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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluating Automated Face Identity-Masking Methods with Human Perception and a Deep Convolutional Neural Network

Face de-identification (or “masking”) algorithms have been developed in response to the prevalent use of video recordings in public places. Here, we evaluated the success of face identity masking for human perceivers and a deep convolutional neural network (DCNN). Eight de-identification algorithms were applied to videos of drivers’ faces, while they actively operated a motor vehicle. These masks were pre-selected to be applicable to low-quality video and to maintain coarse information about facial actions. Humans studied high-resolution images to learn driver identities and were tested on their recognition of active drivers in low-resolution videos. Faces in the videos were either unmasked or were masked by one of the eight algorithms. When participants were tested immediately after learning (Experiment 1), all masks reduced identification, with six of eight masks reducing identification to extremely poor performance. In a second experiment, two of the most effective masks were tested after a delay of 7 or 28 days. The delay did not further reduce identification of the masked faces. In all masked conditions, participants maintained stringent decision criteria, with low confidence in recognition, further indicating the effectiveness of the masks. Next, the DCNN performed an identity-matching task between high-resolution images and masked videos—a task analogous to that done by humans. The pattern of accuracy for the DCNN mirrored some, but not all, aspects of human performance, highlighting the need to test the effectiveness of identity masking for both humans and machines. The DCNN was also tested on its ability to match identity between masked and unmasked versions of the same video, based only on the face. DCNN performance for the eight masks offers insight into the nature of the information in faces that is coded in these networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Performance Demonstration of Self-Powered Neutron Detectors for Steady-State Reactor Operations

The irradiation testing of sensors in reactors is a crucial step towards calibrating and qualifying sensors prior to their deployment in experiments. This report details the process toward qualifying and calibrating custom-designed rhodium-based self-power neutron detectors (Rh-SPNDs) for steady-state reactor irradiations. This process serves to both demonstrate the performance capabilities of Rh-SPNDs as well as to provide experimental data for development of a sensor sensitivity model. Two designs of Rh-SPNDs were tested in various reactors to demonstrate: detection resolution in a low neutron flux environment, a delayed-response compensation technique, output linearity in a large range of neutron flux, and measurement accuracy verified with dosimetry. The detection resolution and compensation technique was demonstrated in the AGN-201m reactor at Idaho State University. The irradiation confirmed the sensors’ capability to perform steady-state operations in a low neutron flux of ~2E8 n/cm 2 -sec. Sensor output linearity coupled with the delayed-response compensation was investigated at the neutron radiography reactor at Idaho National Laboratory. A Rh-SPND was irradiated to neutron fluxes ranging from 2E8 to 2E13 n/cm2-sec range. The measured data demonstrated a wide and linear range of operation with a measured linear sensitivity of 1.0129 ×10 -13 A/W with a correlation-squared value of r 2 =0.9927. The measurement accuracy was investigated at the Advanced Test Reactor Critical reactor. The SPNDs were inserted into a test vehicle with collocated flux wires. Two irradiations with different flux levels were performed, and the SPNDs relative measurement between the two irradiations was calculated to be 1.2613 ± 0.0153 for the small SPND design and 1.1809 ± 0.0108 for the large SPND design. Both SPND measurements fell between the co-axial dosimetry result, which reported 1.218 ± 0.047. Additionally, the preliminary MCNP model for calculating SPND sensitivity was developed in parallel to this work. Modeled neutron spectrum with measured magnitude was used for inputs to determine the simulated SPND output. The results showed an overestimation of signal strength by a factor of 5, which was expected because of model simplification. This leads to future modeling work to account for signal losses from additional physical properties, including high temperature environments for FY-21.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

DSGAN

This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low-and high- resolution simulations to train a neural network to map from the former to the latter. Specifically, we define two types of CNNs, one that stacks variables directly and one that encodes each variable before stacking, and we train each CNN type both with a conventional loss function, such as mean square error (MSE), and with a conditional generative adversarial network (CGAN), for a total of four CNN variants. We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique. Results show that the SR technique produces results similar to those of the bilinear interpolator with smoother spatial and temporal distributions and smaller data variabilities and extremes than the original high resolution simulations. While the new CNNs trained by MSE generate better results over some regions than the interpolator and SR technique do, their predictions are still not as close as the original high resolution simulations. The CNNs trained by CGAN generate more realistic and physically reasonable results, better capturing not only data variability in time and space but also extremes such as intense and long-lasting storms. The new proposed CNN-based downscaling approach can downscale precipitation from 50~km to 12~km in 14~min for 30~years

