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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Effects of normal aging on visuo-motor plasticity

Normal aging is associated with declines in neurologic function. Uncompensated visual and vestibular problems may have dire consequences including dangerous falls. Visuo-motor plasticity is a form of behavioral neural plasticity, which is important in the process of adapting to visual or vestibular alteration, including those changes due to pathology, pharmacotherapy, surgery or even entry into microgravity or an underwater environment. To determine the effects of aging on visuo-motor plasticity, we chose the simple and easily measured paradigm of visual-motor rearrangement created by using visual displacement prisms while throwing small balls at a target. Subjects threw balls before, during and after wearing a set of prisms which displace the visual scene by twenty degrees to the right. Data obtained during adaptation were modeled using multilevel modeling techniques for 73 subjects, aged 20 to 80 years. We found no statistically significant difference in measures of visuo-motor plasticity with advancing age. Further studies are underway examining variable practice training as a potential mechanism for enhancing this form of behavioral neural plasticity.

Clinical Trial↗
NASA NTRS2009

Effects of Transverse Seat Vibration on Near-Viewing Readability of Alphanumeric Symbology

We measured the impacts on human visual function of a range of vibration levels (0.15, 0.3, 0.5, and 0.7 g) at the frequency and along the axis of the anticipated Ares thrust oscillation. We found statistically significant and equivalent decrements in performance on a reading and a numeric processing task at tested vibration levels above 0.3 g (0-to-peak), but no evidence of after-effects. At the smallest font and highest vibration level tested, the average effect was a 50 percent increase in response time and six-fold increase in errors. Our findings support a preliminary trade space in which currently planned Orion font sizes and text spacing appear to be too small to support accurate and efficient reading at the tested vibration levels above 0.3 g, but not too small to support reading at 0.3 g. This study does not address potential impacts on crew cognitive decision-making or motor control and does not test either the full induced Orion-Ares environment with its sustained Gx-loading or the full complexity of the final Orion seat-helmet-suit interface. A final determination of the Orion-Ares program limit on vibration must take these additional factors into consideration and, thus, may need to be lower than that needed to support effective reading at 1-Gx bias.

Readability↗
DOE OSTI2018

Arms Down Cone Beam CT Hepatic Angiography Performance Assessment: Vascular Imaging Quality and Imaging Artifacts

IntroductionThe practice of positioning patients’ arms above the head during catheter-injected hepatic arterial phase cone beam CT (A-CBCT) imaging has been inherited from standard CT imaging due to image quality concerns, but interrupts workflow and extends procedure time. We sought to assess A-CBCT image quality and artifacts with arms extended above the head versus down by the side.MethodsWe performed an IRB approved retrospective evaluation of reformatted and 3D-volume rendered images from 91 consecutive A-CBCTs (43 arms up, 48 arms down) acquired during hepatic tumor arterial embolization procedures. Two interventional radiologists reviewed all A-CBCT imaging and assigned vessel visualization scores (VVS) from 1 to 5, ranging from non-diagnostic to optimal visualization. Streak artifacts across axial images were rated from 1 to 3 based on resulting image quality (none to significant). Presence of respiratory or cardiac motion during acquisition, body mass index and radiation dose area product (DAP) were also recorded and analyzed. Univariate and multivariate analyses were used to assess the impact of arm position on VVS and imaging artifacts.ResultsVVS were not significantly associated with arm position during A-CBCT imaging. One reader reported more streak artifacts across axial images in the arms down group (p = 0.005). DAP was not statistically different between the groups (23.9 Gy cm{sup 2} [6.1–73.4] arms up, 26.1 Gy cm{sup 2} [4.2–102.6] arms down, p = 0.54).ConclusionA-CBCT angiography performed with the arms above the head is not superior for clinically relevant hepatic vascular visualization compared to imaging performed with the arms by the patient’s side.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis

Significance Liquid cell transmission electron microscopy (LCTEM) is an emerging technique, which enables nanoscale visualization and tracking of single nanoparticles near interfaces with unprecedented spatial resolution. Here, we studied the diffusion of nanoparticles in LCTEM experiments using techniques powered by deep neural networks and statistical tests. We observed two underlying regimes of diffusive behavior which are governed by the interaction of the electron beam, the nanoparticle, the nearby substrate, and the liquid environment. This understanding forms the foundation to use LCTEM for single-nanoparticle tracking for a broad range of nanoparticles, interfaces, and liquids.

Jamali, Vida↗
DOE OSTI2021

VAINE: Visualization and AI for Natural Experiments

Natural experiments are observational studies where the assignment of treatment conditions to different populations occur by chance ``in the wild''. Researchers from fields such as economics, healthcare, and the social sciences leverage natural experiments to conduct hypothesis testing and causal effect estimation for treatment and outcome variables that would otherwise be costly, infeasible, or unethical. In this paper, we introduce VAINE (Visualization and AI for Natural Experiments), a visual analytics tool for identifying and understanding natural experiments from observational data. We then demonstrate how VAINE can be used to validate causal relationships, estimate average treatment effects, and identify statistical phenomena such as Simpson’s paradox through two use cases.

