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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Global Observations - The Key to Model Development and Improved Assessments

One application of global models is to predict the response of stratospheric ozone to changes in composition and climate. The recent international ozone assessment included results from three-dimensional models with interactions among the dynamical, photochemical and radiative processes that all influence ozone behavior. The physical basis of such models is far more realistic than that of either the one-dimensional (single profile) models of the 1970's and early 1980's or the two-dimensional (latitude height) models of the late 1980's and 1990's. Observations have played a key role in the model development at all stages. This talk will highlight the role of observations in inspiring broad model improvements that have grown from the effort to reproduce observed relationships or processes, for example the correlations between long-lived constituents seen in aircraft data and the deep unmixed descent of mesospheric air into the winter polar vortices seen from satellite. The talk will also trace the evolution of model evaluation from contour plots showing 'good agreement' to the more rigorous process-oriented evaluation of three-dimensional models that is becoming the norm using the wealth of space-based observations obtained from the late 1970's until present.

Douglass, Anne R.↗
NASA NTRS2011

IMP-8 Magnetometer Experiment

IMP-8 (IMP-J) was launched by NASA on October 26, 1973 to measure the magnetic fields, plasmas, and energetic charged particles (e.g., cosmic rays) of the Earth's magnetotail and magnetosheath and of the near-Earth solar wind. IMP-8, the last often IMP (Interplanetary Monitoring Platform) or AIMP (Anchored-IMP) spacecraft launched in 10 years, operated until October 7, 2006, in a near-circular, 35 Earth Radii, 12-day orbit. It was an important adjunct to the International Solar Terrestrial Physics program, provided in-ecliptic, one Astronomical Unit baseline data for the deep space Pioneer, Voyager and Ulysses missions, and built a long-time-series database useful in understanding long-term solar processes .

Szabo, Adam↗
NASA NTRS2011

Cassini Observations of Plasmoid Structure and Dynamics: Implications for the Role of Magnetic Reconnection in Magnetospheric Circulation at Saturn

We survey the Cassini magnetometer data during the deep tail orbits in 2006, and find 34 direct encounters with plasmoids. They occur as single, isolated events but also in groups of two or more plasmoids as is frequently observed at Earth . We show a case study example of three such plasmoids over three hours, where we estimate an upper limit of 5.68 GWb of flux closure, and derive a reconnection rate over this interval of 526 kV. We show the results of a superposed epoch analysis of al1 34 plasmoids indicating that, on average, plasmoids at Saturn are approix.8 min in duration and they tend toward a loop-like, as opposed to flux rope-like topology, with little or no axial core magnetic field. Our analysis shows that plasmoids at Saturn are followed by an extended interval of the post-plasmoid plasma sheet (PPPS) lasting approx.58 min. The average open magnetic flux disconnected by the continued reconnet:tion following plasmoid formation that creates the PPPS is approx.3 GWb. We calculate expected recurrence rates for plasmoids, and compare these with a derived observational recurrence rate of one plasmoid every approx.2.4 days, explaining the reasons why the spacecraft has not observed as many plasmoids as we predict will be released. We conclude that the Cassini magnetometer measurements require a combination of Vasyliunas-type closed-flux plasma sheet and Dungey-type open-flux lobe reconnection to account for the observed properties of the plasmoids and PPPS in Saturn's magnetotail.

Jackman, C. M.↗
NASA NTRS2016

Human Exploration System Test-Bed for Integration and Advancement (HESTIA) Support of Future NASA Deep-Space Missions

The Engineering Directorate at the NASA - Johnson Space Center is outfitting a 20-Foot diameter hypobaric chamber in Building 7 to support future deep-space Environmental Control & Life Support System (ECLSS) research as part of the Human Exploration System Test-bed for Integration and Advancement (HESTIA) Project. This human-rated chamber is the only NASA facility that has the unique experience, chamber geometry, infrastructure, and support systems capable of conducting this research. The chamber was used to support Gemini, Apollo, and SkyLab Missions. More recently, it was used to conduct 30-, 60-, and 90-day human ECLSS closed-loop testing in the 1990s to support the International Space Station and life support technology development. NASA studies show that both planetary surface and deep-space transit crew habitats will be 3-4 story cylindrical structures driven by human occupancy volumetric needs and launch vehicle constraints. The HESTIA facility offers a 3-story, 20-foot diameter habitat consistent with the studies' recommendations. HESTIA operations follow stringent processes by a certified test team that including human testing. Project management, analysis, design, acquisition, fabrication, assembly and certification of facility build-ups are available to support this research. HESTIA offers close proximity to key stakeholders including astronauts, Human Research Program (who direct space human research for the agency), Mission Operations, Safety & Mission Assurance, and Engineering Directorate. The HESTIA chamber can operate at reduced pressure and elevated oxygen environments including those proposed for deep-space exploration. Data acquisition, power, fluids and other facility resources are available to support a wide range of research. Recently completed HESTIA research consisted of unmanned testing of ECLSS technologies. Eventually, the HESTIA research will include humans for extended durations at reduced pressure and elevated oxygen to demonstrate very high reliability of critical ECLSS and other technologies.

