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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 1,009 records · Page 56

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NASA NTRS1989

The 32-GHz performance of the DSS-14 70-meter antenna: 1989 configuration

The results of preliminary 32 GHz calibrations of the 70 meter antenna at Goldstone are presented. Measurements were done between March and July 1989 using Virgo A and Venus as the primary efficiency calibrators. The flux densites of theses radio sources at 32 GHz are not known with high accuracy, but were extrapolated from calibrated data at lower frequencies. The measured value of efficiency (0.35) agreed closely with the predicted value (0.32), and the results are very repeatable. Flux densities of secondary sources used in the observations were subsequently derived. These measurements were performed using a beamswitching radiometer that employed an uncooled high-electron mobility transistor (HEMT) low-noise amplifier. This system was installed primarily to determine the performance of the antenna in its 1989 configuration, but the experience will also aid in successful future calibration of the Deep Space Network (DSN) at this frequency.

Gatti, M. S.↗

NASA NTRS1991

Combined flatland ST radar and digital-barometer network observations of mesoscale processes

The paper describes a six-station digital-barometer network centered on the Flatland ST radar to support observational studies of gravity waves and other mesoscale features at the Flatland Atmospheric Observatory in central Illinois. The network's current mode of operation is examined, and a preliminary example of an apparent group of waves evident throughout the network as well as throughout the troposphere is presented. Preliminary results demonstrate the capabilities of the current operational system to study wave convection, wave-front, and other coherent mesoscale interactions and processes throughout the troposphere. Unfiltered traces for the pressure and horizontal zonal wind, for days 351 to 353 UT, 1990, are illustrated.

Clark, W. L.↗

NASA NTRS2010

Methods and Results for a Global Precipitation Measurement (GPM) Validation Network Prototype

As one component of a ground validation system to meet requirements for the upcoming Global Precipitation Measurement (GPM) mission, a quasi-operational prototype a system to compare satellite- and ground-based radar measurements has been developed. This prototype, the GPM Validation Network (VN), acquires data from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite and from ground radar (GR) networks in the continental U.S. and participating international sites. PR data serve as a surrogate for similar observations from the Dual-frequency Precipitation Radar (DPR) to be present on GPM. Primary goals of the VN prototype are to understand and characterize the variability and bias of precipitation retrievals between the PR and GR in various precipitation regimes at large scales, and to improve precipitation retrieval algorithms for the GPM instruments. The current VN capabilities concentrate on comparisons of the base reflectivity observations between the PR and GR, and include support for rain rate comparisons. The VN algorithm resamples PR and GR reflectivity and other 2-D and 3-D data fields to irregular common volumes defined by the geometric intersection of the instrument observations, and performs statistical comparisons of PR and GR reflectivity and estimated rain rates. Algorithmic biases and uncertainties introduced by traditional data analysis techniques are minimized by not performing interpolation or extrapolation of data to a fixed grid. The core VN dataset consists of WSR-88D GR data and matching PR orbit subset data covering 21 sites in the southeastern U. S., from August, 2006 to the present. On average, about 3.5 overpass events per month for these WSR-88D sites meet VN criteria for significant precipitation, and have matching PR and GR data available. This large statistical sample has allowed the relative calibration accuracy and stability of the individual ground radars, and the quality of the PR reflectivity attenuation correction in convective and stratiform precipitation to be evaluated. We will present results of PR-GR reflectivity and rain rate bias comparisons for each OR site, and for different rain types, for the full data set and as time series. The capabilities of the statistical analysis and vertical cross section tools for display and analysis of individual site overpass event data will be described, and examples of the tools' outputs will be shown.

