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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Neutrino physics is entering a precision era in which measurements of neutrino oscillations, astrophysical neutrinos from supernovae and other sources, and coherent neutrino scattering will provide insight on the nature of neutrino masses, the presence of CP violation, and perhaps more exotic new physics in the neutrino sector. Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies that uses a combination of lattice QCD, nuclear effective theories, phenomenological models, and neutrino event generators to make reliable theory predictions for experimentally relevant nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Energy Services Interface: Architecture, Requirements, and Agreements

This report continues and extends the development of the Energy Services Interface (ESI) that recently has been led by the U.S. Department of Energy’s Grid Modernization Laboratory Consortium. The ESI is intended to facilitate the coordination of multiple, flexible energy resources that work in tandem to satisfy grid objectives by using performance attributes encoded within an ESI Service Template. The ESI relies on a pair of interfaces, representing the service requestor (the consumer of a service) and a service provider (who manages its resources per the agreed performance attributes) to achieve what is commonly known as a “grid service”. Due to its performance-driven approach, the ESI is hypothesized to be able to satisfy all common grid needs via only six common ESI service types. This report first reviews the status of ESI development, including its fundamental tenets. The report makes three important contributions to ESI development: First, it recognizes the similarity between service level agreements and the contract-like agreements that would be needed between energy service requestors and providers and recommends that ESI service agreements be modeled after the web services agreement specification. Second, whereas prior development efforts had focused on a flat, five-stage lifecycle, this report asserts that the ESI should have three behavioral layers in its architecture—the discovery, agreement, and service layers. Finally, this report offers concrete requirements that should be useful toward the development of the service requestors’ and service providers’ respective communications interfaces.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Wino and Real Minimal Dark Matter Excluded by Fermi Gamma-Ray Observations

We show that minimal, fermionic dark matter (DM) models in the $n$-dimensional representation of the weak force with zero hypercharge that make up 100% of the DM under the standard cosmological history are strongly excluded for $n < 9$. This includes the thermal wino, which we show is ruled out even allowing for DM core sizes up to $\sim$6.7 kpc with the preferred local DM density or $\sim$3.7 kpc in addition to the local DM density being half the preferred value, at less than $0.2$ GeV/cm$^3$. We reach these conclusions through dedicated searches with 14 years of Fermi gamma-ray data in the inner Galaxy between 30 GeV and 2 TeV for the continuum gamma-rays produced in the decays of unstable particles produced in DM annihilation and bound-state formation processes. We consider a variety of Milky Way DM profiles in our analyses, including those motivated by modern hydrodynamic cosmological simulations, and show that all the $n < 9$ minimal DM models are disfavored even under the most conservative assumptions for these density profiles. While wino, quintuplet ($n=5$), and $n = 7$ DM models are strongly disfavored by our analyses under the standard cosmology, we discuss how non-standard cosmological histories or DM sub-fractions could still allow for these particles to be realized in nature, with discovery opportunities at next-generation particle colliders and gamma-ray telescopes.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
NASA NTRS2008

Vibroacoustic Response of the NASA ACTS Spacecraft Antenna to Launch Acoustic Excitation

The Advanced Communications Technology Satellite was an experimental NASA satellite launched from the Space Shuttle Discovery. As part of the ground test program, the satellite s large, parabolic reflector antennas were exposed to a reverberant acoustic loading to simulate the launch acoustics in the Shuttle payload bay. This paper describes the modelling and analysis of the dynamic response of these large, composite spacecraft antenna structure subjected to a diffuse acoustic field excitation. Due to the broad frequency range of the excitation, different models were created to make predictions in the various frequency regimes of interest: a statistical energy analysis (SEA) model to capture the high frequency response and a hybrid finite element-statistical energy (hybrid FE-SEA) model for the low to mid-frequency responses. The strengths and limitations of each of the analytical techniques are discussed. The predictions are then compared to the measured acoustic test data and to a boundary element (BEM) model to evaluate the performance of the hybrid techniques.