Guo, Grace↗
DOE OSTI2025

Impacts of PV Module Connector Failures on Cost and Performance of Utility Scale Photovoltaic Systems

The reliability, cost and performance of electrical connectors are a concern in all types of electrical systems, and demands on connectors used on photovoltaic (PV) systems include that connectors maintain electrical conductivity and physical strength, endure ultraviolet sunlight and high ambient temperature, and resist moisture and chemical intrusion over a very long (>25 year) performance period. Connector failures increase operation and maintenance (O&M) costs and reduce plant production, but connector failure can also cause safety and liability problems, which are of greater concern. This work results from a three-year collaboration between Sandia National Laboratories (SNL), the Electric Power Research Institute (EPRI), and the National Renewable Energy Laboratory (NREL) and funded by the U.S. Department of Energy (DOE) Solar Energy Technology Office (SETO) under Agreements #39035 and #38531 "Connector Reliability Across the US Solar Sector." a multi-pronged investigation of PV connector health across the US (see https://energy.sandia.gov/pvconnectors/). This report presents derivation of a Techno-Economic Analysis (TEA) that models failure modes and frequencies (how often failure occurs), estimates O&M costs and lost production associated with connector failures, and then calculates the effect that PV module connectors can have on Levelized Cost of Energy (LCOE). The model is informed with initial data from quantitative assessment of failure rates, root causes and mechanisms, in-situ diagnostics and data collection, lab-based forensics, and interviews with PV connector manufacturers and plant operators. SNL conducted site inspections at multiple utility-scale sites in different climates and subjected field samples of new, used, and degraded connectors to visual and electrical characterization. EPRI conducted metallurgical analysis of the pin and sleeve conductors to study failure-induced morphological and compositional changes. There is in general a shortage of statistically valid data, but data from PVROM database maintained by SNL was sufficient to ascertain failure rates and lost production as well as provide qualitative insight in its curated maintenance records. This report details the structure of the mathematical model but the sources of data to inform the model will continue to evolve. Analysis of a 100 MW PV plant is provided as an example of the use of the model, with results indicating that connectors are responsible for Annualized O&M Costs of $\$$71,933/year; Annualized Unit O&M Costs of $\$$0.72/kW/year; that a Reserve Account of $\$$187,220 should be available to fund repairs related to connectors; that connectors add $\$$1,494,004 to the Net Present Value of the O&M Costs (project life); and that O&M related to connectors adds about $\$$0.00088/kWh to the Levelized Cost of Energy. The impact of this model is to provide a tool to make the US solar sector more robust by quantifying and monetizing the reliability risks to utility-scale PV systems posed by poorly installed, mismatched and/or poorly designed and manufactured connectors. The TEA provides a model incorporating failure statistics, O&M cost data, and lost production into a single figure of merit, informing decisions and enabling practitioners to optimize cost and performance trade-offs. Stakeholders include connector manufacturers, system designers and equipment specifiers, standards bodies, installers and O&M providers, investors and insurance underwriters. This report supports continued growth of PV predicated on assurances that properly installed and maintained PV system connectors are safe and reliable. The project team is proposing future work including accelerated testing of connectors and expanding the approach taken here to other PV system components, such as TEA for rapid shut-down devices.

14 SOLAR ENERGY↗
NASA NTRS1986

A structural-stochastic model for the analysis and synthesis of cloud images

A structural-stochastic image model is developed for the analysis and synthesis of cloud images. The ability of the model to characterize the visual appearance of cloud fields observed by satellite with a limited number of parameters is demonstrated. The model merges structural and stochastic information, the stochastic model acting as a local statistical operator applied to the output of the structural model. The structural or large-scale organization of the scene is retrieved from the two-dimensional Fourier representation of the digital image. The pattern generated by the major Fourier components provides a first guess of the scene. The stochastic aspect is described by a Markov model of texture that assumes a binomial probability distribution for the local grey-level variability. This Markov model provides four parameters that represent the clustering strength in the horizontal, vertical and diagonal directions. These parameters are estimated by a standard maximum-likelihood technique. The image can be reproduced with a fair degree of verisimilitude from these parameters. The data compression factor is of the order of one hundred to several hundreds.