Morris, Kenneth R.↗

NASA NTRS2011

Incorporating Ameriflux Data into LVT

This paper describes a new generic data reader that was developed in Fortran to handle the Ameriflux data for the LIS Verification Toolkit (LVT). Researchers at the Hydrological Sciences Branch of NASA Goddard Space Flight Center have created a high resolution land surface modeling and data assimilation system known as the Land Information System (LIS), which provides an infrastructure to integrate state-of-the-art land surface models, data assimilation algorithms, observations of land surface from satellite and remotely sensed platforms to provide estimates of land surface conditions such as soil moisture, evaporation, snowpack and runoff. These model predictions are typically evaluated by comparing them with data from observational networks. The observational data; however, are usually available in disparate data formats and require significant effort to process them into a structure amenable for use with the model data. The motivation to develop a uniform approach for land surface verification as a way to alleviate these processing efforts has led to the development of LVT which is designed to enable the rapid evaluation of land surface modeling and analysis products from LIS. LVT focuses on the use of observational datasets in their native format. As the formats of these datasets vary widely, a major part of LVT is creating programs to read and process the native datasets. The primary goal of this project is to enhance LVT capabilities by incorporating observational datasets from Ameriflux

Georgiev, Teodor↗

DOE OSTI2020

Slip Tendency Analysis of Fracture Networks to Determine Suitability of Candidate Testbeds for the EGS Collab Hydroshear Experiment

Experiment 2 of the EGS Collab project is aimed at testing stimulation by hydro-shearing of existing natural fractures, versus Experiment 1, which is focused on hydraulic fracturing a rock mass to enhance permeability. The main criterion for the testbed selection in Experiment 2 is the presence of an interconnected network of fractures, at least 10 meters in extent, and with orientations such that shear slip can be induced at injection pressures less than the minimum horizontal stress (Shmin). The feasibility analysis for this experiment requires a well-constrained stress state along with well-characterized fracture networks. The fracture systems at two candidate locations in the Sanford Underground Research Facility (SURF), the 4850 Level (number refers to depth below ground surface in feet) and the 4100 Level, have been characterized to different extents. The 4850 Level has a well-characterized Discrete Fracture Network (DFN) from borehole (drilled for an experimental test bed) and drift observations. In contrast, the 4100 level has a fracture network characterized only by observations from the drift wall, which provides little constraint on fracture extents. This paper will present assessments for the interpreted slip potential for the natural fractures at the two locations. Data uncertainties are addressed by performing a probabilistic analysis that takes into account the uncertainty in the stress state, uncertainty in the fracture properties, and preliminary borehole locations. There is strong evidence of shear stimulation of some natural fractures in Experiment 1 on the 4850 level. We use examples of natural fractures strongly linked to shear stimulation in Experiment 1 from multiple monitoring indicators to test the consistency of the stress model and guide the uncertainty interpretation. This analysis is intended to guide the site selection process for Experiment 2 by highlighting the fracture orientations that are likely to be shear-stimulated in a majority of modeled realizations.

40 EE - Geothermal Technologies Office (EE-4G)↗

DOE OSTI2023

Robust Real-Time Modeling of Distribution Systems with Data-Driven Grid-Wise Observability (Final Technical Report)

The overall objective of this project is to leverage existing and emerging sensor measurements to develop data-driven observability enhancement algorithms as well as robust state estimation and parameter identification techniques to enable real-time grid-wise monitoring and modeling of loads and distributed energy resources (DERs). The project resulted in a holistic framework with the following key components: 1) data-driven and machine learning-based grid-edge visibility enhancement, 2) robust branch-current-based state estimation (BCSE), and 3) robust real-time steady-state and dynamic-state modeling of loads and DERs. The research outcomes have provided utility companies better network visibility, higher-fidelity load/DER models, and more accurate assessment of DERs’ impacts, thus, facilitating the integration of renewable energy sources. The synergistic collaborative project among Iowa State University (ISU), Argonne National Laboratory (ANL), Electric Power Research Center (EPRC), SIEMENS Industry, Alliant Energy, Cedar Falls Utilities (CFU), and Maquoketa Valley Electric Cooperative (MVEC) to leverage the team’s extensive expertise and experience in power distribution systems, state estimation, online modeling and identification, and DER integrations. The proposed frameworks have been verified with industry adopted software and attempted integrated with existing tool wherever possible

