Data-based determination of the isospin-limit light-quark-connected contribution to the anomalous magnetic moment of the muon
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79 ASTRONOMY AND ASTROPHYSICS↗
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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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Responsibilities and practical limitations in the operation of an astronomical data center
The operation of an astronomical data center requires that many decisions be made concerning the handling of the astronomical catalogs and data distributed. Should a data center be, as Wilkins (1977) described it, passive, in that catalogs and data are collected and distributed blackbox-wise upon request, or should a data center be active and have experts in various fields to scrutinize, correct, reformat, and document data where necessary. These questions will be addressed and illustrated by describing the current operations and future goals of the Astronomical Data Center at NASA/GSFC.
Warren, W. H., Jr.↗
Estimates of the stratospheric distribution of odd nitrogen from the LIMS data
Reasonable lower-limit estimates of the latitude-altitude distribution of stratospheric NO(x) for December 1978 and March 1979 are presented. The lower-limit estimates are based on nighttime measurements of NO2 and HNO3 taken by the LIMS instrument aboard the NIMBUS 7 satellite. It is shown that the estimates do not depend upon model calculations or a priori knowledge of the nature of the stratospheric photochemical system. The results indicate that the measured sum of nighttime NO2 nd HNO3 is as high as 22.5 + or - ppbv and that atmospheric NO(x) levels may be as high as 26 + or - 4.5 ppbv at 37 km, which is larger than most calculated NO(x) levels.
Callis, L. B.↗
Constraining the properties of the proposed supermassive black hole system in 3C66B: limits from pulsar timing
Data from long term timing observations of the radio pulsar PSR B1855+09 have been searched for the signature of Gravitational waves (G-waves) emitted by the proposed supermassive binary black hole system in 3C66B.
pulsars↗
Quantifying Uncertainty in Particle Size Distribution Parameters Inferred from SAGE III/ISS Extinction Spectra
Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on their microphysical properties such as particle size distribution (PSD). The PSD is a mathematical description of the relative abundance of different sized particles within a sampling volume. If the PSD is accurately known then other key modeling parameters (e.g., surface area density) can be derived. Occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts failed to address two key issues with this methodology: 1. The measurement uncertainty was not accounted for; 2. They assumed the PSDs to be single-mode only, while “real-world” PSDs are predominantly bi-modal. Accounting for both issues in the retrieval will yield an expanded solution space to the inferred PSD parameters; the question is “by how much?” To address this knowledge gap, we propose to carry out a series of simulations and, for every valid SAGE III/ISS data point, determine the range of PSD parameters that yield extinction spectra that are indistinguishable from the SAGE III/ISS data, within the limits of the reported uncertainty. Further, we will expand the solution space, for the first time, to include bimodal distributions. The results of this work will advance Earth system modeling/prediction capability through identifying the uncertainty of PSD parameter estimates using SAGE III/ISS data. The key benefits of this study over previous studies are twofold: 1. we will provide PSD estimates that include bimodal distributions in the solution space, 2. we will provide an uncertainty estimate for these parameters. The results of this study may be used directly in current and future climate and chemistry models.
SAGE III/ISS↗
Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning
Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.
36 MATERIALS SCIENCE↗
Spectrum Orbit Utilization Program Documentation: SOUP5 Version 3.8 User's Manual, Volume 2, Appendices a Through G
The appendixes of the user manual are presented. Input forms which may be used to prepare data for the SOUP5V3.4 of the R2BCSAT-83 data base are given. The IBM job control language which can be used to run the SOUP5 system from a magnetic tape is described. Copies of a run using the delivered tape and IBM OS/MVS Job Control Language card deck are illustrated. Numerical limits on scenario data requests are listed. Error handling, error messages and editing procedures are also listed. Instructions as to how to enter a protection ratio template are given. And relation between PARC prameter, channelization, channel families, and interference categories are also listed.
