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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 1,351 records · Page 75

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NASA NTRS2006

Adaptive Changes In Postural Equilibrium And Motion Sickness Following Repeated Exposures To Virtual Environments

Virtual environments offer unique training opportunities, particularly for training astronauts and preadapting them to the novel sensory conditions of microgravity. Two unresolved human factors issues in virtual reality (VR) systems are: 1) potential "cybersickness", and 2) maladaptive sensorimotor performance following exposure to VR systems. Interestingly, these aftereffects are often quite similar to adaptive sensorimotor responses observed in astronauts during and/or following space flight. Changes in the environmental sensory stimulus conditions and the way we interact with the new stimuli may result in motion sickness, and perceptual, spatial orientation and sensorimotor disturbances. Initial interpretation of novel sensory information may be inappropriate and result in perceptual errors. Active exploratory behavior in a new environment, with resulting feedback and the formation of new associations between sensory inputs and response outputs, promotes appropriate perception and motor control in the new environment. Thus, people adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, unilateral labyrinthectomy and experimentally produced stimulus rearrangements. Adaptation is revealed by aftereffects including perceptual disturbances and sensorimotor control disturbances. The purpose of the current study was to compare disturbances in postural control produced by dome and head-mounted virtual environment displays, and to examine the effects of exposure duration, and repeated exposures to VR systems. Forty-one subjects (21 men, 20 women) participated in the study with an age range of 21-49 years old. One training session was completed in order to achieve stable performance on the posture and VR tasks before participating in the experimental sessions. Three experimental sessions were performed each separated by one day. The subjects performed a navigation and pick and place task in either a dome or head-mounted display (HMD) VR system for either 30 or 60 min. The environment was a square room with 15 pedestals on two opposite walls. The objects appeared on one set of pedestals and the subject s objective was to move the objects to the other set of pedestals. After the subject picked up an object, a pathway appeared and they were required to follow the pathway to the other side of the room. The subject was instructed to perform the task as quickly and accurately as possible, avoiding hitting walls and other any obstacles and placing the object on the center of the pedestal. Postural equilibrium was measured (using the Equitest CDP balance system, Neurocom, International) before, immediately after, and at 1 hr, 2 hr, 4 hr and 6 hr following exposure to VR. Postural equilibrium was measured during quiet stance with eyes open, eyes closed and vision and/or ankle proprioceptive inputs selectively altered by servo-controlling the visual surround and/or support surface to the subject s center of mass sway. Posture data was normalized using a log transformation and motion sickness data were normalized using the square root. In general, we found that exposure to VR resulted in decrements in postural stability. The largest decrements were observed in the tests performed immediately following exposure to VR and showed a fairly rapid recovery across the remaining test sessions. In addition, subjects generally showed improvement across days. We found significant main effects for day and time for the composite equilibrium score and for sensory organization tests (SOT) 1, 2 and 6. Significant main effects were observed for day for SOT 3 and 5. Although we found no significant main effects for gender (when center of gravity was used as a covariate), we did observe significant gender X time interaction effects for composite equilibrium and for SOT 1, 3, 4 and 5. Women appeared to show larger decrements in postural stability immediately after exposure to VR than men, but recover more quickly than n. Finally, we found no significant main effects for type of VR device or for exposure duration, however, these factors did interact with other factors during some of the SOTs. Subjects exhibited rapid recovery of motion sickness symptoms across time following exposure to VR and significantly less severe symptoms across days. We did not observe main effects for gender, type of device or duration of exposure. Individuals recovered from the detrimental effects of exposure to virtual reality on postural control and motion sickness within one hour. Sickness severity and initial decrements in postural equilibrium decreases over days, which suggests that subjects become dual-adapted over time. These findings provide some direction for developing training schedules for VR users that facilitate adaptation, and support the idea that preflight training of astronauts may serve as useful countermeasure for the sensorimotor effects of space flight.

Harm, D. L.↗

DOE OSTI2022

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum

We explore the use of deep convolutional neural networks (CNNs) trained on overhead imagery of biomass sorghum to ascertain the relationship between single nucleotide polymorphisms (SNPs), or groups of related SNPs, and the phenotypes they control. We consider both CNNs trained explicitly on the classification task of predicting whether an image shows a plant with a reference or alternate version of various SNPs as well as CNNs trained to create data-driven features based on learning features so that images from the same plot are more similar than images from different plots, and then using the features this network learns for genetic marker classification. We characterize how efficient both approaches are at predicting the presence or absence of a genetic markers, and visualize what parts of the images are most important for those predictions. We find that the data-driven approaches give somewhat higher prediction performance, but have visualizations that are harder to interpret; and we give suggestions of potential future machine learning research and discuss the possibilities of using this approach to uncover unknown genotype × phenotype relationships.

