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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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NASA NTRSDate not supplied

Automated Detection and Analysis of Resident Space Objects with the 1.3-Meter Eugene Stansbery-Meter Class Autonomous Telescope

Optical telescopes dedicated to the detection of orbital debris employ large-area detectors that generate a large number of images each night. Such surveys require automated data analysis pipelines that process the images and detect moving objects. We present an overview of the data analysis pipeline employed by the 1.3-meter Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) on Ascension Island, operated by NASA’s Orbital Debris Program Office. The pipeline enfolds the astrometric and photometric calibration of the images, star-trail removal, object detection, correlation over multiple sequential image frames, and orbital parameter estimation. The performance of the pipeline was investigated by means of Monte-Carlo simulations in which simulated object tracks were inserted into ES-MCAT images and then processed by the pipeline. This technique allows one to confidently estimate the completeness for the detection of resident space objects as a function of apparent magnitude and angular velocity. This paper discusses these techniques and provides examples using actual data.

Paul Hickson↗
NASA NTRS2023

Automated Detection and Analysis of Resident Space Objects with the 1.3-Meter Eugene Stansbery-Meter Class Autonomous Telescope

Optical telescopes dedicated to the detection of orbital debris employ large-area detectors that generate a large number of images each night. Such surveys require automated data analysis pipelines that process the images and detect moving objects. We present an overview of the data analysis pipeline employed by the 1.3-meter Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) on Ascension Island, operated by NASA’s Orbital Debris Program Office. The pipeline enfolds the astrometric and photometric calibration of the images, star-trail removal, object detection, correlation over multiple sequential image frames, and orbital parameter estimation. The performance of the pipeline was investigated by means of Monte-Carlo simulations in which simulated object tracks were inserted into ES-MCAT images and then processed by the pipeline. This technique allows one to confidently estimate the completeness for the detection of resident space objects as a function of apparent magnitude and angular velocity. This paper discusses these techniques and provides examples using actual data.

Paul Hickson↗
DOE OSTI2024

Experimental Safe Extremum Seeking for Accelerators

Here, we demonstrate the recent designs of safe extremum seeking (Safe ES) on the 1-km-long charged particle accelerator at the Los Alamos Neutron Science Center (LANSCE). Safe ES is a modification of extremum seeking (ES) which, in addition to minimizing an analytically unknown cost, also employs a safety filter based on an analytically unknown control barrier function (CBF) safety metric. Tuning is necessitated by accelerators being large complex systems, with many drifting parameters due to thermal effects and degradation. At the same time, safe operation (the maintenance of state constraints) is crucial, as damage brings astronomical costs, both financially and in operation downtime. Our measured (but analytically unknown) safety metric is the beam current. We perform multivariable Safe ES on three accelerator applications, in which we adapt 4, 6, and 3 magnet strength parameters, respectively. Two of the three applications are for validated simulation models of beamlines at LANSCE: the first for the proton radiography (pRad) beamline of 800-MeV protons for spot size tuning; the second on a high-performance code, HPSim, for tuning the low-energy beam transport (LEBT) region that contains a beam of 750-keV protons. The third is an experimental tuning of the steering magnets in the LEBT at LANSCE.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Semi-automated Design of Artificial Intelligence Earth Systems Models

Prediction and observation of water cycles at various scales involve not only patterns isolated in space and time, but also modeling of complex spatio-temporal relationships across multiple domains. For instance, evapotranspiration (ET) and leaf area indexes (LAI) are two parameters that are needed to accurately model and understand land-atmosphere processes. Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFTs), which fail to capture fine-scale variations because of changes in vegetation type across the globe. Similarly LAI estimates have typically been derived from vegetation indices at global scales or estimated locally using physical models, both of which suffer from a range of uncertainties that impact model sensitivity. The new era of AI model development for Earth systems (ES) calls for data-driven methods that provide domain scientists with uncertainty-aware estimations of biophysical parameters such as ET and LAI in a generalizable, interpretable, and discoverable manner.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Lightning Charge Retrievals: Dimensional Reduction, LDAR Constraints, and a First Comparison with LIS Satellite Data

