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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Unusual Central Engine Activity in the Double Burst GRB 110709B

The double burst, GRB 110709B, triggered Swift/BAT twice at 21:32:39 UT and 21:43:45 UT, respectively, on 9 July 2011. This is the first time we observed a GRB with two BAT triggers. In this paper, we present simultaneous Swift and Konus-WIND observations of this unusual GRB and its afterglow. If the two events are from the same physical origin, their different time-dependent spectral evolution suggest they must belong to different episodes of the central engine, which may be a magnetar-to-BH accretion system.

Zhang, Bin-Bin↗
NASA NTRS2016

The Asteroid Redirect Mission (ARM): Exploration of a Former Binary NEA?

The National Aeronautics and Space Administration (NASA) is developing the Asteroid Redirect Mission (ARM) as a capability demonstration for future human exploration, including use of high-power solar electric propulsion, which allows for the efficient movement of large masses through deep space. The ARM will also demonstrate the capability to conduct proximity operations with natural space objects and crewed operations beyond the security of quick Earth return. The Asteroid Redirect Robotic Mission (ARRM), currently in formulation, will visit a large near-Earth asteroid (NEA), collect a multi-ton boulder from its surface, conduct a demonstration of a slow push planetary defense technique, and redirect the multi-ton boulder into a stable orbit around the Moon. Once returned to cislunar space in the mid-2020s, astronauts aboard an Orion spacecraft will dock with the robotic vehicle to explore the boulder and return samples to Earth. The ARM is part of NASA's plan to advance technologies, capabilities, and spaceflight experience needed for a human mission to the Martian system in the 2030s. The ARM and subsequent availability of the asteroidal material in cis-lunar space, provide significant opportunities to advance our knowledge of small bodies in the synergistic areas of science, planetary defense, and in-situ resource utilization (ISRU). The current reference target for the ARM is NEA (341843) 2008 EV5, which may have been the primary body of a former binary system (Busch et al., 2011; Tardivel et al., 2016). The ARRM will perform several close proximity operations to investigate the NEA and map its surface. A detailed investigation of this object may allow a better understanding of binary NEA physical characteristics and the possible outcomes for their evolution. An overview of the ARM robotic and crewed segments, including mission operations, and a discussion of potential opportunities for participation with the ARM will be provided in this presentation.

Abell, P. A.↗
NASA NTRS1992

Low-mass X-ray binaries and gamma-ray bursts

More than twenty years after their discovery, the nature of gamma-ray burst sources (GRBs) remains mysterious. The results from BATSE experiment aboard the Compton Observatory show however that most of the sources of gamma-ray bursts cannot be distributed in the galactic disc. The possibility that a small fraction of sites of gamma-ray bursts is of galactic disc origin cannot however be excluded. We point out that large numbers of neutron-star binaries with orbital periods of 10 hr and M dwarf companions of mass 0.2-0.3 solar mass are a natural result of the evolution of low-mass X-ray binaries (LMXBs). The numbers and physical properties of these systems suggest that some gamma-ray burst sources may be identified with this endpoint of LMXB evolution. We suggest an observational test of this hypothesis.

Lasota, J. P.↗
NASA NTRS2022

Flows in Enthalpy-based Thermal Evolution of Loops

Plasma-filled loop structures are common in the solar corona. Because detailed modeling of the dynamical evolution of these structures is computationally costly, an efficient method for computing approximate but quick physics-based solutions is to rely on space-integrated 0D simulations. The enthalpy-based thermal evolution of loops (EBTEL) framework is a commonly used method to study the exchange of mass and energy between the corona and transition region. EBTEL solves for density, temperature, and pressure, averaged over the coronal part of the loop, velocity at coronal base, and the instantaneous differential emission measure distribution in the transition region. The current single-fluid version of the code, EBTEL2, assumes that at all stages the flows are subsonic. However, sometimes the solutions show the presence of supersonic flows during the impulsive phase of heat input. It is thus necessary to account for this effect. Here, we upgrade EBTEL2 to EBTEL3 by including the kinetic energy term in the Navier–Stokes equation. We compare the solutions from EBTEL3 with those obtained using EBTEL2, as well as the state-of-the-art field-aligned hydrodynamics code HYDRAD. We find that the match in pressure between EBTEL3 and HYDRAD is better than that between EBTEL2 and HYDRAD. Additionally, the velocities predicted by EBTEL3 are in close agreement with those obtained with HYDRAD when the flows are subsonic. However, EBTEL3 solutions deviate substantially from HYDRAD’s when the latter predicts supersonic flows. Using the mismatches in the solution, we propose a criterion to determine the conditions under which EBTEL can be used to study flows in the system.