Zhang, Zeyu↗

DOE OSTI2016

Continuous whole-system monitoring toward rapid understanding of production HPC applications and systems

A detailed understanding of HPC applications’ resource needs and their complex interactions with each other and HPC platform resources are critical to achieving scalability and performance. Such understanding has been difficult to achieve because typical application profiling tools do not capture the behaviors of codes under the potentially wide spectrum of actual production conditions and because typical monitoring tools do not capture system resource usage information with high enough fidelity to gain sufficient insight into application performance and demands. In this paper we present both system and application profiling results based on data obtained through synchronized system wide monitoring on a production HPC cluster at Sandia National Laboratories (SNL). We demonstrate analytic and visualization techniques that we are using to characterize application and system resource usage under production conditions for better understanding of application resource needs. Furthermore, our goals are to improve application performance (through understanding application-to-resource mapping and system throughput) and to ensure that future system capabilities match their intended workloads.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

PanViz: interactive visualization of the structure of functionally annotated pangenomes

Summary: PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses. Availability and Implementation: PanViz is written entirely in JavaScript and is available on https:// github.com/thomasp85/PanViz. A companion R package that facilitates the creation of PanViz visualizations from a range of data formats is released through Bioconductor and is available at https:// bioconductor.org/packages/PanViz Generator.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2014

Resonant Interaction of a Rectangular Jet with a Flat-Plate

A resonant interaction between a large aspect ratio rectangular jet and a flat-plate is addressed in this experimental study. The plate is placed parallel to but away from the direct path of the jet. At high subsonic conditions and for certain relative locations of the plate, the resonance accompanied by an audible tone is encountered. The trends of the tone frequency variation exhibit some similarities to, but also marked differences from, corresponding trends of the well-known edge-tone phenomenon. Under the resonant condition flow visualization indicates a periodic flapping motion of the jet column. Phase-averaged Mach number data obtained near the plate's trailing edge illustrate that the jet cross-section goes through large contortions within the period of the tone. Farther downstream a clear 'axis switching' takes place. These results suggest that the assumption of two-dimensionality should be viewed with caution in any analysis of the flow.

Zaman, K. B. M. Q.↗

NASA NTRS2018

Studying Diurnal Variations of Aerosols with NASA MERRA-2 Reanalysis Data

Aerosols play an important role in atmospheric dynamics, climate variations, and Earth's energy cycle by altering the radiation balance in the atmosphere through interaction with clouds, providing fertilizer for forests and canopy, and as a supply of iron to the ocean over long time periods. Studies suggest that much of the feedback between dust aerosols and dynamics is associated with diurnal and synoptic scale variability. However, the lack of sub-daily resolution of aerosols from satellite observations makes it difficult to study the diurnal characteristics, especially over tropical and subtropical regions. Investigation of this topic utilizes over 37 years of simulated global aerosol products from NASA atmospheric reanalysis, in the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data set, available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). MERRA-2 covers the period 1980-present, and is continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using data from MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated using the MERRA-2 aerosol model, which interacts directly with radiation parameterization, and is radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Hourly, monthly, and monthly diurnal data are available at spatial resolution of 0.5o x 0.625o (latitude x longitude). By using MERRA-2 hourly and monthly diurnal products, different aerosol diurnal variabilities are observed over North America, Africa, Asia, and Australia, that may be due to different meteorological conditions and aerosol sources. The presentation will also provide an overview of MERRA-2 data services at GES DISC, such as how to find and download data, and how to quickly visualize and analyze data online with Giovanni.

aerosol↗

DOE OSTI2021

Scalable Comparative Visualization of Ensembles of Call Graphs

Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources. Code developers often explore various execution parameters, such as hardware configurations, system software choices, and application parameters, and are interested in detecting and understanding bottlenecks in different executions. They often collect hierarchical performance profiles represented as call graphs, which combine performance metrics with their execution contexts. The crucial task of exploring multiple call graphs together is tedious and challenging because of the many structural differences in the execution contexts and significant variability in the collected performance metrics (e.g., execution runtime). In this paper, we present Ensemble CallFlow to support the exploration of ensembles of call graphs using new types of visualizations, analysis, graph operations, and features. We introduce ensemble-Sankey , a new visual design that combines the strengths of resource-flow (Sankey) and box-plot visualization techniques. Whereas the resource-flow visualization can easily and intuitively describe the graphical nature of the call graph, the box plots overlaid on the nodes of Sankey convey the performance variability within the ensemble. Our interactive visual interface provides linked views to help explore ensembles of call graphs, e.g., by facilitating the analysis of structural differences, and identifying similar or distinct call graphs. Finally, we demonstrate the effectiveness and usefulness of our design through case studies on large-scale parallel codes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2024