Davidson, J.↗
Using tabulated NLTE data for Hohlraum simulations
Non-local thermodyamic equilibrium (NLTE) atomic kinetics is necessary in inertial confinement fusion Hohlraum simulations for adequately modeling high-Z walls and dopants but is computationally very expensive. We present here an approach for tabulating NLTE material data in an economical manner. Material properties for an arbitrary radiation field are provided through tabulated data for a limited set of radiation fields plus derivatives with respect to components of those radiation fields. We have implemented this method in a radiation-hydrodynamics code and compare Hohlraum simulations done with inline NLTE calculations with those done with tables constructed from the same atomic data. The results demonstrate that NLTE tables can replace inline calculations in Hohlraum simulations without a significant loss of accuracy.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Development of a High Fidelity Dynamic Module of the Advanced Resistive Exercise Device (ARED) Using Adams
NASA's Digital Astronaut Project (DAP) implements well-vetted computational models to predict and assess spaceflight health and performance risks, and enhance countermeasure development. DAP provides expertise and computation tools to its research customers for model development, integration, or analysis. DAP is currently supporting the NASA Exercise Physiology and Countermeasures (ExPC) project by integrating their biomechanical models of specific exercise movements with dynamic models of the devices on which the exercises were performed. This presentation focuses on the development of a high fidelity dynamic module of the Advanced Resistive Exercise Device (ARED) on board the ISS. The ARED module, illustrated in the figure below, was developed using the Adams (MSC Santa Ana, California) simulation package. The Adams package provides the capabilities to perform multi rigid body, flexible body, and mixed dynamic analyses of complex mechanisms. These capabilities were applied to accurately simulate: Inertial and mass properties of the device such as the vibration isolation system (VIS) effects and other ARED components, Non-linear joint friction effects, The gas law dynamics of the vacuum cylinders and VIS components using custom written differential state equations, The ARED flywheel dynamics, including torque limiting clutch. Design data from the JSC ARED Engineering team was utilized in developing the model. This included solid modeling geometry files, component/system specifications, engineering reports and available data sets. The Adams ARED module is importable into LifeMOD (Life Modeler, Inc., San Clemente, CA) for biomechanical analyses of different resistive exercises such as squat and dead-lift. Using motion capture data from ground test subjects, the ExPC developed biomechanical exercise models in LifeMOD. The Adams ARED device module was then integrated with the exercise subject model into one integrated dynamic model. This presentation will describe the development of the Adams ARED module including its capabilities, limitations, and assumptions. Preliminary results, validation activities, and a practical application of the module to inform the relative effect of the flywheels on exercise will be discussed.
Humphreys, B. T.↗
CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting
With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.
60 APPLIED LIFE SCIENCES↗
Data Standards and the Synthesis of Magnetograms
A key component of future models of coronal evolution will be the high resolution vector magnetograms that drive the models. Much of this data will have limited field of view, and so will need to be supplemented from other sources, particularly when a global context is needed. I will discuss our plans to develop a tool capable of synthesizing magnetograms from multiple sources. This will rely heavily on the CCMC's KAMELEON data formatter and interpolator.
MacNeice, P. J.↗
Operations of the Optical Communications Demonstration for the Orion EM-2 Mission
The GSFC implementation of an Optical Communication System to demonstrate an operational optical communication link for Orion EM-2. It will serve as a base for providing an operational optical communications capability for future Orion missions. GSFC plans to maintain a development path for the optical communication flight terminal to allow commercialization and implementation on future Orion missions. The Orion optical module part of the optical communications flight terminal and its control electronics have a common architecture with the ILLUMA-T optical terminal provided by GSFC for use on the ISS. The plan is to flow data from Orion through the Optical Communication Fight Terminal to the Optical Communication Ground Terminal and reverse. NASA's Orion spacecraft is an exploratory vehicle designed for longer-duration flights beyond the Moon. Following Orion's Exploration Mission-1 (EM-1), during which the spacecraft will travel beyond the Moon, enter a distant retrograde orbit around the Moon and return to Earth unmanned, Exploration Mission-2 (EM-2) will see a crewed spacecraft complete a slightly different flight path. First crewed test flight of the Orion spacecraft, currently targeting a June 30, 2022 launch. The mission involves: One revolution in Low Earth Orbit (LEO) parking orbit to verify basic Orion systems functionality and deploy solar arrays. A single 42-hour Highly Elliptical Orbit (HEO) intermediate checkout orbit allows characterization of the Orion vehicle system performance prior to committing to a cis-lunar flight. Trans Lunar Injection (TLI) burn using Orion Service Module (SM) main engine, which sends Orion on a lunar flyby and free return. Skip reentry at lunar return velocities to splashdown off the coast of San Diego. Total mission duration is approximately 10 days. EM-2 is the first crewed mission of the Orion Spacecraft that crew brings more video up/downloads, file transfers, and real-time chats with family back home and high-rate communications enables live HD streaming for Crew conferences, Public Affairs Office (PAO) events, and significant mission events. Also still collecting vehicle data on numerous Orion subsystems via Development Flight Instrumentation (DFI) allows large data volume returns sooner for DFI and future science payloads, as opposed to waiting for end-of-mission. O2O is a demonstration of operational utility system tested as a Developmental Test Objective (DTO) and not required to meet mission requirements/success/ Flight Test Objectives (FTO). EM-2 architecture is as close to future mission operational architecture as possible.Orion subsystems (video, DFI, etc.) expected to generate ~250 GB of data in the first 24 hours of flight. Total data generated over the mission estimated to be more than 400 GBUsing S-Band alone, Orion limited to ~ 6GB of data downlink per day. Because of this limitation, Orion is planning to limit live video downlinks on EM-1 in order to downlink high priority fileswith 1 hour/day of Optical Communication, Orion could downlink ~6x more data per day (~ 36GB/day).The optical communication system is capable of multiple data rates up to at least 80 Mbps downlink for the transfer of Orion data to Earth while Orion is operating in the lunar vicinity.