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Direct observation of key aluminum hydroxide prenucleation oligomers for gibbsite nucleation and crystallization in sodium aluminate solution by liquid ToF-SIMS

The mechanism of gibbsite (aluminum hydroxide) crystallization from highly alkaline solutions such as Bayer liquors remains poorly understood, where aluminum (Al) transforms from largely tetrahedrally coordinated aluminate monomers in sodium aluminate solutions into a network of octahedra in gibbsite crystals. A variety of traditional analytical approaches applied to this system do not readily reveal the presence of higher-order oligomeric intermediates. To overcome this limitation, we employed in-situ liquid Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to examine the Al species present in concentrated sodium aluminate solutions favoring crystallization of gibbsite or sodium aluminate. A complex mixture of Al oligomers was found. By comparing the change in the relative concentration of Al oligomers with +1 and -1 charge, we were able to identify three major Al oligomer candidates, iso-tetramers, iso-pentamers, and cyclic-hexamers, for the nucleation and crystallization of gibbsite. The concentrations of iso-tetramers and iso-pentamers significantly surpass those of cyclic-hexamers. Time-dependent in-situ Raman spectroscopy analysis indicated that the appearance of gibbsite coincided with the peak concentration of these oligomers. The Density-functional theory (DFT) calculation suggests that the formation of iso-oligomers is more favorable than that of cyclic-hexamers. The combined results suggest that iso-tetramers and iso-pentamers play the most substantial role in the nucleation and growth of gibbsite in the sodium aluminate solutions. Our findings also suggest that the oligomers that promote gibbsite crystallization are more stable in dilute sodium aluminate solutions, making these solutions particularly suitable for efficient gibbsite crystallization. In conclusion, our study fills a major knowledge gap in understanding Al speciation that leads to the nucleation and crystallization of gibbsite in concentrated sodium aluminate solutions.

Bayer liquor↗

DOE OSTI2023

Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning

Modern astronomical experiments are designed to achieve multiple scientific goals, from studies of galaxy evolution to cosmic acceleration. These goals require data of many different classes of night-sky objects, each of which has a particular set of observational needs. These observational needs are typically in strong competition with one another. This poses a challenging multi-objective optimization problem that remains unsolved. The effectiveness of Reinforcement Learning (RL) as a valuable paradigm for training autonomous systems has been well-demonstrated, and it may provide the basis for self-driving telescopes capable of optimizing the scheduling for astronomy campaigns. Simulated datasets containing examples of interactions between a telescope and a discrete set of sky locations on the celestial sphere can be used to train an RL model to sequentially gather data from these several locations to maximize a cumulative reward as a measure of the quality of the data gathered. We use simulated data to test and compare multiple implementations of a Deep Q-Network (DQN) for the task of optimizing the schedule of observations from the Stone Edge Observatory (SEO). We combine multiple improvements on the DQN and adjustments to the dataset, showing that DQNs can achieve an average reward of 87%+-6% of the maximum achievable reward in each state on the test set. This is the first comparison of offline RL algorithms for a particular astronomical challenge and the first open-source framework for performing such a comparison and assessment task.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2017

Static Electric Fields and Lightning Over Land and Ocean in Florida Thunderstorms

