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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 325 records · Page 18

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NASA NTRS1991

Flow visualization and flow field measurements of a 1/12 scale tilt rotor aircraft in hover

The results are given of flow visualization studies and inflow velocity field measurements performed on a 1/12 scale model of the XV-15 tilt rotor aircraft in the hover mode. The complex recirculating flow due to the rotor-wake-body interactions characteristic of tilt rotors was studied visually using neutrally buoyant soap bubbles and quantitatively using hot wire anemometry. Still and video photography were used to record the flow patterns. Analysis of the photos and video provided information on the physical dimensions of the recirculating fountain flow and on details of the flow including the relative unsteadiness and turbulence characteristics of the flow. Recirculating flows were also observed along the length of the fuselage. Hot wire anemometry results indicate that the wing under the rotor acts to obstruct the inflow causing a deficit in the inflow velocities over the inboard region of the model. Hot wire anemometry also shows that the turbulence intensities in the inflow are much higher in the recirculating fountain reingestion zone.

Coffen, Charles D.↗

NASA NTRS1991

Flow visualization and flow field measurements of a 1/12 scale tilt rotor aircraft in hover

Coffen, Charles D.↗

NASA NTRS1997

Interaction of Burning Metal Particles

Multiple particle/droplet flames are ubiquitous in practical combustion systems, and thus the flame interaction processes are of great practical importance. This explains the strong current interest in interactive combustion phenomena. This research is aimed at the investigation of combustion parameters of microgravity model aerosols: relatively large uniform metal particles aerosolized in microgravity environment. An experiment consisting of creation and ignition of a metal multiparticle system in microgravity and high-speed video-recording of the combustion events will produce visual records of the development of individual particle flames, their interactions and the particle motion they induce simultaneously with the observation of the entire aerosol combustion process. Frame by frame analysis of the video-images taken using a high-speed movie camera will allow one to determine particle brightness temperatures and the decrease in particle diameter during combustion. Analysis of the experimental results and comparison with the results of single metal particle combustion experiments, conducted under similar microgravity conditions in the framework of a parallel program, will establish the relationship between single and multiple particle burning rates and combustion temperatures, concentrations at which the flame substructure forms rather than individual particle flames, efficiency of radiative heat transfer in metal aerosol combustion, what is the role of electrostatic forces in structuring the flame and the effect of that structure on the flame propagation rate. Although some details of fine particle aerosol clouds, such as the kinetics limited burning rate, radiative heat transfer in a system with a high specific surface, particle induced turbulence, etc., will probably not be very well simulated in the planned experiments, they are relatively well understood and can be accounted for using an adequate individual particle combustion model. On the other hand, the unknown particle interaction phenomena to be studied in this research program are generic and can be readily projected onto a cloud combustion model which would also incorporate a correction for particle size.

Dreizin, Edward L.↗

NASA NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Our work explores the use of extended reality (XR) to im- prove scientific discovery with numerical weather/climate models that inform Earth science digital twins, specifically the NASA Goddard Earth Observing System (GEOS) global atmospheric model. The overall project is named the Vi- sualization And Lagrangian dynamics Immersive eXtended Reality Toolkit (VALIXR), which has two main areas of focus: (1) enhancing the understanding of and interaction with model output data through advanced visualizations in the XR environment, and (2) the integration of Lagrangian dynamics into the GEOS model, which allows a natural, feature-specific analysis of Earth science phenomena as op- posed to traditional, fixed-point Eulerian dynamics. Here, we report initial work on these focus areas.

Thomas Grubb↗

NASA NTRS2003

Coordinated turn-and-reach movements. II. Planning in an external frame of reference