Marmolejo, Jose↗
NASA NTRS2004

6-DOF aerobraking trajectory reconstruction by use of inertial measurements unit (IMU) data for the improvement of aerobraking navigation

For any interplanetary mission, there are certain types of data that are used as a means of determining both the position and velocity of a spacecraft. The data types currently in use are Doppler, Range, Optical and VLBI. All of them are radiometric with the exception of the Optical data type. NASA's Deep Space Network is employed for the purpose of transmitting and receiving data to and from the spacecraft repsectively. For this exchange of information to take place, both the DSN and spacecrft high gain antennae must be pointed towards each other.

Lisano, Michael E.↗
NASA NTRSDate not supplied

Dynamical Considerations of Hypothesized Vertically Stacked Meridional Circulation Cells in the Ice Giant Atmospheres

This study examines the dynamical implications of the vertically stacked meridional circulation structure hypothesized for the atmospheres of Uranus and Neptune. The existence of vertically stacked circulation cells was first hypothesized for Jupiter to explain the puzzling observation during Voyager and Galileo missions that Jupiter’s thunderstorms tend to erupt in regions where the atmosphere is expected to have enhanced static stability rather than reduced static stability. Since then, Juno has added a wealth of data, including the deep ammonia distribution, to add further context to this hypothesis. For the Ice Giant planets, a similar hypothesis for vertically stacked circulation was proposed to explain the meridional distribution of methane in the upper troposphere near the 1-bar level, and further hypothesized that Uranus and Neptune may harbor three layers of cells at depth driven by condensations of methane for the top cell, hydrogen sulfide-methane mixture for the middle cell, and ammonia-hydrogen sulfide-methane mixture for the lowest cell. This study examines the dynamical implications of the existence of such vertically stacked cells. Specifically, using the Eulerian Mean framework in the beta-plane, we derive the constraints for the eddy momentum flux, diabatic heating (i.e. latent heat), and eddy heat flux required to balance the vertically stacked circulation. Using these constraints, observable effects will be identified to guide future observations by the upcoming missions to Uranus and Neptune that may test the hypothesized vertically stacked circulation.

Kunio M Sayanagi↗
NASA NTRSDate not supplied

Lucy Orbit Determination Performance From Launch Through EGA-1

Lucy is a 12-year long NASA Discovery-class mission which launched on October 16, 2021 and is currently on its way to the Jupiter-Trojan asteroids at the L4 and L5 Lagrange points. On its journey to the Trojan asteroids, Lucy will also fly by two main belt asteroids, and perform 3 Earth fly bys. This paper summarizes primarily the Orbit Determination (OD) aspect of the first year of the mission from launch through the first Earth fly by (EGA-1). Some challenges were encountered for OD as part of the +Y solar array not fully deploying, but these were resolved within the first year of flight. The high quality radio-metric data from the Deep Space Network including 2- and 3-way Doppler, sequential 2-way ranging, complemented by delta differential one-way ranging (∆DOR) has enabled the OD team to characterize the Solar Radiation Pressure force, resolve desaturation maneuvers, generate both maneuver reconstructions and accurate long-term predicted trajectories. This paper discusses the filter setup and strategies implemented, as well as the OD performance from launch, through cruise, and including EGA-1.

Jeroen L. Geeraert↗
NASA NTRSDate not supplied

Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data

Clouds at different altitudes play different roles in Earth’s climate. Comprehensive understanding of overlapping clouds is important for climate and weather prediction. The East Pacific region is where El Ni˜no and La Ni˜na originate and where multi-layer clouds frequently occur. The overlap of clouds at different altitudes in this region increases the classification complexity for cloud-based climatological studies. Unlike prior work in cloud layer classification that assumes single layer or two-layer of clouds, in this work, we consider multi-layer cloud classification with 8 cloud-level classes (clear-sky, high, middle, low, high+middle, high+low, middle+low, high+middle+low). We develop and analyze machine learning models on features extracted from satellite images from the East Pacific regions collected by GOES Advanced Baseline Imager (ABI). These are used to classify CloudSat/CALIPSO observed multi-layer clouds. Due to the imbalanced nature of the data, we investigate the adoption of conventional resampling methods, as well as deep learning methods with data augmentation. In our experiments, we utilize the random forest classifier and Multilayer perceptron classifier with data augmentation methods to reduce the class imbalance during training. With these approaches, we achieve a classification accuracy of 83.6% without exploiting any ancillary information.

