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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Integrated Data Visualization for Human Missions

Interplanetary missions produce exceptionally large and complex volumes of data that can be extremely difficult to navigate. This is especially true for human missions. This project seeks to develop an integrated data visualization environment that builds on the success of Apollo17.org allowing for integration of operational, engineering and scientific data while also preserving the context under which it was collected during the mission. We will build a product that integrates existing data from the Neutral Buoyancy Lab (NBL) to improve data visualization for extra vehicular activity and interplanetary missions.

Regberg, Aaron B.↗
NASA NTRS2011

Visible and Near-IR Reflectance Spectra of Smectite Acquired Under Dry Conditions for Interpretation of Martian Surface Mineralogy

Visible and near-IR (VNIR) spectra from the MEx OMEGA and the MRO CRISM hyper-spectral imaging instruments have spectral features associated with the H2O molecule and M OH functional groups (M = Mg, Fe, Al, and Si). Mineralogical assignments of martian spectral features are made on the basis of laboratory VNIR spectra, which were often acquired under ambient (humid) conditions. Smectites like nontronite, saponite, and montmorillionite have interlayer H2O that is exchangeable with their environment, and we have acquired smectite reflectance spectra under dry environmental conditions for interpretation of martian surface mineralogy. We also obtained chemical, Moessbauer (MB), powder X-ray diffraction (XRD), and thermogravimetric (TG) data to understand variations in spectral properties. VNIR spectra were recorded in humid lab air at 25-35C, in a dynamic dry N2 atmosphere (50-150 ppmv H2O) after exposing the smectite samples (5 nontronites, 3 montmorillionites, and 1 saponite) to that atmosphere for up to approximately l000 hr each at 25-35C, approximately 105C, and approximately 215C, and after re-exposure to humid lab air. Heating at 105C and 215C for approximately 1000 hr is taken as a surrogate for geologic time scales at lower temperatures. Upon exposure to dry N2, the position and intensity of spectral features associated with M-OH were relatively insensitive to the dry environment, and the spectral features associated with H2O (e.g., approximately 1.90 micrometers) decreased in intensity and are sometimes not detectable by the end of the 215C heating step. The position and intensity of H2O spectral features recovered upon re-exposure to lab air. XRD data show interlayer collapse for the nontronites and Namontmorillionites, with the interlayer remaining collapsed for the latter after re-exposure to lab air. The interlayer did not collapse for the saponite and Ca-montmorillionite. TG data show that the concentration of H2O derived from structural OH was invariant to the dry N2 treatment for saponite and the montmorillionites, but the nontronites had additional structural OH after treatment. Upon exposure to dry N2, the VNIR spectra also acquired a red slope with decreasing albedo between approximately 0.4 and approximately 2.0 micrometers. The magnitude of the effects covaries with exposure time to dry N2 and heating temperature. Upon re-exposure to lab air, the slope and albedo do not completely recover to pre-exposure values. MB data show that these effects do not result from partial reduction of ferric to ferrous iron, and TG data show they do not result from loss of structural OH. Possible explanations include formation of small clusters of (superparamagnetic) ferric oxide and reduced smectite crystallinity. The difference in spectral properties between spectra acquired in humid lab air and under dry conditions are consequential for interpretation of CRISM and OMEGA spectra. For example, nontronite by itself and not nontronite plus ferrihydrite can account for the red spectral slope in martian spectra where nontronite is indicated by the Fe-OH spectral features.

Morris, Richard V.↗
DOE OSTI2024

Variational inference of effective range parameters for 3 He− 4 He scattering

We use two different methods, Monte Carlo sampling and variational inference (VI), to perform a Bayesian calibration of the effective-range parameters in 3 He– 4 He elastic scattering. The parameters are calibrated to data from a recent set of 3 He– 4 He elastic scattering differential cross section measurements. Analysis of these data for E lab ≤ 4.3 MeV yields a unimodal posterior for which both methods obtain the same structure. However, the effective-range expansion amplitude does not account for the 7/2 − state of 7 Be so, even after calibration, the description of data at the upper end of this energy range is poor. The data up to E lab = 2.6 MeV can be well described, but calibration to this lower-energy subset of the data yields a bimodal posterior. After adapting VI to treat such a multi-modal posterior we find good agreement between the VI results and those obtained with parallel-tempered Monte Carlo sampling.

effective field theory↗
DOE OSTI2022

Lab-on-a-Fish Monitoring Software V1.0

This is the original monitoring software for processing and displaying data for Lab-on-a-Fish. Lab-on-a-Fish simultaneously evaluates and monitors the health, behavior, and environment of fish or small aquatic species. The sensor is a miniaturized underwater monitoring system that measures animal behavior (acceleration and gyration); physiology (electrocardiogram and electromyogram); and environmental parameters (temperature, pressure, and magnetic sensor).