LIU, ZHENGCHUN↗
DOE OSTI2025

Development of thin-gap GEM- μ RWELL hybrid detectors

Micro Pattern Gaseous Detectors (MPGDs) are used for tracking in High Energy Physics and Nuclear Physics because of their large area, excellent spatial resolution capabilities and low cost. However, for high energy charged particles impacting at a large angle with respect to the axis perpendicular to detector plane, the spatial resolution degrades significantly because of the long trail of ionization charges produced in clusters all along the track in the drift region of the detector. The long ionization charge trail results in registering hits from large number of strips in the readout plane which makes it challenging to precisely reconstruct the particle’s position using simple center of gravity algorithm. As a result, the larger the drift gap, the more severe the deterioration of spatial resolution for inclined tracks. For the same reason, the position resolution is also severely degraded in a large magnetic field, where the Lorentz E x B effect causes the ionization charges to follow a curved and longer path in the detector gas volume. In this paper, we report on the development of thin-gap MPGDs as a way to maintain excellent spatial resolution capabilities of MPGD detectors over a wide angular range of incoming particles. In a thin-gap MPGD, the thickness of the gas volume in the drift region is reduced from typically 3 mm to 1 mm or less. We present preliminary test beam results demonstrating the improvement in spatial resolution from 400 m with a standard 3 mm gap μ RWELL prototype to ~140 μ m with a double amplification GEM- μ RWELL thin-gap hybrid detector. Here, we also discuss the impact of a thin-gap drift volume on other aspects of the performance of MPGD technologies such as the efficiency and detector stability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2014

Grid Resolution Study over Operability Space for a Mach 1.7 Low Boom External Compression Inlet

This paper presents a statistical methodology whereby the probability limits associated with CFD grid resolution of inlet flow analysis can be determined which provide quantitative information on the distribution of that error over the specified operability range. The objectives of this investigation is to quantify the effects of both random (accuracy) and systemic (biasing) errors associated with grid resolution in the analysis of the Lockheed Martin Company (LMCO) N+2 Low Boom external compression supersonic inlet. The study covers the entire operability space as defined previously by the High Speed Civil Transport (HSCT) High Speed Research (HSR) program goals. The probability limits in terms of a 95.0% confidence interval on the analysis data were evaluated for four ARP1420 inlet metrics, namely (1) total pressure recovery (PFAIP), (2) radial hub distortion (DPH/P), (3) ) radial tip distortion (DPT/P), and (4) ) circumferential distortion (DPC/P). In general, the resulting +/-0.95 delta Y interval was unacceptably large in comparison to the stated goals of the HSCT program. Therefore, the conclusion was reached that the "standard grid" size was insufficient for this type of analysis. However, in examining the statistical data, it was determined that the CFD analysis results at the outer fringes of the operability space were the determining factor in the measure of statistical uncertainty. Adequate grids are grids that are free of biasing (systemic) errors and exhibit low random (precision) errors in comparison to their operability goals. In order to be 100% certain that the operability goals have indeed been achieved for each of the inlet metrics, the Y+/-0.95 delta Y limit must fall inside the stated operability goals. For example, if the operability goal for DPC/P circumferential distortion is ≤0.06, then the forecast Y for DPC/P plus the 95% confidence interval on DPC/P, i.e. +/-0.95 delta Y, must all be less than or equal to 0.06.

Grid↗
NASA NTRS1986

Theoretical study of the X-ray emission from astrophysical shock waves

Theoretical X-ray emission spectra are needed to interpret the X-ray emission observed by many low and moderate resolution X-ray instruments, and to provide diagnosis of physical conditions for high resolution spectra. Over the past decade, a set of model codes which compute the X-ray and XUV emission for a wide set of physical conditions, including high or low densities, photoionized gas, and time-dependent ionization balance was developed. In the past year, the atomic rate coefficients in the code was improved. Further capabilities were added, and applied to several astrophysical problems.