machine learning↗
DOE OSTI2022

Disentangling the EMC effect: from free to bound nucleon structure

Deep inelastic scattering experiments using electron beams on fixed targets allow for the study of the structure of nucleons. While the structure of the free proton has been well measured, the free neutron structure and the modification of nucleon structure in the nuclear environment, the EMC effect, remain open questions. Studies suggest that the EMC effect may arise due to strongly-interacting nucleon-nucleon systems, referred to as short-range correlations. The BAND experiment at the Thomas Jefferson National Accelerator Facility seeks to probe the bound proton structure when in a strongly-interacting state, using spectator-tagged deep inelastic scattering. This thesis presents the results of the BAND experiment, demonstrating the proton is modified when strongly-interacting with the spectator neutron in deuterium. This thesis also explores efforts to describe inclusive and tagged deep inelastic scattering data within a uniform theoretical framework to explore nucleon structure modification effects and extract the free neutron structure.

Segarra, Efrain↗
DOE OSTI2023

Collaborative Proposal: Improving Understanding of the Internal Structure and Dynamics of Deep Convection Using ARM Observations and Large Eddy Simulations (Final progress report)

This is the final technical report for the DOE Atmospheric System Research funded project entitled "Collaborative Proposal: Improving Understanding of the Internal Structure and Dynamics of Deep Convection Using ARM Observations and Large Eddy Simulations". This project addressed several science questions related to the structure and behavior of deep convective clouds in the atmosphere. It applied knowledge gained from this work to improve the deep cumulus convection parameterization in the Community Earth System Model (CESM). Specific outcomes related to the project include an improved understanding of: (1) how convective cloud environments regulate the size of thermals reaching the upper troposphere, and hence the shallow-to-deep convective transition; (2) the role of dynamic pressure forcing in thermal and convective cloud evolution; and (3) the role of vertical wind shear on the behavior of moist thermals and the transition from shallow to deep convection. Although the primary motivation of this project was to improve basic understanding of thermal dynamics in atmospheric convection, an important component of this work was using this improved understanding to modify the representation of entrainment and vertical velocity profiles in the Zhang-McFarlane cumulus parameterization used in CESM. This work also had a strong observational component, with analyses of Atmospheric Radiation Measurement (ARM) observations to characterize thermal characteristics and behavior. Observations collected during the ARM-supported CACTI field project were used with high-resolution simulations to explore environmental controls on deep convection initiation. Data from the ARM-supported MC3E field project were also used to evaluate the representation of updraft vertical velocities in the Zhang-McFarlane cumulus parameterization. This project directly supported the training of two post-doctoral researchers and led to 16 peer-reviewed published papers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees

Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Developing Confidence in Machine Learning Results

As the field of deep learning has emerged in recent years, the amount of knowledge and expertise that data scientists are expected to absorb and maintain has correspondingly increased. One of the challenges experienced by data scientists working with deep learning models is developing confidence in the accuracy of their approach and the resulting findings. In this study, we conducted semi-structured interviews with data scientists at a National Laboratory to understand the processes that data scientists use when attempting to develop their models and the ways that they gain confidence that the results they obtained were accurate. These interviews were analysed to provide an overview of the techniques currently used when working with machine learning (ML) models and opportunities for collaboration with human factors researchers to develop new tools are identified.

Baweja, Jessica A.↗
DOE OSTI2023

Demonstration of object location, classification, and characterization by developed deep learning dust ablation trail analysis code package using plasma jets

Based on deep learning, a Dust Ablation Trail Analysis (DATA) code package is developed to detect dust ablation trails in tokamaks, which is intended to analyze a large amount data of tokamak dusts. To validate and benchmark the DATA code package, 2440 plasma jet images are exploited for the training and test of the deep learning DATA code package, since plasma jets resemble the shape and size of dust ablation clouds in tokamaks. After being trained by 1920 plasma jet images, the DATA code package is able to locate 100% plasma jets, classify plasma jets with the accuracy of >99.9%, and output image skeleton information for classified plasma jets. The DATA code package trained by the plasma jet images is also used to analyze the dust ablation trails captured in the Experimental Advanced Superconducting (EAST) tokamak with the satisfactory performance, further verifying its applicability in the fusion dust ablation investigation. Based on its excellent performance presented here, it is demonstrated that our DATA code package is able to automatically identify and analyze dust ablation trails in tokamaks, which can be used for further detailed investigations, such as the three-dimensional reconstruction of dusts and their ablation trails.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Pathways to a Sustainable Aviation Ecosystem: Flight DNA: An Anonymized Aviation Data Tool and Repository