Interpretable Machine Learning for Molecular Biosignatures: a Novel Single-Sample Feature Importance Method That Is Sensitive To Statistical Interactions

Isotope ratio mass spectrometry (IRMS) of volatiles (e.g., CO 2 ) promises to be a powerful tool for potential biosignature detection for future missions to ocean worlds (OW) such as Europa and Enceladus. Machine learning (ML) methods for IRMS data could enable science autonomy by onboard prediction of seawater chemistry and biosignature presence. However, ML models are likely to be complex and involve statistical interactions between features (variables), which can make predictions seem opaque and enigmatic. For ML predictions as significant as extraterrestrial biosignatures, we must place extraordinary confidence in models. It is therefore essential that these models make interpretable predictions (i.e., human-understandable) and include false-prediction diagnostics. We achieve high accuracy and interpretability in ML biosignature and seawater chemistry models for OW through a nearest-neighbors feature selection tool that detects statistical interactions between predictors, constructs interaction networks for visualization of selected features working together to make a prediction, and reports single-sample feature importance scores for false-detection diagnostics. Here we develop a novel single-sample nearest-neighbors projected distance regression(ssNPDR) feature selection method that improves upon existing single-sample algorithms through the inclusion of statistical interactions while providing false-prediction diagnostics for ML models.

geochemistry↗

DOE OSTI2024

Ecological Trait-Based Digital Categorization of Microbial Genomes for Denitrification Potential

Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2017

Retroreflective Background Oriented Schlieren Imaging Results from the NASA Plume/Shock Interaction Test

In support of NASA's Commercial Supersonics Technology (CST) project, a test was conducted in the 9-by-7 ft. supersonic section of the NASA Ames Unitary Plan Wind Tunnel (UPWT). The tests were designed to study the interaction of shocks with a supersonic jet characteristic of those that may occur on a commercial supersonic aircraft. Multiple shock generating geometries were tested to examine the interaction dynamics as they pertain to sonic boom mitigation. An integral part of the analyses of these interactions are the interpretation of the data generated from the retroreflective Background Oriented Schlieren (RBOS) imaging technique employed for this test. The regularization- based optical flow methodology used to generate these data is described. Sample results are compared to those using normalized cross-correlation. The reduced noise, additional feature detail, and fewer false artifacts provided by the optical flow technique produced clearer time-averaged images, allowing for better interpretation of the underlying flow phenomena. These images, coupled with pressure signatures in the near field, are used to provide an overview of the detailed interaction flowfields.

optical flow↗

DOE OSTI2016

WarpIV: In situ visualization and analysis of ion accelerator simulations

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analytics to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Electronic interactions in Dirac fluids visualized by nano-terahertz spacetime interference of electron-photon quasiparticles

Ultraclean graphene at charge neutrality hosts a quantum critical Dirac fluid of interacting electrons and holes. Interactions profoundly affect the charge dynamics of graphene, which is encoded in the properties of its electron-photon collective modes: surface plasmon polaritons (SPPs). Here, we show that polaritonic interference patterns are particularly well suited to unveil the interactions in Dirac fluids by tracking polaritonic interference in time at temporal scales commensurate with the electronic scattering. Spacetime SPP interference patterns recorded in terahertz (THz) frequency range provided unobstructed readouts of the group velocity and lifetime of polariton that can be directly mapped onto the electronic spectral weight and the relaxation rate. Our data uncovered prominent departures of the electron dynamics from the predictions of the conventional Fermi-liquid theory. The deviations are particularly strong when the densities of electrons and holes are approximately equal. The proposed spacetime imaging methodology can be broadly applied to probe the electrodynamics of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1987

Optical interferometry in fluid dynamics research

Optical interferometry techniques were applied to the investigation of transonic airfoil flow fields in large wind tunnels. Holographic interferometry techniques were used to study 2 dimensional symmetric NACA 64A010 and Douglas Aircraft Co. DSMA671 supercritical airfoil performance in the NASA Ames 2 x 2 ft transonic wind tunnel. Quantitative data obtained from the interferograms were compared to the surface pressure data. The agreement obtained verified the accuracy of the flow visualization and demonstrated the potential for acquiring quantitative scalar results. Measurements of the inviscid flow speed and the boundary layer and wake velocity profiles were extracted from the interferograms and compared to laser Doppler velocimeter measurements. These results were also in good agreement. A method for acquiring real time interferometric data in large scale facilities was developed. This method, based on the point diffraction interferometer, was successfully tested in the 2 x 2 ft transonic wind tunnel. The holographic and real time interferometry methods were applied to the investigations of circulation control airfoils utilizing the Coanda effect. These results reveals the details of the jet interacting with the trailing edge boundary layer and the other parameters affecting the lift augmentation.