A "dimensional reduction" ("DR") method is introduced for analyzing lightning field changes ((Delta)Es) whereby the number of unknowns in a discrete two-charge model is reduced from the standard eight (x, y, z, Q, x', y', z', Q') to just four (x, y, z, Q). The four unknowns (x, y, z, Q) are found by performing a numerical minimization of a chi-square function. At each step of the minimization, an overdetermined fixed matrix (OFM) method is used to immediately retrieve the best "residual source" (x', y', z', Q'), given the values of (x, y, z, Q). In this way, all eight parameters Ix. y, z, Q, x', y', z', Q') are found, yet a numerical search of only four parameters (x, y, z, Q) is required. The DR method has been used to analyze lightning-caused (Delta)Es derived from multiple ground-based electric field measurements at the NASA Kennedy Space Center (KSC) and U.S. Air Force Eastern Range (ER). The accuracy of the DR method has been assessed by comparing retrievals with data provided by the lightning detection and ranging (LDAR) system at the KSC-ER. and from least squares error estimation theory, and the method is shown to be a useful "stand alone" charge retrieval tool. Since more than one charge distribution describes a finite set of (Delta)Es (i.e., solutions are nonunique), and since there can be appreciable differences in the physical characteristics of these solutions, not all DR solutions are physically acceptable. Hence. an alternative and more accurate method of analysis is introduced that uses LDAR data to constrain the geometry of the charge solutions. thereby removing physically unacceptable retrievals. The charge solutions derived from this method are shown to compare well with independent satellite- and ground-based observations of lightning m several Florida storms.

Koshak, W. J.↗
DOE OSTI2025

Kinetics for the reaction between the solvated electron and dissolved oxygen in n-dodecane from 2.5 to 40 °C

Temperature-controlled, time-resolved picosecond electron pulse radiolysis was utilized to measure the rate of reaction between the solvated electron (eS–) and dissolved oxygen in n-dodecane solutions from 2.5 to 40 °C for the first time. At 20.0 °C, the reaction rate was determined to be k(eS– + O2) = (4.54 ± 0.21) × 1010 M-1 s-1, with an activation energy of Ea = 14.4 ± 1.3 kJ mol-1. These newly determined kinetic parameters are important for predicting and managing the effects of aerated environments on the degradation of organic solvents used in nuclear fuel reprocessing technologies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

An energy storage dispatch optimization for demand-side management in industrial facilities

An energy storage (ES) dispatch optimization was implemented to test lithium-ion battery ES, supercapacitor ES, and compressed air ES on two different industrial facilities – one intermittent process facility and one continuous process facility. The model first shows the capability of optimizing the size of a single technology on a single industrial facility to maximize the return on investment. Then, for the same profile, the model identifies significant differences in the optimal size for different technologies based on their performance parameters. Third, the model identifies differences in the optimal size for each technology based on the facilities profile. Here the results show compressed air ES yields the highest return on investment for both facilities and provides insight for future development of ES systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Extremum Seeking-Based Control System for Particle Accelerator Beam Loss Minimization

Particle accelerators throughout the world vary widely in terms of age and availability of advanced noninvasive diagnostics that provide varying levels of detail about the accelerated beams. Additionally, beam loss measurements and current monitors are ubiquitous in the accelerator community, they are noninvasive, and they are some of the most important metrics in terms of preventing damage or irradiation of beam pipes and equipment for high-energy machines. However, beam loss and current measurements are difficult to use for feedback tuning because of a lack of a known analytic relationship between scalar loss measurements throughout an accelerator and the hundreds of thousands of parameters that influence the beam and time variation of the beam source itself. In this work, we present a model-independent extremum seeking (ES) controller, which has been implemented for automated tuning and optimization of the Los Alamos Neutron Science Center (LANSCE) linear ion accelerator based only on scalar quantities, such as beam loss or flux measurements. We demonstrate the approach on various accelerator subsystems, including groups of radio frequency (RF) accelerating cavities, quadrupole magnets, bending magnets, and steering magnets. This tool is now available as a use graphical user interface (GUI) in the LANSCE control room, allowing beam physicists to choose arbitrary groups of parameters and beam loss or current monitors for adaptive tuning.

43 PARTICLE ACCELERATORS↗
NASA NTRS2004

Chondrule Crystallization Experiments

Given the great diversity of chondrules, laboratory experiments are invaluable in yielding information on chondrule formation process(es) and for deciphering their initial conditions of formation together with their thermal history. In addition, they provide some critical parameters for astrophysical models of the solar system and of nebular disk evolution in particular (partial pressures, temperature, time, opacity, etc). Most of the experiments simulating chondrules have assumed formation from an aggregate of solid grains, with total pressure of no importance and with virtually no gain or loss of elements from or to the ambient environment. They used pressed pellets attached to wires and suffered from some losses of alkalis and Fe.