Optical Communication↗
Interpretation of Lyman opacity measurements in JET with the ITER-like wall using a particle balance approach
Recent measurements of the Ly β /D α ratio in the JET ITER-like wall (ILW) divertor show comparatively more pronounced Ly β reabsorption relative to previous results in JET with the carbon wall (JET-C). At the outer horizontal target ion current rollover point a Ly β reabsorption rate of 60% is measured, increasing to 80% in more pronounced detachment, implying a Ly α reabsorption rate of 90%–98%. The radially resolved Ly β /D α measurements are used to constrain Lyman opacity corrections to atomic rate coefficients using the population escape factor technique in order to capture the local changes to the excited state population structure in the high Lyman opacity regions at and outboard of the outer strike point. To check the self-consistency of the Lyman opacity measurements, a detailed spectroscopic interpretation of the outer divertor particle balance is presented, in which the impact of opacity corrections to the Ly α inverse photon efficiency coefficients is assessed. A five-fold deficit in the estimated D + source rate obtained with optically thin plasma assumptions is reconciled once the opacity corrections are factored into the Ly α photon rate to ionization rate conversion. The experiment results are reproduced in EDGE2D-EIRENE density scan simulations in which an imposed ad hoc Lyman reabsorption rate is recovered spectroscopically using synthetic measurements, and a similar shortfall in the D + source rate estimates is reconciled using Lyman opacity corrected atomic data. The model limitations prevent a more detailed self-consistent analysis of the Lyman opacity impact on divertor parameters and detachment evolution, and hence motivate renewed efforts to re-establish routine exploitation of the photon transport modelling capabilities in the EIRENE code package. Lyman opacity corrections to atomic data coefficients are necessary for spectroscopic interpretation of the JET-ILW divertor plasma, with significant influence on the divertor plasma also a likely consequence of the presence of strong Ly α reabsorption. Finally, a scan of auxiliary heating powers spanning L-mode and H-mode conditions reveals a strong correlation of the measured Ly β opacity with the outer target temperature, suggesting new possibilities for using Lyman opacity measurements in establishing detachment scalings.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Gearbox bearing crack growth prognostics and uncertainty quantification with physics-informed machine learning
This paper introduces the extreme theory of functional connections (X-TFC), a physics-informed machine learning algorithm, and tailors it to estimate the remaining useful life (RUL) of wind turbine gearbox bearings experiencing fatigue crack growth. Unlike purely data-driven methods, X-TFC embeds a physics model, based on Head's theory in this work, into its training objective. The core of X-TFC is a random-projection single-layer neural network trained via an extreme learning machine, which requires only limited damage progression data and solves for output weights with a least-squares optimization algorithm. A composite loss function balances the network's fit to observed degradation data against the residuals of the governing crack growth differential equation, ensuring the learned damage trajectory remains physically plausible. When applied to a vibration-based health-index (HI) dataset measured during the growth of a crack on the inner ring of a high-speed bearing in a wind turbine gearbox (Bechhoefer and Dubé, 2020), X-TFC achieves near-zero prediction bias. Even when trained on only the first 10 %–20 % of the damage progression data, with sufficient physics weighting its predictions remain monotonic and smooth, delivering high prognosability and trendability. To quantify the epistemic uncertainty, we employ a Monte Carlo ensemble of independently initialized X-TFC models trained on noise-perturbed data, which yields confidence intervals around each RUL estimate and captures both model-parameter and epistemic uncertainty. In addition to a vibration-based HI, we demonstrate that the proposed framework can be directly applied to a supervisory control and data acquisition (SCADA) data-based HI (Eftekhari Milani et al., 2026) measured during similar wind turbine gearbox bearing crack faults, preserving its accuracy and interpretability. This extension shows the versatility of our approach, which is applicable to bearings of multiple gearbox manufacturers, models, and ratings using only SCADA data. By integrating domain knowledge with machine learning, X-TFC offers a rapid, reliable tool for crack prognostics. Its adaptability to other bearing failure modes, such as pitch bearing ring cracks, positions X-TFC as a powerful enabler of data-driven, physics-informed asset management in the wind energy sector and beyond.