Larko, Jeffrey M.↗
NASA NTRS2012

New Measurements of the Cosmic Infrared Background Fluctuations in Deep SpitzerllRAC Survey Data and their Cosmological Implications

We extend the previous measurements of CIB fluctuations to angular scales of less than or equal to 1 degree new data obtained in the course of the 2,000+ hour Spitzer Extended Deep Survey. Two fields with completed observations of approximately equal to 12 hr/pixel are analyzed for source-subtracted CIB fluctuations at 3.6 and 4.5 micrometers. The fields, EGS and UDS, cover a total area of approximately 0.25 deg and lie at high Galactic and Ecliptic latitudes, thus minimizing cirrus and zodiacal light contributions to the fluctuations. The observations have been conducted at 3 distinct epochs separated by about 6 months. As in our previous studies, the fields were assembled using the self-calibration method which is uniquely suitable for probing faint diffuse backgrounds. The assembled fields were cleaned off the bright sources down to the low shot noise levels corresponding to AB mag approximately equal to 25, Fourier-transformed and their power spectra evaluated. The noise was estimated from the time-differenced data and subtracted from the signal isolating the fluctuations remaining above the noise levels. The power spectra of the source-subtracted fields remain identical (within the observational uncertainties) for the three epochs of observations indicating that zodiacal light contributes negligibly to the fluctuations. By comparing to the measurements for the same regions at 8 micrometers we demonstrate that Galactic cirrus cannot account for the levels of the fluctuations either. The signal appears isotropically distributed on the sky as required by its origin in the CIB fluctuations. This measurement thus extends our earlier results to the important range of sub-degree scales. We find that the CIB fluctuations continue to diverge to more than 10 times those of known galaxy populations on angular scales out to less than or equal to 1 degree. The low shot noise levels remaining in the diffuse maps indicate that the large scale fluctuations arise from spatial clustering of faint sources well within the confusion noise. The spatial spectrum of these fluctuations is in reasonable agreement with simple fitting assuming that they originate in early populations spatially distributed according to the standard cosmological model (ACDM) at epochs coinciding with the first stars era. The alternative to this identification would require a new population never observed before, nor expected on theoretical grounds, but if true this would represent an important discovery in its own right.

Kashlinsky, A.↗
NASA NTRS2013

Lessons Learned from the Stardust Sample Return Mission

These are science and mission design and operations lessons learned from the Stardust Mission, which returned grains from comet Wild-2 and fresh interstellar dust to Earth in 2006 [1]. Science Lessons: Major discoveries of the Stardust Wild-2 samples include the presence of numerous chondrules and CAI in a comet, which requires a much more dynamic early solar system than many had envisaged, and verified predictions made by models requiring outward flow of early solar system solids before the early nebular gas had dissipated [1-3]. No evidence has been found for the presence of live Al-26 in the comet, suggesting late accretion [4]. Carbonates and unusual sulfides were found which potentially require activity of liquid water within the comet, but to only a minor degree at best [5-6]. The presence of abundant thermally-metamorphosed silicates in Wild-2 appears to require assembly from an earlier generation of bodies [7]. The abundance of presolar grains in the Wild-2 samples appears to be below what has been found in most chondritic IDPs and primitive chondrites [1]. The bulk mineralogy of Wild-2 grains does not match the mineralogy from any single other known astromaterial [7], and is also strikingly unlike that inferred from Spitzer Telescope spectra of Comet Temple 1 dust [8]. Amino acids and other fragile organics have been detected among the Wild-2 samples [9], which highlights the critical importance of further developing techniques for organic analysis in small samples, and cleaning outbound spacecraft.

Zolensky, M. E.↗
NASA NTRSDate not supplied

Under Pressure: The Artemis I Heatshield Char Loss Investigation and Artemis II’s Successful Entry

Following the successful Artemis I skip reentry on December 11, 2022, unexpected char liberation from the Orion heat- shield prompted formation of an Anomaly Response Team to determine root cause and establish flight rationale and corrective actions for subsequent missions. Through a comprehensive investigation including detailed hardware analysis, modeling & simulation, and ground testing, the team determined that the low permeability Avcoat experienced extreme internal gas pressure buildup during the skip entry that could not adequately outgas, leading to crack formation and char liberation. Key discoveries included significant performance differences between permeable and impermeable heatshield regions and successful replication of the anomaly through ground testing. Based on extensive ground testing and analysis, Artemis II flew a modified trajectory without the skip entry to minimize crack-inducing conditions, and successfully splashed down on April 10, 2026 with significantly reduced char loss. For Artemis III and beyond, a corrective action was implemented to produce a more permeable version of Avcoat that will substantially reduce internal pressure accumulation during entry.