Bachalo, W. D.↗

NASA NTRS1992

SKYMAP: Exploring the Universe in software

SKYMAP is a computer program which produces maps of arbitrary portions of the sky in a variety of projections and coordinate systems. Over the past ten years it has been used to produce finder charts for occultations by planets, display scan and image data from the Spacelab 2 Infrared Telescope, and make maps of fields for astronomical observations at X-ray, optical, infrared, and radio wavelengths. It can display multiple source catalogs, including the HST Guide Star Catalog, as well as solar system objects with astrometric accuracy using the JPL DE-130 ephemeris or tabulated positions. SKYMAP can be tuned to a specific task using an ASCII parameter file which controls how information is displayed on any Tektronix-compatible graphics display. The program contains a variety of interactive graphic and image processing features and has been ported to a variety of computer systems. A recent project visually demonstrates source density variation in various commonly-used all-sky catalogs.

Mink, D. J.↗

NASA NTRSDate not supplied

Time Resolved Visualization of Liquid Jet Interaction With H2-Air Rotating Detonations Using MHz Rate Diesel PLIF

The characterization of the dynamic response of liquid jets to transient detonation wave passage is critical for optimization and modeling of liquid fueled rotating detonation combustors. In this work, a rotating detonation combustor (RDC) is operated on hydrogen and air to sustain stable detonation waves that acts as a detonation driver and interact in a one-way coupled manner with a single liquid fuel jet that propagates into the combustion chamber with cycle periods of ~ 250 μs. Diesel is utilized as a realistic fuel surrogate with higher aromatic compounds to enable fluorescence excitation, using the 355 nm thirdharmonic output of a burst-mode Nd:YAG laser, imaged at rates up to 1 MHz. By optimizing the technique to accommodate orders of magnitude variations in the fuel density throughout the injection process, the PLIF data enable quantitative measurements including the refill time, the relative recovery between liquid and gaseous jets and jet trajectory across various momentum flux ratio. As the passage of the detonation wave imparts significant changes in the momentum flux ratio, the qualitative liquid break-up process and spatial distribution varies significantly in time. As the injection system recovers ~ 70% of the cycle period and return to a quasi-steady position and allow comparisons with theoretical jet trajectories. These data, enabled by ultra-high-speed PLIF imaging, represent some of the first detailed measurements for quantifying the dynamic response and recovery of liquid jets exposed to periodic detonations in an operating RDC.

Propulsion↗

NASA NTRS1993

Flow visualization of mast-mounted-sight/main rotor aerodynamic interactions

Flow visualization tests were conducted on a 27 percent-scale AH-64 attack helicopter model fitted with various mast-mounted-sight configurations in an attempt to identify the cause of adverse vibration encountered during full-scale flight tests of an Apache/Longbow configuration. The tests were conducted at the NASA Langley Research Center in the 14- by 22-Foot Subsonic Tunnel. A symmetric and an asymmetric mast-mounted-sight oriented at several skew angles were tested at forward and rearward flight speeds of 30 and 45 knots. A laser light sheet seeded with vaporized propylene glycol was used to visualize the wake of the sight in planes parallel and perpendicular to the freestream flow. Analysis of the flow visualization data identified the frequency of the wake shed from the sight, the angle-of-attack at the sight, and the location where the sight wake crossed the rotor plane. Differences in wake structure were observed between the various sight configurations and slew angles. Postulations into the cause of the adverse vibration found in flight test are given along with considerations for future tests.

Ghee, Terence A.↗

DOE OSTI2017

Interface Metaphors for Interactive Machine Learning

To promote more interactive and dynamic machine learn- ing, we revisit the notion of user-interface metaphors. User-interface metaphors provide intuitive constructs for supporting user needs through interface design elements. A user-interface metaphor provides a visual or action pattern that leverages a user’s knowledge of another domain. Metaphors suggest both the visual representations that should be used in a display as well as the interactions that should be afforded to the user. We argue that user-interface metaphors can also offer a method of extracting interaction-based user feedback for use in machine learning. Metaphors offer indirect, context-based information that can be used in addition to explicit user inputs, such as user-provided labels. Implicit information from user interactions with metaphors can augment explicit user input for active learning paradigms. Or it might be leveraged in systems where explicit user inputs are more challenging to obtain. Each interaction with the metaphor provides an opportunity to gather data and learn. We argue this approach is especially important in streaming applications, where we desire machine learning systems that can adapt to dynamic, changing data.

Interactive machine learning↗