Hweins, R. H.↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗
NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗
DOE OSTI2021

Quantifying the Uncertainty of the Future Hydrological Impacts of Climate Change: Comparative Analysis of an Advanced Hierarchical Sensitivity in Humid and Semiarid Basins

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. Further, the results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Fine structure in plasma waves and radiation near the plasma frequency in Earth's foreshock

Novel observations are presented of intrunsic fine structure in the frequency spectrum of electomagnetic (EM) radiation and plasma waves near the electron plasma frequency f(sub p) during a period of unusually high interplanetary magnetic field strength. Measured using the wideband receiver on the International Sun-Earth Explorer (ISEE) 1 spacecraft, fine-structured emissions are observed both in the solar wind and the foreshock, The fine structure is shown to correspond to emissions spaced above f(sub p) near half harmonies of the electon cyclotron frequency f(sub ce), i.e., near f(sub p) + nf(sub ce)/2. These appear to be the first space physics observations of emissions spaced by f(sub ce)/2. Indirect but strong arguments are used to discriminate between EM and electrostatic (ES) signals, to identify whether ISEE 1 is in the solar wind or the foreshock, and to determine the relative frequencies of the emissions and the local f(sub p). The data are consistent with generation of the ES and EM emissions in the foreshock, with subsequent propagation of the EM emissions into the solar wind. It remains possible that some emissions currently identified as ES have significant EM character. The ES and EM emisions often merge into one another with minimal changes in frequency, arguing that their source regions and generation mechanisms are related and imposing significant constraints on theories. The f(sub ce)/2 ES and EM fine structures observed may be intrinsic to the emission mechanisms or to superposition of two series of signals with f(sub ce) spacing that differ in starting frequency by f(sub ce)/2. Present theories for nonlinear wave coupling processes, cyclotron maser emission, and other linear instability processes are all unable to explain multiple EM and/or ES components spaced by approximately f(sub ce)/2 above f(sub p) for f(sub p)/f(sub ce) much greater than 1 and typical for shock beams parameters. Suitable avenues for further theoretical research are identified. Empirically, the observed fine structures appear very similar to those in split bnad and multiple-lane type II solar radio bursts; interpretation of both these type II fine structures in terms of f(sub ce)/2 splitting is suggested, thereby supporting and generalizing a suggestion by Wild (1950). A possible application to continuum radiation is mentioned. The ubiquity of these fine structures in the Earth's f(sub p) radiation and foreshock waves remains unknown. Only the ISEE 1 wideband receiver has sufficient frequency resolution (approximately less than or equal to 100 Hz) to perform a dedicated search. Further study of the ubiquity of these fine structures, of how reliably the splitting corresponds to f(sub ce)/2, and of the other interpretations above is necessary.

Cairns, Iver H.↗
DOE OSTI2020

Annual Storm Water Report for the Y-12 National Security Complex Oak Ridge, Tennessee

This is the seventh annual storm water report prepared in accordance with the modified National Pollutant Discharge Elimination System permit issued to the Y-12 National Security Complex (Y-12) on April 1, 2014. This modified permit removed the authorization to augment flow in East Fork Poplar Creek (EFPC) and thus removed the requirement to sample this effluent in conjunction with other major outfalls on EFPC. The general condition of the site continues to improve. The concentrations of Escherichia Coli (Es. coli) at the major outfalls and instream monitoring locations on EFPC are no longer elevated as they were in 2018. Follow-up samples indicated normal levels. Monitoring for this parameter will continue into 2020. The repair of Outfall 014 is nearing completion and will be sampled for storm water in 2020. This repair was expected to occur in 2019 but was delayed until 2020. There are several construction and demolition activities currently in progress at Y-12. These include the construction of the Uranium Processing Facility (UPF), the Mercury Treatment Facility (MTF) on EFPC and the impending demolition of the Biology Complex. These projects will present challenges for the protection of storm water. Oversight of these activities will be a priority in 2020. Y-12 will continue to implement appropriate Best Management Practices and reduce outside material storage areas where possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Leptodermic corrections to the TOV equations and nuclear astrophysics within the effective surface approximation

The macroscopic model for a neutron star (NS) as a liquid drop at the equilibrium is used to extend the Tolman-Oppenheimer-Volkoff (TOV) equations taking into account the gradient terms responsible for the system surface. The parameters of the Schwarzschild metric in the spherical case are found with these surface corrections to the known leading (zero) order of the leptodermic approximation a/R << 1, where a is the NS effective-surface (ES) thickness, and R is the effective NS radius. The energy density $\mathscr{E}$ is considered in a general form including the functions of the particle number density and of its gradient terms. The macroscopic gravitational component $Φ$(ρ) of the energy density is taken into account in the simplest form as expansion in powers of $ρ$ – $\overline{ρ}$, where $\overline{ρ}$ is the saturation density, up to second order, in terms of its contributions to the separation particle energy and incompressibility. Density distributions ρ across the NS ES in the normal direction to the ES, which are derived in the simple analytical form at the same leading approximation, was used for the derivation of the modified TOV (MTOV) equations by accounting for their NS surface corrections. As a result, the MTOV equations are analytically solved at first order and the results are compared with the standard TOV approach of the zero order.

Magner, A. G. [Institute for Nuclear Research, Kyi↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