Solar coronal heating↗
DOE OSTI2025

A Review of Intense Electromagnetic Fields in Heavy-Ion Collisions: Theoretical Predictions and Experimental Results

In heavy-ion collisions at relativistic energies, the incident nuclei travel at nearly the speed of light. These collisions deposit kinetic energy into the overlap region and create a high-temperature environment where hadrons “melt” into deconfined quarks and gluons. The spectator nucleons, which do not undergo scatterings, generate an ultraintense electromagnetic field—on the order of 10 18 G at the Relativistic Heavy Ion Collider and 10 19 G at the Large Hadron Collider. These powerful electromagnetic fields have a substantial impact on the produced particles, not only complicating the study of particle interactions but also inducing novel physical phenomena. To explore the nature of these fields and their interactions with deconfined quarks, we provide a detailed overview, encompassing theoretical estimations of their generation and evolution, as well as experimental efforts to detect them. We also provide physical interpretations of the discovered results and discuss potential directions for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

Nature and evolution of the meteorite parent bodies: Evidence from petrology and metallurgy

The physical as well as chemical properties of the meteorite parent bodies are reviewed and it is concluded that many differentiated meteorites were likely formed in asteroidal-sized parents. A new model is developed for the formation of pallasites at the interface between an iron core and olivine mantle in differentiated bodies only about 10 km in diameter, which are later incorporated into a second generation of larger (100 km) parent bodies.

Wood, J. A.↗
NASA NTRS2012

SN 1987 A: A Unique Laboratory for Shock Physics

Supernova 1987 A has given us an unprecedented view of the evolution of the explosion debris and its interaction with circumstellar matter. The outer supernova debris, now expanding with velocities approx.8000 km/s, encountered the relatively dense circumstellar ring formed by presupernova mass loss in the early 1990s. The shock interaction is manifested by UV-optical "hotspots", an expanding X-ray ring, an expanding ring of knotty non-thermal radio emission, and a ring of thermal IR emission from silicate dust Recent ultraviolet observations of the emissions from the reverse shock and the ring with the HST/COS reveal new details about the shock interaction. Lyman alpha emission from the reverse shock is much stronger than H alpha and they have different emission morphologies, pointing to different emission mechanisms. The reverse shock was detected for the first time in C IV 1550. The N V to C IV brightness ratio indicates the N/C abundance ratio in the expanding debris is about 100X solar, about 3X N/C in the inner ring.

Sonneborn, George↗
NASA NTRS1996

Evolution of Imaging Spectrometry: Past, Present and Future

An overview of the physical principals of imaging spectrometry for detailed characterization of remote objects and of gas vapors is given. The terms Multi-spectral, Hyperspectral, and Ultra-spectral are defined within the framework of applications and instrument system design approaches.