Raymond, J.↗
NASA NTRS2008

Reducing Surface Clutter in Cloud Profiling Radar Data

An algorithm has been devised to reduce ground clutter in the data products of the CloudSat Cloud Profiling Radar (CPR), which is a nadir-looking radar instrument, in orbit around the Earth, that measures power backscattered by clouds as a function of distance from the instrument. Ground clutter contaminates the CPR data in the lowest 1 km of the atmospheric profile, heretofore making it impossible to use CPR data to satisfy the scientific interest in studying clouds and light rainfall at low altitude. The algorithm is based partly on the fact that the CloudSat orbit is such that the geodetic altitude of the CPR varies continuously over a range of approximately 25 km. As the geodetic altitude changes, the radar timing parameters are changed at intervals defined by flight software in order to keep the troposphere inside a data-collection time window. However, within each interval, the surface of the Earth continuously "scans through" (that is, it moves across) a few range bins of the data time window. For each radar profile, only few samples [one for every range-bin increment ((Delta)r = 240 m)] of the surface-clutter signature are available around the range bin in which the peak of surface return is observed, but samples in consecutive radar profiles are offset slightly (by amounts much less than (Delta)r) with respect to each other according to the relative change in geodetic altitude. As a consequence, in a case in which the surface area under examination is homogenous (e.g., an ocean surface), a sequence of consecutive radar profiles of the surface in that area contains samples of the surface response with range resolution (Delta)p much finer than the range-bin increment ((Delta)p << r). Once the high-resolution surface response has thus become available, the profile of surface clutter can be accurately estimated by use of a conventional maximum-correlation scheme: A translated and scaled version of the high-resolution surface response is fitted to the observed low-resolution profile. The translation and scaling factors that optimize the fit in a maximum-correlation sense represent (1) the true position of the surface relative to the sampled surface peak and (2) the magnitude of the surface backscatter. The performance of this algorithm has been tested on CloudSat data acquired over an ocean surface. A preliminary analysis of the test data showed a surface-clutter-rejection ratio over flat surfaces of >10 dB and a reduction of the contaminated altitude over ocean from about 1 km to about 0.5 km (over the ocean). The algorithm has been embedded in CloudSat L1B processing as of Release 04 (July 2007), and the estimated flat surface clutter is removed in L2B-GEOPROF product from the observed profile of reflectivity (see CloudSat product documentation for details and performance at http://www.cloudsat.cira.colostate.edu/ dataSpecs.php?prodid=1).

Tanelli, Simone↗
DOE OSTI2022

CLAIRE—Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging Applications

We study the performance of CLAIRE—a diffeomorphic multi-node, multi-GPU image-registration algorithm and software—in large-scale biomedical imaging applications with billions of voxels. At such resolutions, most existing software packages for diffeomorphic image registration are prohibitively expensive. As a result, practitioners first significantly downsample the original images and then register them using existing tools. Our main contribution is an extensive analysis of the impact of downsampling on registration performance. We study this impact by comparing full-resolution registrations obtained with CLAIRE to lower resolution registrations for synthetic and real-world imaging datasets. Our results suggest that registration at full resolution can yield a superior registration quality—but not always. For example, downsampling a synthetic image from 10243 to 2563 decreases the Dice coefficient from 92% to 79%. However, the differences are less pronounced for noisy or low contrast high resolution images. CLAIRE allows us not only to register images of clinically relevant size in a few seconds but also to register images at unprecedented resolution in reasonable time. The highest resolution considered are CLARITY images of size 2816×3016×1162. To the best of our knowledge, this is the first study on image registration quality at such resolutions.

Himthani, Naveen↗
NASA NTRS1992

Optical imaging of QSOs with 0.5 arcsec resolution

Optical imaging data are presented on 28 low redshift QSOs with 0.5 arcsec resolution. The group includes a range of radio and IR luminosities. The high-resolution data reveal significant new morphological information on 16 objects, and yield good luminosity profiles on all of them. Most objects appear to have R exp 1/4 law or peculiar luminosity profiles. The QSOs are almost all found to be in merging or interacting galaxies, most of them with a smaller companion. The observed structural details appear to be similar to lower luminosity AGN at low redshift. There are few unexplained features such as 'jets' near the nucleus. Detailed descriptions are given of all objects, including new high-resolution radio observations of a few of the QSOs.