The National Renewable Energy Laboratory (NREL) has deep experience developing secure, national data repositories, which it augments with analysis, technology and market expertise, high-performance computing, and innovative data visualization. By adapting the architecture of existing mobility databases (i.e., Fleet DNA, the Transportation Secure Data Center, the National Fuel Cell Technology Evaluation Center), NREL can build a powerful aviation data clearinghouse - Flight DNA - that helps stakeholders navigate the web of pitfalls and possibilities generated by new aviation technologies.

aviation↗
NASA NTRS1991

Combining GPS and VLBI earth-rotation data for improved universal time

The Deep Space Network (DSN) routinely measures Earth orientation in support of spacecraft tracking and navigation using very long-baseline interferometry (VLBI) with the deep-space tracking antennas. The variability of the most unpredictable Earth-orientation component, Universal Time 1 (UT1), is a major factor in determining the frequency with which the DSN measurements must be made. The installation of advanced Global Positioning System (GPS) receivers at the DSN sites and elsewhere may soon permit routine measurements of UT1 variation with significantly less dependence on the deep-space tracking antennas than is currently required. GPS and VLBI data from the DSN may be combined to generate a precise UT1 series, while simultaneously reducing the time and effort the DSN must spend on platform-parameter calibrations. This combination is not straightforward, however, and a strategy for the optimal combination of these data is presented and evaluated. It appears that, with the aid of GPS, the frequency of required VLBI measurements of Earth orientation could drop from twice weekly to once per month. More stringent real-time Earth orientation requirements possible in the future would demand significant improvements in both VLBI and GPS capabilities, however.

Freedman, A. P.↗
DOE OSTI2021

A data-independent acquisition-based global phosphoproteomics system enables deep profiling

Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (<0.1 ng), accurate site localization and reproducible quantification (~5% median coefficient of variation). As a proof-of-concept, we use lung cancer cell lines and patient-derived tissue to construct a hybrid phosphoproteome spectral library covering 159,524 phosphopeptides (88,107 phosphosites). Based on this library, our single-shot streamlined DIA workflow quantifies 36,350 phosphosites (19,755 class 1) in cell line samples within two hours. Application to drug-resistant cells and patient-derived lung cancer tissues delineates site-specific phosphorylation events associated with resistance and tumor progression, showing that our workflow enables the characterization of phosphorylation signaling with deep coverage, high sensitivity and low between-run missing values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Utah FORGE: Stress Logging Data

This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 - 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in situ stress (determined from the density logging) and the total maximum and minimum horizontal stresses. The horizontal stresses were determined from the DSI (Dipole Sonic Imager) and corrected to match the direct measurements.

15 GEOTHERMAL ENERGY↗
NASA NTRS2001

On Quality Control Procedures Being Adopted for TRMM LBA and KWAJEX Soundings Data Sets

During NASA's Tropical Rainfall Measuring Mission (TRMM) field campaigns Large Scale Biosphere Atmosphere (LBA) held in Amazonia (Brazil) in the period January- February, 1999, and the Kwajalein Experiment (KWAJEX) held in the Republic of Marshall Islands in the period between August-September, 1999, extensive radiosonde observations (raob) were collected using VIZ and Vaisala sondes which have different response characteristics. In all, 320 raob for LBA and 972 fixed raob for KWAJEX have been obtained and are being processed. Most atmospheric sensible heat source (Q1) and apparent moisture sink (Q2) budget studies are based on sounding data, and the accuracy of the raob is important especially in regions of deep moist convection. A data quality control (QC) project has been initiated at GSFC by the principal investigator (JBH), and this paper addresses some of the quantitative findings for the level I and II QC procedures. Based on these quantitative assessment of sensor (or system) biases associated with each type of sonde, the initial data repair work will be started. Evidence of moisture biases between the two different sondes (VIZ and Vaisala) has been shown earlier by Halverson et al. (2000). Vaisala humidity sensors are found to have a low-level dry bias in the boundary layer, whereas above 600 mb the VIZ sensor tends to register a dryer atmosphere. All raob data were subjected to a limit check based on an algorithm already well tested for the raob data obtained during the Tropical Ocean Global Atmosphere (TOGA-COARE).

Roy, B.↗