Garand, L.↗
NASA NTRS1991

Visualizing characteristics of ocean data collected during the Shuttle Imaging Radar-B experiment

Topographic measurements of sea surface elevation collected by the Surface Contour Radar (SCR) during NASA's Shuttle Imaging Radar (SIR-B) experiment are plotted as three dimensional surface plots to observe wave height variance along the track of a P-3 aircraft. Ocean wave spectra were computed from rotating altimeter measurements acquired by the Radar Ocean Wave Spectrometer (ROWS). Fourier power spectra computed from SIR-B synthetic aperture radar (SAR) images of the ocean are compared to ROWS surface wave spectra. Fourier inversion of SAR spectra, after subtraction of spectral noise and modeling of wave height modulation, yields topography similar to direct measurements made by SCR. Visual perspectives on the SCR and SAR ocean data are compared. Threshold distinctions between surface elevation and texture modulations of SAR data are considered within the context of a dynamic statistical model of rough surface scattering. The result of these endeavors is insight as to the physical mechanism governing the imaging of ocean waves with SAR.

Tilley, David G.↗
NASA NTRS2015

Advanced Bayesian Method for Planetary Surface Navigation

Autonomous Exploration, Inc., has developed an advanced Bayesian statistical inference method that leverages current computing technology to produce a highly accurate surface navigation system. The method combines dense stereo vision and high-speed optical flow to implement visual odometry (VO) to track faster rover movements. The Bayesian VO technique improves performance by using all image information rather than corner features only. The method determines what can be learned from each image pixel and weighs the information accordingly. This capability improves performance in shadowed areas that yield only low-contrast images. The error characteristics of the visual processing are complementary to those of a low-cost inertial measurement unit (IMU), so the combination of the two capabilities provides highly accurate navigation. The method increases NASA mission productivity by enabling faster rover speed and accuracy. On Earth, the technology will permit operation of robots and autonomous vehicles in areas where the Global Positioning System (GPS) is degraded or unavailable.

Center, Julian↗
NASA NTRSDate not supplied

Near-Field Separation Analysis of SLS Block-1 and Block-1B Secondary Payloads

The NASA Space Launch System (SLS) Program Block-1 and Block-1B missions are expected to carry a number of CubeSat secondary payloads (SPL) to space, where they will be ejected from internal SLS structures to begin their own missions. This near-field ejection process must be closely evaluated to ensure that no SPL contacts the SLS structures, as contacts could result in SPL component damage, mission loss, or aberrant SPL trajectories. To this end, multiple SPL ejection events were analyzed for both Block-1 and Block-1B mission configurations using CLVTOPS, a NASA Marshall Space Flight Center (MSFC) developed multi-body dynamics, proximity analysis, and visualization toolchain. This paper details the SPL-to-SLS clearance assessment process, with a focus on simulation setup and results as well as SPL design requirement analysis. Relevant CLVTOPS, statistics, and mission backgrounds are covered; important constraints, difficulties, and assumptions are also documented. Furthermore, the importance of SPL housing geometry on near-field vehicle clearance is highlighted, and examples are shown.

Jared Rucker↗
NASA NTRS2000

Visual detection of spatial contrast patterns: evaluation of five simple models

The ModelFest Phase One dataset is a collection of luminance contrast thresholds for 43 two-dimensional monochromatic spatial patterns confined to an area of approximately two by two degrees. These data were collected by a collaboration among twelve laboratories, and were designed to provide a common database for calibration and testing of spatial vision models. Here I report fits of the ModelFest data with five models: Peak Contrast, Contrast Energy, Generalized Energy, a Gabor Channels model, and a Discrete Cosine Transform model. The Gabor Channels model provides the best fit, though the other, simpler models, with the exception of Peak Contrast, provide remarkably good fits as well. Though there are clear individual differences, regularities in the data suggest the possibility of constructing a standard observer for spatial vision. c2000 Optical Society of America.