Deng, Daniel↗
NASA NTRS2014

The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation

From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of graphs from BDRA's past work supporting operations and/or research efforts.

Babiak-Vazquez, A.↗
NASA NTRSDate not supplied

Performance Risk Model Validation with Operationally Relevant Tasks

Human Research Program aims to develop methods to support astronauts’ health and productivity during spaceflight. The Crew Health and Performance Probabilistic Risk Assessment (CHP-PRA) team uses powerful computational methods to predict mission risk in both domains: medical and performance. Here, we show how CHP-PRA uses the Performance Risk Model (PRisM) to quantify the performance risk and show an application of the model on operationally relevant tasks. There are various metrics adopted across performance researchers that PRisM can accommodate. For data analysis, interpretation, and integration, we use a method of unifying data from multiple sources by converting each to a single metric. We consult subject matter experts prior to integrating the converted data into PRisM. The method we use is inspired by the Cooper-Harper rating scale [1]. Using this unified metric, we can easily combine data from various tests and lab groups. We explain our conversion method in detail and show how it pertains to the process of testing and validation of PRisM on operational tasks. We conducted an initial validation in collaboration with the Behavioral Health and Performance (BHP) lab. We test PRisM using data on their operationally relevant task ROBoT-r, a track-and-capture task for grappling incoming resupply vehicles [2]. Several other labs at NASA Johnson Space Center worked together to design 7 Functional Task Tests (FTTs) in pursuit of simulating the tasks required after landing on a planetary surface and after return to Earth [3]. Here we use the results from both ROBoT-r and the 7 FTTs and compare their experiment data to PRisM’s computational output to demonstrate how PRisM can support operations by predicting crew performance on future missions.

performance modeling↗
DOE OSTI2022

Multi-lab study on the pure-gas permeation of commercial polysulfone (PSf) membranes: Measurement standards and best practices

Gas-separation membranes are a critical industrial component for a low-carbon and energy-efficient future. As a result, many researchers have been testing membrane materials over the past several decades. Unfortunately, almost all membrane-based testing systems are home-built, and there are no widely accepted material standards or testing protocols in the literature, making it challenging to accurately compare experimental results. Further, in this multi-lab study, ten independent laboratories collected high-pressure pure-gas permeation data for H 2 , O 2 , CH 4 , and N 2 in commercial polysulfone (PSf) films. Equipment information, testing procedures, and permeation data from all labs were collected to provide (1) accepted H 2 , O 2 , CH 4 , and N 2 permeability values at 35°C in PSf as a reference standard, (2) statistical analysis of lab-to-lab uncertainties in evaluating permeability, and (3) a list of best practices for sample preparation, equipment set-up, and permeation testing using constant-volume variable-pressure apparatuses. Results summarized in this work provide a reference standard and recommended testing protocols for pure-gas testing of membrane materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Study of Nuclear Structure Functions at Jefferson Lab

This thesis presents a study of nuclear modification of quark distributions (the EMC effect) using inclusive electron-scattering data from Jefferson Lab Hall C, with emphasis on experiment E12-10-008 (XEM2). The analysis spans nuclei from light to heavy targets and combines measurements at multiple spectrometer settings to constrain EMC ratios over a broad range in Bjorken-x and Q2. A complete analysis framework was developed to extract charge-normalized and efficiency-corrected yields, including detector calibrations, beam-current calibration, density-loss corrections for cryogenic targets, background subtraction, radiative and Coulomb corrections, and systematic studies. Instrumental cross-checks, including HMS–SHMS comparisons and reconstruction studies, show that residual spectrometer differences are predominantly multiplicative in the kinematic region relevant to the EMC analysis. The extracted EMC ratios are broadly consistent with previous measurements while extending coverage across many nuclei. The EMC slope increases from light to heavy nuclei and shows signs of saturation at large A. After accounting for the dominant A dependence, the results are consistent with no isospin dependence, but also consistent with the predicted modification from the isovector model.