17 WIND ENERGY↗
Estimating the Crustal Power Spectrum From Vector Magsat Data: Crustal Power Spectrum
The Earth's magnetic field can be subdivided into core and crustal components and we seek to characterize the crustal part through its spatial power spectrum (R(sub l)). We process vector Magsat data to isolate the crustal field and then invert power spectral densities of flight-local components along-track for R(sub l) following O'Brien et al. [1999]. Our model (LPPC) is accurate up to approximately degree 45 (lambda=900 km) - this is the resolution limit of our data and suggests that global crustal anomaly maps constructed from vector Magsat data should not contain features with wavelengths less than 900 km. We find continental power spectra to be greater than oceanic ones and attribute this to the relative thicknesses of continental and oceanic crust.
Lowe, David A. J.↗
High resolution imaging
Diffraction-limited telescopic observations were obtained of solar system objects and a program of research into Uranus, Neptune, Pluto and the asteroids based upon the data obtained was persued. Two camera systems appropriate for this work were developed. Most importantly, the PAPA photon address camera was developed and proven. Algorithms were developed for both phase and amplitude recovery and were validated on theoretical and laboratory data and to a limited extent on telescopic data. A laboratory simulator was constructed that was used for development but is also available for controlled investigation of image reconstruction. During 1985 two successful expeditions were made to Hawaii and Cerro Tololo and a large body of data on Pluto, Uranus, Neptune and two asteroids are on tape.
Goody, R.↗
Towards Automating Spacecraft Attitude Sensor Calibration
With a view towards reducing cost and complexity for spacecraft early mission support at the NASA Goddard Space Flight Center (GSFC), efforts are being made to automate the attitude sensor calibration process. This paper addresses one of the major components needed by such a system. The beneficiaries of an improved calibration process are missions that demand moderate to high precision attitude knowledge or that need to perform accurate attitude slews. Improved slew accuracy reduces the time needed for re-acquisition of fine-pointing after each attitude maneuver, Rapid target acquisition can be very important for astronomical targeting or for off-nadir surface feature targeting by Earth-oriented spacecraft. The normal sequence of on-orbit calibration starts with alignment calibration of the star trackers and possibly the Sun sensor. Their relative alignment needs to be determined using a sufficiently large data set so their fields of view are adequately sampled. Next, the inertial reference unit (IRU) is calibrated for corrections to its alignment and scale factors. The IRU biases are estimated continuously by the onboard attitude control system, but the IRU alignment and scale factors are usually determined on the ground using a batch-processing method on a data set that includes several slews sufficient to give full observability of all the IRU calibration parameters. Finally, magnetometer biases, alignment, and its coupling to the magnetic torquers are determined in order io improve momentum management and occasionally for use in the attitude determination system. The detailed approach used for automating calibrations will depend on whether the automated system resides on the ground or on the spacecraft with an ultimate goal of autonomous calibration. Current efforts focus on a ground-based system driving subsystems that could run either on the ground or onboard. The distinction is that onboard calibration should process the data sequentially rather than in a single large batch since onboard computer data storage is limited. Very good batch- processing calibration utilities have been developed and used extensively at NASA/GSFC for mission support but no sequential calibration utilities are available. To meet this need, this paper presents the mathematical description of a sequential IRU calibration system. The system has been tested using flight data from the Rossi X-ray Timing Explorer (RXTE) during a series of attitude slews. The paper also discusses the current state of the overall automated system and describes plans for adding sequential alignment calibration and other additions that will reduce the amount of analyst time and input.
Sedlak, Joseph↗
Integrating Radar, Multispectral, and Landing Site Data for Analysis of the Lunar Surface
Radar maps of the Moon have been produced since the late 1960s, and have been used by a number of authors to study the surface roughness, subsurface rock abundance, and dielectric properties of the lunar surface. These studies focused on a range of topics, including the depth and rock population of the regolith, crater ejecta blankets, pyroclastic mantling layers, and cryptomare deposits. Limited radar sounding data from the Apollo missions identified layering in some regions of the maria. As radar datasets have improved in resolution and calibration, it has become more possible to make quantitative comparisons between the backscatter properties of the Moon, other remote-sensing observations, and the ground truth provided by Surveyor photos and Apollo traverses. This presentation will focus on the results of recent studies of the lunar regolith that make use of these diverse sources of information, and discuss research directions that will be possible with radar data to be collected in the near future.
Campbell, B. A.↗