Hutchings, J. B.↗
DOE OSTI2024

Precision Agriculture using Networks of Degradable Analytical Sensors (PANDAS) (Final Technical Report)

Precision agriculture, where sensing of soil, environment and crop conditions are used to precisely synchronize inputs (such as water and fertilizer) to crop needs enhances input use efficiency. This can improve yields and farm profitability while mitigating environmental losses, improving soil carbon content and substantially decreasing energy use for food, feed and fuel crops. Unfortunately, farmers are not yet able to harness the full potential of these management technologies as there is a lack of available management information, and there is therefore a need for sensors that are able to economically measure spatio-temporal variability in soil and crop properties of extremely heterogeneous farm fields precisely at high resolution and at low cost. Real-time, in-situ monitoring of agricultural soil conditions is today carried out using devices that limit the total number of nodes that can be used economically to typically one per acre or less. Higher spatio-temporal resolution sensing would enable more precise agricultural input optimization, with significant benefits to the farmer and the environment. In order to address this issue, this project focused on developing additively manufactured, biodegradable, soil sensors with predicted costs of < $\$$1 per unit to monitor crop inputs (such as water and fertilizer) that predictably, harmlessly degrade away into the soil when no longer needed. These sensor nodes should be easy to place, accurately and continuously monitor soil and crop conditions for an entire season, be read remotely using existing farm equipment, require no ongoing maintenance, not impede farm operations and produce no persistent waste. This approach could enable a >100× increase in information density over current solutions for precision farming of row and other crops, and lead to significant reductions in input energy use and provide increased yield for biofuel crops. Over the course of this project the team at the University of Colorado Boulder, University of California Berkeley, and Colorado State University/Kansas State University investigated a wide range of printable biodegradable electronic materials and sensor designs for determining soil moisture and soil nitrate concentration. These efforts expanded the available materials set for printed soil degradable electronic materials, particularly for conductors, enabling high conductivity and stability. Printed soil moisture and nitrate sensors with suitable sensitivity and selectivity were developed and characterized. Low power and passive wireless electronic systems were integrated with the soil sensors, and testing was carried out with completed sensors to understand their functionality under agricultural conditions. Additionally, other sensor types enabled by the biodegradable materials set created during this project, such as soil microbial activity sensors, were also developed and demonstrated. Project outputs include 10 peer reviewed publications, 4 patent applications, 21 technical presentations, 3 PhD thesis, 10 media reports, 8 additional grants worth over $\$$6M, and the formation of 3 start-up companies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

symfind : Addressing the Fragility of Subhalo Finders and Revealing the Durability of Subhalos

Abstract A major question in ΛCDM is what this theory actually predicts for the properties of subhalo populations. Subhalos are difficult to accurately simulate and to find within simulations, and this propagates into uncertainty in theoretical predictions for satellite galaxies. We present Symfind , a new particle-tracking-based subhalo finder, and demonstrate that it can track subhalos to orders-of-magnitude lower masses than commonly used halo-finding tools, with a focus on Rockstar and consistent-trees . These longer survival times mean that at a fixed peak subhalo mass, we find ≈ 15%–40% more subhalos within the virial radius, R vir , and ≈35%–120% more subhalos within R vir /4 in the Symphony dark-matter-only simulation suite. More subhalos are found as the resolution is increased, in contrast to the Rockstar halo finder, which appears to be converged at smaller subhalo counts. We perform extensive numerical testing. In agreement with idealized simulations, we show that the v max , the maximum circular velocity, is systematically biased low until high resolutions ( n peak ≳ 3 × 10 4 ) are achieved, but that mass loss itself can be resolved at much more modest resolutions ( n peak ≳ 4 × 10 3 ). We show that Rockstar converges to false solutions for the mass function, radial distribution, and disruption masses of subhalos. We argue that our new method can trace resolved subhalos until the point of typical galaxy disruption without invoking post hoc orphan modeling. We outline a concrete set of steps for determining whether other subhalo finders meet the same criteria. We publicly release Symfind catalogs and particle data for the Symphony simulation suite at http://web.stanford.edu/group/gfc/symphony .