Artemis II↗
DOE OSTI2021

Enabling discovery data science through cross-facility workflows

Experimental and observational instruments for scientific research (such as light sources, genome sequencers, accelerators, telescopes and electron microscopes) increasingly require High Performance Computing (HPC) scale capabilities for data analysis and workflow processing. Next-generation instruments are being deployed with higher resolutions and faster data capture rates, creating a big data crunch that cannot be handled by modest institutional computing resources. Often these big data analysis pipelines also require near real-time computing and have higher resilience requirements than the simulation and modeling workloads more traditionally seen at HPC centers. While some facilities have enabled workflows to run at a single HPC facility, there is a growing need to integrate capabilities across HPC facilities to enable cross-facility workflows, either to provide resilience to an experiment, increase analysis throughput capabilities, or to better match a workflow to a particular architecture. In this paper we describe the barriers to executing complex data analysis workflows across HPC facilities and propose an architectural design pattern for enabling scientific discovery using cross-facility workflows that includes orchestration services, application programming interfaces (APIs), data access and co-scheduling.

Antypas, Katerina B.↗
NASA NTRS2012

The Pursuit of K: Reflections on the Current State-of-the-Art in Stress Intensity Factor Solutions for Practical Aerospace Applications

The elastic stress intensity factor (SIF, commonly denoted as K) is the foundation of practical fracture mechanics (FM) analysis for aircraft structures. This single parameter describes the first-order effects of stress magnitude and distribution as well as the geometry of both structure/component and crack. Hence, the calculation of K is often the most significant step in fatigue analysis based on FM. This presentation will provide several reflections on the current state-of-the-art in SIF solution methods used for practical aerospace applications, including a brief historical perspective, descriptions of some recent and ongoing advances, and comments on some remaining challenges. Newman and Raju made significant early contributions to practical structural analysis by developing closed-form SIF equations for surface and corner cracks in simplified geometries, often based on empirical fits of finite element (FE) solutions. Those solutions (and others like them) were sometimes revised as new analyses were conducted or limitations discovered. The foundational solutions have exhibited striking longevity, despite the relatively "coarse" FE models employed many decades ago. However, in recent years, the accumulation of different generations of solutions for the same nominal geometry has led to some confusion (which solution is correct?), and steady increases in computational capabilities have facilitated the discovery of inaccuracies in some (not all!) of the legacy solutions. Some examples of problems and solutions are presented and discussed, including the challenge of maintaining consistency with legacy design applications. As computational power has increased, the prospect of calculating large numbers of SIF solutions for specific complex geometries with advanced numerical methods has grown more attractive. Fawaz and Andersson, for example, have been generating literally millions of new SIF solutions for different combinations of multiple cracks under simplified loading schemes using p-version FE methods. These data are invaluable, but questions remain about their practical use, because the tabular databases of key results needed to support practical life analysis can occupy gigabytes of storage for only a few classes of geometries. The prospect of using such advanced numerical methods to calculate in real time only those K solutions actually needed to support a specific crack growth analysis is also tempting, but the stark reality is that the computational cost is still so high that the approach is not practical except for specific, critical application problems. Some thoughts are offered about alternative paradigms. Compounding approaches are some of the earliest building blocks of SIF development for more complex geometries. These approaches are especially attractive because of their very low computational cost and their conceptual robustness; they are, in some ways, an intriguing contrast and complement to the brute-force numerical methods. In recent years, researchers at NRC-Canada have published remarkable results showing how compounding approaches can be used to generate accurate solutions for very difficult problems. Examples are provided of some successes--and some limitations--using this approach. These closed-form, tabulated numerical, and compounding approaches have typically been used for simple remote loading with simple load paths to the crack. However, many significant cracks occur in complex stress gradient fields. This is a job for weight function (WF) methods, where the arbitrary stress distribution on the crack plane in the corresponding uncracked body (typically determined using FE methods) is used to determine K. Several significant recent advances in WF methods and solutions are highlighted here. Fueled by advanced 3D numerical methods, many new solutions have been generated for classic geometries such as surface and corner cracks with wide ranges of geometrical validity. A new WF formulation has also be developed for part-through cracks considering the arbitrary stress gradients in all directions in the crack plane (so-called bivariant solutions). Basic WF methods have recently been combined with analytical expressions for crack plane stresses to develop a large family of accurate SIF solutions for corner, surface, and through cracks at internal or external notches with very wide ranges of shapes, sizes, acuities, and offsets. Finally, WF solutions are much faster than FE or boundary element solutions, but can still be much slower than simple closed-form solutions, especially for bivariant solutions that can require 2D numerical integration. Novel pre-integration and dynamic tabular methods have been developed that substantially increase the speed of these advanced WF solutions. The practical utility of advanced SIF methods, including both WF and direct numerical methods, is greatly enhanced if the FM life analysis can be directly and efficiently linked with digital models of the actual structure or component (e.g., FE models for stress analysis). Two recent advances of this type will be described. One approach directly interfaces the FM life analysis with the FE model of the uncracked component (including stress results). Through a powerful graphical user interface, simplified FM life models can be constructed (and visualized) directly on the component model, with the computer collecting the geometry and stress gradient information needed for the life calculation. An even more powerful paradigm uses expert logic to automatically build an optimum simple fracture model at any and every desired location in the component model, perform the life calculation, and even generate fatigue crack growth life contour maps, all with minimal user intervention. This paradigm has also been extended to the automatic calculation of fracture risk, considering uncertainty or variability in key input parameters such as initial crack size or location. Another new integrated approach links the engineering life analysis, the component model, and a 3D numerical fracture analysis built with the same component model to generate a table of SIF values at a specific location that can then be employed efficiently to perform the life calculation. Some attention must be given to verification and validation (V&V) issues and challenges: how good are these SIF solutions, how good is good enough, and does anyone believe the life answer? It is important to think critically about the different sources of error or uncertainty and to perform V&V in a hierarchal, building-block manner. Some accuracy issues for SIF solutions, for example, may actually involve independent material behavior issues, such as constraint loss effects for crack fronts near component surfaces, and can be a source of confusion. Recommendations are proposed for improved V&V approaches. This presentation will briefly but critically survey the range of issues and advances mentioned above, with a particular view towards assembling an integrated approach that combines different methods to create practical tools for real-world design and analysis problems. Examples will be selectively drawn from the recent literature, from recent enhancements in the NASGRO and DARWIN computer codes, and from previously unpublished research