NASA Discipline Space Human Factors↗
NASA NTRS2001

Runway Texture and Grid Pattern Effects on Rate-of-Descent Perception

To date, perceptual errors occur in determining descent rate from a computer-generated image in flight simulation. Pilots tend to touch down twice as hard in simulation than in flight, and more training time is needed in simulation before reaching steady-state performance. Barnes suggested that recognition of range may be the culprit, and he cited that problems such as collimated objects, binocular vision, and poor resolution lead to poor estimation of the velocity vector. Brown's study essentially ruled out that the lack of binocular vision is the problem. Dorfel added specificity to the problem by showing that pilots underestimated range in simulated scenes by 50% when 800 ft from the runway threshold. Palmer and Petitt showed that pilots are able to distinguish between a 1.7 ft/sec and 2.9 ft/sec sink rate when passively observing sink rates in a night scene. Platform motion also plays a role, as previous research has shown that the addition of substantial platform motion improves pilot estimates of vertical velocity and results in simulated touchdown rates more closely resembling flight. This experiment examined how some specific variations in the visual scene properties affect a pilot's perception of sink rate. It extended another experiment that focused on the visual and motion cues necessary for helicopter autorotations. In that experiment, pilots performed steep approaches to a runway. The visual content of the runway and its surroundings varied in two ways: texture and rectangular grid spacing. Four textures, included a no-texture case, were evaluated. Three grid spacings, including a no-grid case, were evaluated. The results showed that pilot better controlled their vertical descent rates when good texture cues were present. No significant differences were found for the grid manipulation. Using those visual scenes a simple psychophysics, experiment was performed. The purpose was to determine if the variations in the visual scenes allowed pilots to better perceive vertical velocity. To determine that answer, pilots passively viewed a particular visual scene in which the vehicle was descending at two different rates. Pilots had to select which of the two rates they thought was the fastest rate. The difference between the two rates changed using a staircase method, depending on whether or not the pilot was correct, until a minimum threshold between the two descent rates was reached. This process was repeated for all of the visual scenes to decide whether or not the visual scenes did allow pilots to perceive vertical velocity better among them. All of the data have yet to be analyzed; however, neither the effects of grid nor texture revealed any statistically significant trends. On further examination of the staircase method employed, a possibility exists that the lack of an evident trend may be due to the exit criterion used during the study. As such, the experiment will be repeated with an improved exit criterion in February. Results of this study will be presented in the submitted paper.

Schroeder, J. A.↗
NASA NTRS2011

Retrospective Analog Year Analyses Using NASA Satellite Data to Improve USDA's World Agricultural Supply and Demand Estimates

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attach s, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly affect crop yields, WAOB often uses precipitation time series to identify growing seasons with similar weather patterns and help estimate crop yields for the current growing season, based on observed yields in analog years. Historically, these analog years are visually identified; however, the qualitative nature of this method sometimes precludes the definitive identification of the best analog year. Thus, one goal of this study is to derive a more rigorous, statistical approach for identifying analog years, based on a modified coefficient of determination, termed the analog index (AI). A second goal is to compare the performance of AI for time series derived from surface-based observations vs. satellite-based measurements (NASA TRMM and other data).

Teng, William↗
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

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

High performance computers have for many years been on a trajectory that gives them extraordinary compute power with the addition of more and more compute cores. At the same time, other system parameters such as the amount of memory per core and bandwidth to storage have remained constant or have barely increased. This creates an imbalance in the computer, giving it the ability to compute a lot of data that it cannot reasonably save out due to time and storage constraints. While technologies have been invented to mitigate this problem (burst buffers, etc.), software has been adapting to employ in situ libraries which perform data analysis and visualization on simulation data while it is still resident in memory. This avoids the need to ever have to pay the costs of writing many terabytes of data files. Instead, in situ enables the creation of more concentrated data products such as statistics, plots, and data extracts, which are all far smaller than the full-sized volume data. With the increasing popularity of in situ, multiple in situ infrastructures have been created, each with its own mechanism for integrating with a simulation. To make it easier to instrument a simulation with multiple in situ infrastructures and include custom analysis algorithms, this project created the SENSEI framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Accelerated Depth Computation for Surface Boxplots with Deep Learning

Functional depth is a well-known technique used to derive descriptive statistics (e.g., median, quartiles, and outliers) for 1D data. Surface boxplots extend this concept to ensembles of images, helping scientists and users identify representative and outlier images. However, the computational time for surface boxplots increases cubically with the number of ensemble members, making it impractical for integration into visualization tools. In this paper, we propose a deep-learning solution for efficient depth prediction and computation of surface boxplots for time-varying ensemble data. Our deep learning framework accurately predicts member depths in a surface boxplot, achieving average speedups of 6X on a CPU and 15X on a GPU for the 2D Red Sea dataset with 50 ensemble members compared to the traditional depth computation algorithm. Our approach achieves at least a 99% level of rank preservation, with order flipping occurring only at pairs with extremely similar depth values that pose no statistical differences. This local flipping does not significantly impact the overall depth order of the ensemble members.

Han, Mengjiao↗
DOE OSTI2025

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗
NASA NTRS1979

Multiple asteroid rendezvous missions

Asteroid missions, centered on multiple asteroid rendezvous missions to main belt asteroids, are discussed and the required solar electric propulsion for these missions as well as the current performance estimates are examined. A brief statistical analysis involving asteroid availability transfer requirements and propulsion system capabilities is given, leading to a prediction that 5 to 8 asteroids can be encountered with a single launch. Measurement techniques include visual imaging, radio tracking, magnetometry, and in the case of landers, seismometry. The spacecraft will be propelled by a solar electric system with a power level of 25 kW to 40 kW and tour possibilities for 13 different asteroids have been developed. Preliminary estimates of asteroid triaxiality are made to calculate the effect of close orbits.

Bender, D. F.↗