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

The Fourier-Kelvin Stellar Interferometer a Low Complexity, Low Cost Space Mission for High-Resolution Astronomy and Direct Exoplanet Detection

The Fourier-Kelvin Stellar Interferometer (FKSI) is a mission concept for a spacecraft-borne nulling interferometer for high-resolution astronomy and the direct detection of exoplanets and assay of their environments and atmospheres. FKSI is a high angular resolution system operating in the near to midinfrared spectral region and is a scientific and technological pathfinder to the Darwin and Terrestrial Planet Finder (TPF) missions. The instrument is configured with an optical system consisting, depending on configuration, of two 0.5 - 1.0 m telescopes on a 12.5 - 20 m boom feeding a symmetric, dual Mach- Zehnder beam combiner. We report on progress on our nulling testbed including the design of an optical pathlength null-tracking control system and development of a testing regime for hollow-core fiber waveguides proposed for use in wavefront cleanup. We also report results of integrated simulation studies of the planet detection performance of FKSI and results from an in-depth control system and residual optical pathlength jitter analysis.

Barry, R. K.↗
DOE OSTI2020

Benefits of MeV-scale reconstruction capabilities in large liquid argon time projection chambers

Using truth-level Monte Carlo simulations of particle interactions in a large volume of liquid argon, we demonstrate physics capabilities enabled by reconstruction of topologically compact and isolated low-energy features, or “blips,” in large liquid argon time projection chamber (LArTPC) events. These features are mostly produced by electron products of photon interactions depositing ionization energy. The blip identification capability of the LArTPC is enabled by its unique combination of size, position resolution precision, and low energy thresholds. Here, we show that consideration of reconstructed blips in LArTPC physics analyses can result in substantial improvements in calorimetry for neutrino and new physics interactions and for final-state particles ranging in energy from the MeV to the GeV scale. Blip activity analysis is also shown to enable discrimination between interaction channels and final-state particle types. In addition to demonstrating these gains in calorimetry and discrimination, some limitations of blip reconstruction capabilities and physics outcomes are also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Self-Admitted Technical Debt in Scientific Software: Prioritization, Sentiment, and Propagation Across Artifacts

Self-admitted technical debt (SATD) impairs scientific software (SSW), yet its prioritization, sentiment, persistence, and propagation remains underexplored. Understanding how SSW developers express, and address SATD is crucial for improving SSW maintenance, and tooling. This study investigates how SATD types and artifacts in SSW are prioritized, how sentiment relates to urgency, SATD removal and resolution rates, and the extent to which SATD propagates across artifacts. We analyzed nine SSW repositories using a SATD classification model and a semantic embedding-based prioritization heuristic. SATD was examined across multiple artifacts, with sentiment assessed via a fine-tuned transformer. Propagation was traced, priority scores compared to static analysis, and removal and resolution rates quantified. SATD in comments, commits, and pull requests receive higher priority than SATD in issues, with negative sentiment amplifying urgency. Resolution and removal rates lag behind open-source software (OSS) averages. Most SATD remains confined to the originating artifact, but longer propagation chains are rare and correlate with higher priority, highlighting persistent and high impact debt. Prioritization is influenced by artifact type and sentiment, while low removal and resolution rates signal persistent debt. Cross-artifact propagation marks high priority, unresolved SATD, providing empirical guidance for targeted monitoring, review prioritization, and tool supported maintenance in SSW.

Melin, Eric [Boise State University]↗
NASA NTRS2004

On the Fringe Field of Wide Angle LC Optical Phased Array

For free space laser communication, light weighted large deployable optics is a critical component for the transmitter. However, such an optical element will introduce large aberrations due to the fact that the surface figure of the large optics is susceptable to deformation in the space environment. We propose to use a high-resolution liquid crystal spatial light modulator to correct for wavefront aberrations introduced by the primary optical element, and to achieve very fine beam steering and shaping at the same time. A 2-D optical phased array (OPA) antenna based on a Liquid Crystal on Silicon (LCOS) spatial light modulator is described. This device offers a combination of low cost, high resolution, high accuracy, high diffraction efficiency at video speed. To quantitatively understand the influence factor of the different design parameters, a computer simulation of the device is given by the 2-D director simulation and the Finite Difference Time domain (FDTD) simulation. For the 1-D OPA, we define the maximum steering angle to have a grating period of 8 pixel/reset scheme; as for larger steering angles than this criterion, the diffraction efficiency drops dramatically. In this case, the diffraction efficiency of 0.86 and the Strehl ratio of 0.9 are obtained in the simulation. The performance of the device in achieving high resolution wavefront correction and beam steering is also characterized experimentally.

Wang, Xighua↗