Natural cloud-to-ground (CG) lightning and the charge structure of the associated clouds behave differently over land and ocean. Existing literature has raised questions over the years on the behavior of thunderstorms and lightning over oceans, and there are still open scientific questions. We expand on the observational datasets by obtaining identical electric field observations over coastal land, near-shore, and deep ocean regions during both clear air and thunderstorm periods. Oceanic observations were obtained using two 3-meter NOAA buoys that were instrumented with Campbell Scientific electric field mills to measure the static electric fields. These data were compared to selected electric field records from the existing on-shore electric field mill suite of 31 sensors at Kennedy Space Center (KSC). CG lightning occurrence times, locations and peak current values for both on-shore and ocean were provided by the U.S. National Lightning Detection Network. The buoy instruments were first evaluated on-shore at the Florida coast, to calibrate field enhancements and to confirm proper behavior of the system in elevated-field environments. The buoys were then moored 20NM and 120NM off the coast of KSC in February (20NM) and August (120NM) 2014. Statistically larger CG peak currents were reported over the deep ocean for first strokes and for subsequent strokes with new contacts points. Storm-related static fields were significantly larger at both oceanic sites, likely due to decreased screening by nearby space charge. Time-evolution of the static field during storm development and propagation indicated weak or missing lower positive charge regions in most storms that initiated over the deep ocean, supporting one mechanism for the observed high peak currents in negative first strokes over the deep ocean. This project also demonstrated the practicality of off-shore electric field measurements for safety-related decision making at KSC.

Lightning↗

NASA NTRS2017

Static Electric Fields and Lightning Over Land and Ocean in Florida Thunderstorms

Electric Fields↗

NASA NTRS2019

Cognitive Communications for NASA Space Systems

The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗

DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

GW190412: Observation of a binary-black-hole coalescence with asymmetric masses

We report the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO's and Virgo's third observing run. The signal was recorded on April 12, 2019 at 05:30:44 UTC with a network signal-to-noise ratio of 19. The binary is different from observations during the first two observing runs most notably due to its asymmetric masses: A ~30 M ⊙ black hole merged with a ~8 M ⊙ black hole companion. The more massive black hole rotated with a dimensionless spin magnitude between 0.22 and 0.60 (90% probability). Asymmetric systems are predicted to emit gravitational waves with stronger contributions from higher multipoles, and indeed we find strong evidence for gravitational radiation beyond the leading quadrupolar order in the observed signal. A suite of tests performed on GW190412 indicates consistency with Einstein's general theory of relativity. While the mass ratio of this system differs from all previous detections, we show that it is consistent with the population model of stellar binary black holes inferred from the first two observing runs.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1983

The NASA SETI Program - Objectives of the R&D activity

The current activity in NASA's SETI Program is a research and development program jointly carried out by the NASA Ames Research Center and the Jet Propulsion Laboratory. The purpose of this R&D phase is to develop all prerequisites for a well defined microwave observing program. The specific objectives include the development of a prototype search system which will ultimately be capable of processing data rates up to 10 gigabytes/second. Specialized signal detection algorithms and automated search procedures will be developed and tested with the prototype hardware. A series of field tests will be carried out with the NASA Deep Space Network facilities at Goldstone, CA and with the 305-m radio telescope at the Arecibo Ionospheric Observatory in Puerto Rico.

Klein, M. J.↗

NASA NTRS1989

Intent inferencing with a model-based operator's associate

A portion of the Operator Function Model Expert System (OFMspert) research project is described. OFMspert is an architecture for an intelligent operator's associate or assistant that can aid the human operator of a complex, dynamic system. Intelligent aiding requires both understanding and control. The understanding (i.e., intent inferencing) ability of the operator's associate is discussed. Understanding or intent inferencing requires a model of the human operator; the usefulness of an intelligent aid depends directly on the fidelity and completeness of its underlying model. The model chosen for this research is the operator function model (OFM). The OFM represents operator functions, subfunctions, tasks, and actions as a heterarchic-hierarchic network of finite state automata, where the arcs in the network are system triggering events. The OFM provides the structure for intent inferencing in that operator functions and subfunctions correspond to likely operator goals and plans. A blackboard system similar to that of Human Associative Processor (HASP) is proposed as the implementation of intent inferencing function. This system postulates operator intentions based on current system state and attempts to interpret observed operator actions in light of these hypothesized intentions.