CraigMcClung, R.↗
DOE OSTI2020

Double Chooz {theta}13 measurement via total neutron capture detection

Neutrinos were assumed to be massless particles until the discovery of the neutrino oscillation process. This phenomenon indicates that the neutrinos have non-zero masses and the mass eigenstates (nu(1), nu(2), nu(3)) are mixtures of their flavour eigenstates (nu(e), nu(mu), nu(tau)). The oscillations between different flavour eigenstates are described by three mixing angles (theta(12), theta(23), theta(13)), two differences of the squared neutrino masses of the nu(2)/nu(1) and nu(3)/nu(1) pairs and a charge conjugation parity symmetry violating phase delta(CP). The Double Chooz experiment, located near the Chooz Electricite de France reactors, measures the oscillation parameter theta(13) using reactor neutrinos. Here, the Double Chooz collaboration reports the measurement of the mixing angle theta(13) with the new total neutron capture detection technique from the full data set, yielding sin(2)(2 theta(13)) = 0.105 +/- 0.014. This measurement exploits the multidetector configuration, the isoflux baseline and data recorded when the reactors were switched off. In addition to the neutrino mixing angle measurement, Double Chooz provides a precise measurement of the reactor neutrino flux, given by the mean cross-section per fission <sigma(f)& rang; = (5.71 +/- 0.06) x 10(-43) cm(2) per fission, and reports an empirical model of the distortion in the reactor neutrino spectrum. The Double Chooz collaboration reports the neutrino oscillation parameter theta(13) from a measurement of the disappearance of reactor anti-electron neutrinos with the total neutron capture technique.