Sharda, Abhyuday [Univ. of Tennessee, Knoxville, T↗
NASA NTRS1990

Experimental characterization of the effects of pneumatic tubing on unsteady pressure measurements

Advances in aircraft control system designs have, with increasing frequency, required that air data be used as flight control feedback. This condition requires that these data be measured with accuracy and high fidelity. Most air data information is provided by pneumatic pressure measuring sensors. Typically unsteady pressure data provided by pneumatic sensing systems are distorted at high frequencies. The distortion is a result of the pressure being transmitted to the pressure sensor through a length of connective tubing. The pressure is distorted by frictional damping and wave reflection. As a result, air data provided all-flush, pneumatically sensed air data systems may not meet the frequency response requirements necessary for flight control augmentation. Both lab and flight test were performed at NASA-Ames to investigate the effects of this high frequency distortion in remotely located pressure measurement systems. Good qualitative agreement between lab and flight data are demonstrated. Results from these tests are used to describe the effects of pneumatic distortion in terms of a simple parametric model.

Whitmore, Stephen A.↗
DOE OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository: Preprint

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗
DOE OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗
DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗
DOE OSTI2022

EJFAT: Towards Intelligent Compute Destination Load Balancing

To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.

Lawrence, David↗
NASA NTRS1994

Numerical modeling studies of wake vortex transport and evolution within the planetary boundary layer

The proposed research involves four tasks. The first of these is to simulate accurately the turbulent processes in the atmospheric boundary layer. TASS was originally developed to study meso-gamma scale phenomena, such as tornadic storms, microbursts and windshear effects in terminal areas. Simulation of wake vortex evolution, however, will rely on appropriate representation of the physical processes in the surface layer and mixed layer. This involves two parts. First, a specified heat flux boundary condition must be implemented at the surface. Using this boundary condition, simulation results will be compared to experimental data and to other model results for validation. At this point, any necessary changes to the model will be implemented. Next, a surface energy budget parameterization will be added to the model. This will enable calculation of the surface fluxes by accounting for the radiative heat transfer to and from the ground and heat loss to the soil rather than simple specification of the fluxes. The second task involves running TASS with prescribed wake vortices in the initial condition. The vortex models will be supplied by NASA Langley Research Center. Sensitivity tests will be performed on different meteorological environments in the atmospheric boundary layer, which include stable, neutral, and unstable stratifications, calm and severe wind conditions, and dry and wet conditions. Vortex strength may be varied as well. Relevant non-dimensional parameters will include the following: Richardson number or Froude number, Bowen ratio, and height to length scale ratios. The model output will be analyzed and visualized to better understand the transport, decay, and growth rates of the wake vortices. The third task involves running simulations using observed data. MIT Lincoln Labs is currently planning field experiments at the Memphis airport to measure both meteorological conditions and wake vortex characteristics. Once this data becomes available, it can be used to validate the model for vortex behavior under different atmospheric conditions. The fourth task will be to simulate the wake in a more realistic environment covering a wider area. This will involve grid nesting, since high resolution will be required in the wake region but a larger total domain will be used. During the first allocation year, most of the first task will be accomplished.

Lin, Yuh-Lang↗
NASA NTRS2020

Laboratory Studies of Astronomical Ices: Reaction Chemistry and Spectroscopy

In this article, we will describe the work of the Cosmic Ice Laboratory at NASA’s Goddard Space Flight Center to characterize the composition of and to understand the chemistry occurring in icy bodies in the Solar System and beyond. Our work has touched on a wide range of extraterrestrial environments including icy interstellar grains, small bodies such as comets and asteroids, and planets and moons. We are especially interested in the chemical and physical changes that occur in ices as a result of thermal changes or exposure to radiation. To this end, we conduct experiments designed to simulate cold extraterrestrial environments and measure physical properties of single- and multi-component ices. We expose ices to radiation (e.g., MeV protons or keV-MeV electrons) or high-energy photons (e.g., UV) to initiate physical and chemical changes. We conduct experiments using cryo-vacuum chambers equipped with analytical tools and radiation sources to make most of our measurements, including the collection of all spectroscopic data,in situ. When possible and appropriate, we also collect reaction products for further ex situ analysis. The work of the Cosmic Ice Lab provides critical data to astrochemists and others seeking to understand observations, make predictions, and plan future space missions.

Christopher K Materese↗