The preceding study demonstrated that normal subjects compensate for the additional interaction torques generated when a reaching movement is made during voluntary trunk rotation. The present paper assesses the influence of trunk rotation on finger trajectories and on interjoint coordination and determines whether simultaneous turn-and-reach movements are most simply described relative to a trunk-based or an external reference frame. Subjects reached to targets requiring different extents of arm joint and trunk rotation at a natural pace and quickly in normal lighting and in total darkness. We first examined whether the larger interaction torques generated during rapid turn-and-reach movements perturb finger trajectories and interjoint coordination and whether visual feedback plays a role in compensating for these torques. These issues were addressed using generalized Procrustes analysis (GPA), which attempts to overlap a group of configurations (e.g., joint trajectories) through translations and rotations in multi-dimensional space. We first used GPA to identify the mean intrinsic patterns of finger and joint trajectories (i.e., their average shape irrespective of location and orientation variability in the external and joint workspaces) from turn-and-reach movements performed in each experimental condition and then calculated their curvatures. We then quantified the discrepancy between each finger or joint trajectory and the intrinsic pattern both after GPA was applied individually to trajectories from a pair of experimental conditions and after GPA was applied to the same trajectories pooled together. For several subjects, joint trajectories but not finger trajectories were more curved in fast than slow movements. The curvature of both joint and finger trajectories of turn-and-reach movements was relatively unaffected by the vision conditions. Pooling across speed conditions significantly increased the discrepancy between joint but not finger trajectories for most subjects, indicating that subjects used different patterns of interjoint coordination in slow and fast movements while nevertheless preserving the shape of their finger trajectory. Higher movement speeds did not disrupt the arm joint rotations despite the larger interaction torques generated. Rather, subjects used the redundant degrees of freedom of the arm/trunk system to achieve similar finger trajectories with differing joint configurations. We examined finger movement patterns and velocity profiles to determine the frame of reference in which turn-and-reach movements could be most simply described. Finger trajectories of turn-and-reach movements had much larger curvatures and their velocity profiles were less smooth and less bell-like in trunk-based coordinates than in external coordinates. Taken together, these results support the conclusion that turn-and-reach movements are controlled in an external frame of reference.

NASA Discipline Neuroscience↗

DOE OSTI2018

Creating an Interprocedural Analyst-Oriented Data Flow Representation for Binary Analysts (CIAO)

National security missions require understanding third-party software binaries, a key element of which is reasoning about how data flows through a program. However, vulnerability analysts protecting software lack adequate tools for understanding data flow in binaries. To reduce the human time burden for these analysts, we used human factors methods in a rolling discovery process to derive user-centric visual representation requirements. We encountered three main challenges: analysis projects span weeks, analysis goals significantly affect approaches and required knowledge, and analyst tools, techniques, conventions, and prioritization are based on personal preference. To address these challenges, we initially focused our human factors methods on an attack surface characterization task. We generalized our results using a two-stage modified sorting task, creating requirements for a data flow visualization. We implemented these requirements partially in manual static visualizations, which we informally evaluated, and partially in automatically generated interactive visualizations, which have yet to be integrated into workflows for evaluation. Our observations and results indicate that 1) this data flow visualization has the potential to enable novel code navigation, information presentation, and information sharing, and 2) it is an excellent time to pursue research applying human factors methods to binary analysis workflows.

42 ENGINEERING↗

DOE OSTI2021

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis

This study aims to effectively analyze and visualize the concept to concept network derived from the COVID-19 Open Research Dataset (CORD-19) dataset, where we have more than 48,000 concepts with more than 300,000 relationships between concepts. In analyzing networks, we focus on finding relationship patterns between the coronavirus disease 2019 (COVID-19) concepts and other concepts. Given the node and edge datasets, we construct directional graphs and calculate all pair shortest paths based on multiple edge weight schemes. However, statistical metrics are not sufficient to identify specific relationships represented in the network. Therefore, we also propose a visual analytics approach to effectively understand the knowledge graph. Our highly interactive visual analytics allows users to effectively analyze the evolving graphs and (COVID-19) concept nodes and other nodes related to the COVID-19 nodes. We envision that this study will pave the path to develop strategies to provide more accurate and scalable predictive analysis on knowledge graphs related to CORD19 and other biomedical knowledge graphs.

Lim, Seung-Hwan↗

DOE OSTI2024

FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier‐Transform Mass Spectrometry Data

The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner. FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise. FREDA was built to explore outputs from a molecular identification tool, like CoreMS, and provide a suite of methods to filter data, compute chemical properties of peaks, statistically compare samples and groups of samples, conduct exploratory data analysis, and download the results with a report detailing all steps conducted. To demonstrate the utility of FREDA, an example analysis was conducted using FT-MS data from a soil microbiology study of samples collected in two different soil depths at the Sphagnum bog forest north of Grand Rapids, Minnesota. Differences between the two depths are observed using Kendrick, Gibbs free energy, and van Krevelen plots. G-tests are used to quantify a significant difference between the groups. All analyses and plotting are conducted using only the FREDA application. FREDA is an open-source and readily available web application that allows users to explore and make statistically valid conclusions about their FT-MS data. The application is available online (https://map.emsl.pnnl.gov/app/freda) with a tutorial web series (https://youtu.be/k5HLE2kNSBY?si=yB6sGoyvzxrFf5MP) and freely accessible code on Github (https://github.com/EMSL-Computing/FREDA).