Jones, Patricia M.↗

NASA NTRS1997

The dynamic quiet solar corona: 4 days of joint observing with MDI and EIT

The analysis of a sequence of joint extreme ultraviolet imaging telescope (EIT) Fe XII and Michelson Doppler imager (MDI) magnetogram observations of the quiet sun near disk center is presented. It was found that: all the emerging flux above the threshold of approximately 10(sup 17) Mx is associated with enhanced coronal emissions; loop systems between the polarities in ephemeral regions remain visible up to separations of 10000 up to 30000 km; brightenings between approaching opposite polarity network concentrations form when the concentrations are between 5000 and 25000 km apart, and that faint connections up to 40000 km in length form as sets of concentrations of the same polarity coagulate. The coronal emission over patches of the quiet sun depends on the total flux in connected concentrations, on their distance and on the positions and strengths of neighboring concentrations.

Schrijver, C. J.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-17940-DND

The NASA/GEWEX SRB (Global Energy and Water Exchanges, Surface Radiation Budget) project produces and archives shortwave and longwave radiation budget flux estimates at the top of the atmosphere and at the Earth's surface. The latest version in the archive, Release 3.0, is available as 3-hourly, 3-hourly-monthly, daily and monthly means continuously over the period from July 1983 to December 2007 on a quasi-equal-area grid system of 44016 grid boxes. SRB Release 4 with further improvements in data quality and higher spatial resolution is being developed. The SRB shortwave/longwave fluxes at the Earth's surface from the algorithm GSW(V3.0)/GLW(V3.1) have been extensively validated against high-quality ground-based observations, in particular observed data from the Baseline Surface Radiation Network (BSRN). Comparisons with nearly 6000 site-months of both shortwave and longwave data from 52 BSRN sites show generally good agreement. In addition, the GEWEX SRB data have also been found to compare favorably with the World Radiation Data Centre (WRDC) data and the Global Energy Balance Archive (GEBA) data. In spite of the fact that the BSRN sites are scattered on all seven continents, the validation of the SRB data over the vast oceans had not been done until recently. In this paper, we present comparisons of the GEWEX-SRB data shortwave/longwave data with observations made on arrays moored in tropical oceans. Specifically, we have data from 21 buoys, or moorings, from Predictions and Research Moored Array in the Atlantic (PIRATA), 14 buoys from the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) in the Indian Ocean, 20 buoys from the Tropical Atmosphere Ocean (TAO) array in the Pacific, and 3 buoys from the Woods Hole Oceanographic Institute (WHOI) (2 in the Pacific and 1 in the Atlantic). The data from these buoys span 12 years from 2000 to 2011, though not necessarily continuously. It is found that except for occasional outliers, the majority of the comparable pairs of data points agree well. Further examination of the outliers is necessary to determine whether they can be attributed to wind-driven tilt and/or aerosol accumulation on the instruments. In order to see how the ocean-based validation compares with land-based validation, we made SRB-BSRN monthly mean shortwave/longwave radiation comparisons in the tropical region only, where all the buoys are moored. The results show that in the case of shortwave radiation, the bias error from the ocean-based validation is somewhat larger than its land-based counterpart, but their RMS errors are not significantly different. In the case of longwave radiation, the ocean-based and land-based validations show nearly identical comparison statistics.

Taiping Zhang↗

NASA NTRSDate not supplied

Observing System Simulation Experiments to Determine the Impact of Spaceborne Differential Absorption Radar Measurements of Marine Surface Pressure on Numerical Weather Prediction

Surface air pressures over marine regions can potentially be measured by estimating the total atmospheric column oxygen content with differential absorption radar (DAR). A demonstration instrument, the Microwave Barometric Radar and Sounder (MBARS) has been funded by NASA for airborne missions in 2024 to show proof of concept. In this presentation, the potential use of such marine surface pressure observations from a spaceborne DAR platform to improve numerical weather prediction is examined using the NASA/GMAO global Observing System Simulation Experiment. Several aspects of the instrument are explored, including contamination by heavy precipitation and the expected error characteristics of the observations. Different orbit and scan configurations are compared, including various constellations of nadir smallsats and A-Train-type scanning configurations. The impacts of marine surface pressure observations are put into context with the current global observing network with a Forecast Sensitivity Observation Impact tool.

Nikki Privé↗