Djurcic, Z.↗
DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Bayesian experimental design and parameter estimation for ultrafast spin dynamics

Abstract Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and materials physics, which often suffer from the scarcity of large-scale facility resources, such as x-ray or neutron scattering centers. To address these limitations, we introduce a methodology that leverages the Bayesian optimal experimental design paradigm to efficiently uncover key quantum spin fluctuation parameters from x-ray photon fluctuation spectroscopy (XPFS) data. Our method is compatible with existing theoretical simulation pipelines and can also be used in combination with fast machine learning surrogate models in the event that real-time simulations are unfeasible. Our numerical benchmarks demonstrate the superior performance in predicting model parameters and in delivering more informative measurements within limited experimental time. Our method can be adapted to many different types of experiments beyond XPFS and spin fluctuation studies, facilitating more efficient data collection and accelerating scientific discoveries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cyber Attack Sequences Generation for Electric Power Grid

Security assessment of cyber-physical energy systems (CPESs) such as the electric power grid is a critical operation to maintain availability, reliability, and quality of service in the presence of persistent threats from malicious cyber actors. Existing security assessment approaches such as penetration testing and red teaming rely on subject matter expert experience and forensic cyber analysis of historical events to perform realistic, threat-informed assessments of CPES defense. CPESs have a large attack surface because of the heterogeneity and complexity of underlying topology, devices, measurements, and vulnerabilities. The aforementioned approaches lead to partial coverage of the attack surface with a large set of unknown but possible exploits. There is a need to automate the CPES attack surface discovery and contextualize it for relevant, highly probable, real-world attack scenarios. We propose a methodology and framework to facilitate the discovery of the CPES attack surface. We present a multilayer attack graph with ranked attack sequences to describe CPES failure scenarios. We present a work-in-progress framework that lists key components to automate the attack modeling and sequence generation. We demonstrate the published National Electric Sector Cybersecurity Organization Resource CPES failure scenario to highlight the trustworthiness of generated attack sequences.

Dutta, Ashutosh↗
DOE OSTI2025

Kinematic Evidence for Bipolar Ejecta Flows in the Galactic Supernova Remnant W49B

W49B is a unique Galactic supernova remnant with centrally peaked, “bar”-like ejecta distribution, which was once considered evidence for a hypernova origin that resulted in a bipolar ejection of the stellar core. However, chemical abundance measurements contradict this interpretation. Closely connected to the morphology of the ejecta is its velocity distribution, which provides critical details for understanding the explosion mechanism. We report the first ever observational constraint on the kinematics of the ejecta in W49B using the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission (XRISM). Using XRISM/Resolve, we measured the line-of-sight velocity traced by the Fe Heα emission, which is the brightest feature in the Resolve spectrum, to vary by ±300 km s −1 with a smooth east-to-west gradient of a few tens of kilometers per second per parsec along the major axis. Similar trends in the line-of-sight velocity structure were found for other Fe-group elements Cr and Mn, traced by the Heα emission, and also for intermediate-mass elements Si, S, Ar, and Ca, traced by the Lyα emission. The discovery of the east–west gradient in the line-of-sight velocity, together with the absence of a twin-peaked line profile or enhanced broadening in the central region, clearly rejects the equatorially expanding disk model. In contrast, the observed velocity structure suggests bipolar flows reminiscent of a bipolar explosion scenario. An alternative scenario would be a collimation of the ejecta by an elongated cavity sculpted by bipolar stellar winds.

High resolution spectroscopy↗
NASA NTRS1986

Free precession in quasi-periodic oscillators

The recent discoveries of quasi-periodic oscillations (QPOs) brought about a surge of theoretical work concerned with the disk-magnetosphere boundary in accreting neutron stars. Much of the detailed theoretical discussion deals with the beat-frequency model (BFM). The beat frequency (BF) spectrum resulting from applying the BFM to the most general freely rotating neutron star, i.e., a freely precessing neutron star whose angular momentum vector is, in addition, not perpendicular to the disk, is considered. It is found that in the course of free precession, the BF spectrum usually changes, with the various QPO lines changing in intensity. This allows, in principle, phenomena of frequency changing not due to changes in luminosity such as those observed in Cyg X-2 and, perhaps, in other QPOs. Such 'mode' changes may, in turn, reflect the nature of the disk-magnetosphere coupling in QPOs.

Shaham, Jacob↗
NASA NTRS1988

Observations of supernova SN1987a

Supernova SN1987a was discovered on February 23, 1987, in the Large Magellanic Cloud, a nearby galaxy that is visible only from the Southern Hemisphere. The NASA program for observations of SN1987a, which was developed rapidly after the discovery of the explosion, was designed to be implemented through a series of coordinated campaigns of gamma-ray, X-ray, ultraviolet, and infrared observations from spacecraft, rockets, balloons, aircraft and the ground. The author summarizes models for supernovae, recent results for SN1987a, and the NASA plans for further observations.

Riegler, Guenter R.↗
DOE OSTI2024

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