47 OTHER INSTRUMENTATION↗

NASA NTRS2023

Information Systems Technology for NASA Earth Systems Digital Twins (ESDT)

The term “Digital Twin” was first used in 2002 for product lifecycle management. Since then, Digital Twin concepts have been proposed in various domains until very recently for Earth Science. For NASA’s Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as composed of three components: 1. A Digital Replica, i.e., an integrated picture of the past and current states of Earth systems 2. Forecasting capabilities, providing an integrated picture of how Earth systems will evolve in the future from the current state 3. Impact Assessment capabilities, providing an integrated picture of how Earth systems could evolve under different hypothetical what-if scenarios. Developing such a vision will require technologies related to: integrating continuous observations from various disparate sources; developing frameworks that builds on inter-connected models; improving the speed and accuracy of integrated prediction, analysis and visualization capabilities (e.g., by using machine learning); and utilizing causality and uncertainty quantification to improve our understanding of the evolution of Earth Science systems as a function of their interactions with other Earth and human systems. In addition, AIST is also investigating interoperability standards to federate multiple Digital Twins, as well as computational resources required by those systems.

Earth Science Remote Sensing; Information Systems↗

DOE OSTI2019

Deep learning analysis of defect and phase evolution during electron beam-induced transformations in WS2

Abstract Recent advances in scanning transmission electron microscopy (STEM) allow the real-time visualization of solid-state transformations in materials, including those induced by an electron beam and temperature, with atomic resolution. However, despite the ever-expanding capabilities for high-resolution data acquisition, the inferred information about kinetics and thermodynamics of the process, and single defect dynamics and interactions is minimal. This is due to the inherent limitations of manual ex situ analysis of the collected volumes of data. To circumvent this problem, we developed a deep-learning framework for dynamic STEM imaging that is trained to find the lattice defects and apply it for mapping solid state reactions and transformations in layered WS 2 . The trained deep-learning model allows extracting thousands of lattice defects from raw STEM data in a matter of seconds, which are then classified into different categories using unsupervised clustering methods. We further expanded our framework to extract parameters of diffusion for sulfur vacancies and analyzed transition probabilities associated with switching between different configurations of defect complexes consisting of Mo dopant and sulfur vacancy, providing insight into point-defect dynamics and reactions. This approach is universal and its application to beam-induced reactions allows mapping chemical transformation pathways in solids at the atomic level.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Final Report: Modeling coupled ice sheet-ocean interactions in the Model for Prediction Across Scales (MPAS) and in DOE Earth System Models

Ice sheet-ocean interactions are involved in a potential climate tipping point in the climate system. Weakening of dynamical ocean barriers that currently hold warmer waters off the Antarctic continental shelf could lead to warming under Antarctica’s largest ice shelves, causing as much as a hundredfold increase in sub-ice-shelf melting. Increased ice-sheet melting could trigger dynamical instabilities in the ice sheet itself if sufficient buttressing from ice shelves is lost. This project developed and tested several modeling capabilities needed to investigate these phenomena. In collaboration with a number of international groups, notably the climate modeling group at Los Alamos National Laboratory (LANL), the following capabilities were added to the Energy Exascale Earth System Model (E3SM) and its ocean component (the Model for Prediction Across Scales Ocean, MPAS-Ocean): 1) a new vertical coordinate appropriate for ice-shelf cavities; 2) an initialization procedure appropriate for damping waves from imbalances in ocean pressure and that of the overlying ice shelf; 3) A suite of idealized test cases related to ice shelf-ocean interactions; 4) A set of diagnostics for tracking freshwater fluxes and heat budgets from ice-shelf melting; 5) infrastructure for computing ice sheet-ocean fluxes in the E3SM coupler; and 6) A set of analysis and visualization tools for E3SM ocean and sea-ice validation with a particular focus on Antarctic and Southern Ocean climate. Additionally, the project included participation and leadership in a number of international model intercomparison projects (MIPs). Most notably, the PI was a co-chair of the Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP), designing the experiment, coordinating participation in the MIP and performing the bulk of the analysis. Although the project was cut short when the PI accepted a staff scientist position at LANL, the project played a role in seven publications and has segued smoothly into ongoing Department of Energy projects in the “ecosystem” surrounding E3SM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario

Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish common ground among collaborators. The use of provenance to communicate analytic sensemaking carries promise by describing the interactions and summarizing the steps taken to reach insights. Yet, no universal guidelines exist for communicating provenance in different settings. Our work here focuses on the presentation of provenance information and the resulting conclusions reached and strategies used by new analysts. In an open-ended, 30-minute, textual exploration scenario, we qualitatively compare how adding different types of provenance information (specifically data coverage and interaction history) affects analysts' confidence in conclusions developed, propensity to repeat work, filtering of data, identification of relevant information, and typical investigation strategies. We see that data coverage (i.e., what was interacted with) provides provenance information without limiting individual investigation freedom. On the other hand, while interaction history (i.e., when something was interacted with) does not significantly encourage more mimicry, it does take more time to comfortably understand, as represented by less confident conclusions and less relevant information-gathering behaviors. In conclusion, our results contribute empirical data towards understanding how provenance summarizations can influence analysis behaviors.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Investigating intermolecular interactions among CO 2 , water and PEEK-ionene membrane using cryo ToF-SIMS and isotopic labeling

Cryogenic time-of-flight secondary ion mass spectrometry (cryo ToF-SIMS) has emerged as a powerful tool for investigating molecular interactions, speciation, and dynamics in materials for CO 2 capture. In this study, we apply cryo ToF-SIMS to probe interactions between CO 2 , water, and PEEK-ionene membranes—a promising material for direct CO 2 capture due to its selectivity, durability, and efficiency. Despite this potential, the mechanisms governing CO 2 diffusion and the influence of water vapor on CO 2 behavior remain unclear. To address this, we loaded PEEK-ionene membranes with 13 CO 2 and D 2 O and employed cryo ToF-SIMS to visualize the 3D distribution of CO 2 and water within the membrane. While prior studies suggest that 13 CO 2 is absorbed under ambient conditions, our cryo ToF-SIMS analysis revealed no enhancement of the 13 C/ 12 C ratio, suggesting weak CO 2 -membrane interactions. As a result, CO 2 vaporizes even at low temperatures (−140°C) under vacuum conditions. In contrast, D 2 O displayed a relatively homogeneous distribution in the membrane, suggesting stronger water-membrane interactions via hydrogen bonding (18–20 kJ/mol). Interestingly, CO 2 was not detected in D 2 O-loaded membranes, indicating minimal interference from water vapor on CO 2 diffusion. As a comparison, the cryo ToF-SIMS data show that 13 CO 2 can readily react with a basic Na 2 CO 3 aqueous solution to form NaH 13 CO 3 . These findings demonstrate cryo ToF-SIMS as a critical technique for understanding gas-water-membrane interactions, offering insights for membrane functionalization to improve CO 2 capture efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

CCQE-like $\nu_{e}$ Selection in SBND using Convolutional Visual Network

Neutrinos from the Booster Neutrino Beam (BNB) at Fermilab interact with argon in a Liquid Argon Time Projection Chamber (LArTPC) differently based on their flavour. By examining the particles produced in a charged-current interaction, both the interaction type and the neutrino flavour can be inferred. The Short Baseline Near Detector has the largest neutrino-argon cross section data to date, motivating in-depth studies of various cross-section channels and topologies. This project aims to select electron neutrino quasi-elastic-like (QE-like) interactions in SBND using Convolutional Visual Network (CVN) scores. The CVN is a neural network that processes visual information from an event and assigns scores corresponding to its likelihood of being each interaction type. An inclusive study of electron neutrino charged current interactions using CVN has already been conducted. This analysis aims to build on this study, further utilizing CVN scores to isolate electron neutrino QE-like interactions characterized by the presence of an electron and one or more protons ($N > 0$) in the final state. The project s goal is to contribute to the overall cross-section measurement efforts within the SBN program at Fermilab.

