and limited scalability of the MC approach. (1) We derive a closed-form approach for highly efficient and accurate uncertainty visualization of local divergence, assuming independently Gaussian-distributed vector uncertainties. (2) We further integrate our approach into Viskores, a platform-portable parallel library, to accelerate uncertainty visualization. In our results, we demonstrate significantly enhanced efficiency and accuracy of our serial analytical (speed-up up to 1946×) and parallel Viskores (speed-up up to 19698×) algorithms over the classical serial MC approach. We also demonstrate qualitative improvements of our probabilistic divergence visualizations over traditional mean-field visualization, which disregards uncertainty. We validate the accuracy and efficiency of our methods on wind forecast and ocean simulation datasets.

Ouermi, Timbwaoga [University of Utah]↗

In-progress absolute radiometric inflight calibration of the LANDSAT-4 sensors

An approach is described for providing periodic inflight absolute radiometric calibrations of the LANDSAT-4 sensors by reference to selected, instrumented ground areas. Results of some early ground measurements and computer simulations are presented. Selection of a suitable ground reference site, accurate measurement of the spectral reflectance of the selected area, determination of atmospheric characteristics during the morning of the sensor overpass, reduction of the measured data and their use in an appropriate atmospheric radiative transfer program, and comparison of the radiance level data with the digital counts of for the images of the selected areas are discussed. Preliminary measurements of gypsum are being made as an aid in defining the characteristics of field equipment to be constructed and calibrated for use over the White Sands Missile Range.

Castle, K.↗