Breen, Genevieve [Mt. Holyoke Coll.]↗

NASA NTRS2023

Exploring Interactive Visuals for Orbital Debris Report

NASA often produces reports or memos that include complex data and these findings can often be most effectively communicated using dynamic or interactive visualizations. While newsrooms, such as the New York Times, and academic journals, such as Distill, have demonstrated the power of interactivity within a prose context (i.e., not dashboards), NASA is still lagging in this area. A shift towards more interactive NASA publications will require new technology and expertise. In this presentation, we begin to explore the avenues that the Office of Technology, Policy, and Strategy are using to make its reports interactive by using results from the “Cost and benefit Analysis of Orbital Debris Remediation” as initial examples. We share our current findings and aim to start a discussion with other members of the NASA analytics community interested in or currently adding interactivity to Agency products.

data visualization↗

DOE OSTI2022

A geo-visual analysis for exploring the socioeconomic benefits of the heating electrification using geothermal energy

In parallel to population growth and climate change, the rapid pace of urbanization worldwide has led to an enormous increase in energy demand and costs in urban areas. The subsequent energy burden has become an increasing concern for many households in the U.S. Previous studies have revealed that geothermal resources can effectively lower the electricity demand and carbon emissions in large cities. In this paper, we focus on the socioeconomic impacts of geothermal energy on urban systems by presenting an interactive visual analytics dashboard. The dashboard allows urban planners to spatially examine geothermal energy's practical benefits on energy affordability, urban livability, and resilience across the U.S. We compiled a list of socioeconomic metrics by integrating the simulation results from multiple geothermal and building models with multi-domain urban datasets (socioeconomic, demographic, and electricity utility). These metrics are created to characterize the benefits of the heating electrification of buildings using Geothermal Heat Pumps (GHP) for lowering the energy burden of middle-and low-income households nationwide. The visual dashboard employs a combination of multivariate, glyph-based, and geospatial visualization to reveal the variability and patterns in our metrics. We present a pilot study to demonstrate the GHPs' potential as a renewable and affordable solution for increasing the economic and energy grid resilience in U.S cities.

Xu, Haowen↗

NASA NTRS2012

3D Visualization for Phoenix Mars Lander Science Operations

Planetary surface exploration missions present considerable operational challenges in the form of substantial communication delays, limited communication windows, and limited communication bandwidth. A 3D visualization software was developed and delivered to the 2008 Phoenix Mars Lander (PML) mission. The components of the system include an interactive 3D visualization environment called Mercator, terrain reconstruction software called the Ames Stereo Pipeline, and a server providing distributed access to terrain models. The software was successfully utilized during the mission for science analysis, site understanding, and science operations activity planning. A terrain server was implemented that provided distribution of terrain models from a central repository to clients running the Mercator software. The Ames Stereo Pipeline generates accurate, high-resolution, texture-mapped, 3D terrain models from stereo image pairs. These terrain models can then be visualized within the Mercator environment. The central cross-cutting goal for these tools is to provide an easy-to-use, high-quality, full-featured visualization environment that enhances the mission science team s ability to develop low-risk productive science activity plans. In addition, for the Mercator and Viz visualization environments, extensibility and adaptability to different missions and application areas are key design goals.

Edwards, Laurence↗

DOE OSTI2017

Status of a Deep Learning Based Measurement of the Inclusive Muon Neutrino Charged-current Cross Section in the NOvA Near Detector

NOvA is a long-baseline neutrino oscillation experiment. It uses the NuMI beam from Fermilab and two sampling calorimeter detectors placed off-axis from the beam. The 293 ton Near Detector measures the unoscillated neutrino energy spectrum, which can be used to predict the neutrino energy spectrum observed at the 14 kton Far Detector. The Near Detector also provides an excellent opportunity to measure neutrino interaction cross sections with high statistics, which will benefit current and future long-baseline neutrino oscillation experiments. This analysis implements new algorithms to identify $\nu_{\mu}$ charge-current events by using visual deep learning tools such as convolutional neural networks. We present the status of a measurement of the inclusive $\nu_{\mu}$ CC cross section in the NOvA Near Detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