imaging↗
NASA NTRS2002

Photoevaporation of Clumps in Photodissociation Regions

We present the results of an investigation of the effects of Far Ultraviolet (FUV) radiation (6.0eV < hv < 13.6eV) from hot early type OB stars on clumps in star-forming molecular clouds. Clumps in FUV-illuminated regions (or photodissociation regions or PDRs) undergo external heating and photodissociation as they are exposed to the FUV field, resulting in a loss of cold, molecular lump mass as it is converted to warm atomic gas. The heating, if rapid, creates strong photoevaporative mass flows off the clump surfaces, and drives shocks into the clumps, compressing them to high densities. The clumps lose mass on relatively short timescales. The evolution of an individual clump is found to be sensitive to three dimensionless parameters: Nc0, the ratio of the initial column density of the clump to the column N(0) approx. 10(exp 21) cm(exp -2) of a warm FUV-heated surface region; upsilon, the ratio of the sound speed in the heated surface to that in the cold clump material: and t(FUV)t(c), the ratio of the "turn-on time" t(FUV) of the heating flux on a clump to its initial sound crossing-time t(c). The evolution also depends on whether a confining interclump medium exists, or whether the interclump region has negligible pressure, as is the case for turbulence-generated clumps. In this paper, we use spherical 1-D numerical hydrodynamic models as well as approximate analytical models to study the dependence of clump photoevaporation on the physical parameters of the clump, and to derive the dynamical evolution, mass loss rates and photoevaporative timescales of a clump for a variety of astrophysical situations. Turbulent clumps evolve so that their column densities are equal to a critical value determined by the local FUV field, and typically have short photo evaporation timescales, approx. 10(exp 4-5) years for a 1 M(solar mass) clump in a typical star-forming region (Nc0 = 10, upsilon = 10). Clumps with insufficient magnetic pressure support, and in strong FUV fields may be driven to collapse by the compressional effect of converging shock waves. We also estimate the rocket effect on photoevaporating clumps and find that it is significant only for the smallest clumps, with sizes much less than the extent of the PDR itself. Clumps that are confined by all interclump medium may either get completely photoevaporated, or may preserve a shielded core with a warm, dissociated, protective shell that, absorbs the incident FUV flux. We compare our results with observations of some well studied PDRs: the Orion Bar, M17SW NGC 2023 and the Rosette Nebula. The data are consistent with both interpretations of clump origin. turbulence and pressure confinement, with a slight indication for favouring the turbulent model for clumps over pressure-confined

Gorti, Uma↗
NASA NTRS1977

The evolution of asteroids as meteorite parent-bodies

The hypothesis that the asteroid belt is the source region for nearly all meteorites, remains viable and there is no compelling reason to ascribe any meteorites to cometary origin. On the other hand, uncertainties about the true composition of the larger S type asteroids and difficulties in finding plausible main-belt source-bodies for the ordinary chondrites leave room open for further speculation on this question. The scenario for the evolution of asteroids, based on collisional models of two distinct populations of different physical properties, is being criticized and refined. It remains uncertain whether this approach will ultimately prove to be the correct interpretation of the collisional evolution of asteroids.

Chapman, C. R.↗
NASA NTRSDate not supplied

Imaging Science Requirements for a Uranus Flagship Mission

Introduction: Our presentation will summarize the requirements for UV/Visible/Near-IR remote-sensing imaging science instruments (including mapping spectrometers) envisioned for the Uranus Orbiter and Probe (UOP) mission recommended by the recent planetary decadal survey. The Uranus system offers many targets for imaging investigations. Imaging science investigations are crucial to answering fundamental questions about various physical processes that shape the Uranian system and drive its evolution. Each science objective addressed through imaging has requirements for observation and illumination geometries as well as coverage and resolution in the spatial, spectral and temporal dimensions. By combining the requirements for the diverse science targets in the Uranian system, we present a set of overarching imaging science requirements for UOP. Atmospheric Science: The study of Uranus’ atmosphere is crucial in understanding the planet's energy balance and interior heat flux. Imaging observations map how the atmosphere scatters incident solar radiation. Imaging is key to characterizing planetary-scale energy/material transport though global atmospheric dynamics and local meteorology. Hyperspectral mapping combined with radiative transfer analysis reveals the vertical distribution of clouds and hazes. Chronicling temporal variabilities of atmospheric features is key to understanding the various processes that operate within the dynamic Uranian atmosphere. A comprehensive understanding of Uranus' atmosphere is essential in deciphering the planet's origins and evolution as well as providing insight into the broader field of planetary and exoplanetary science. Magnetospheric Interactions: Imaging science is critical to understand the elusive Uranian aurorae. Mapping the aurorae and their temporal dynamics will reveal the interaction of Uranus’ complex magnetosphere with the solar wind. The apparent decades-long cooling of Uranus’ upper atmosphere is thought to be due to changes in energy input from the overlying magnetosphere, and so mapping and quantifying the auroral evidence for this energy flux is particularly relevant for upper atmospheric science In addition, Uranus’ large moons may generate auroral footprints, which can be used to constrain the planet’s unusual magnetic field structure. Satellite Interiors: Imaging science can address the potential habitability of the larger moons of Uranus by measuring their shapes and rotational states (including librations), which combined with gravity data are crucial to understanding their internal density structure. Satellite Origins: Origin markers such as organics and volatiles may be preserved on the satellite surfaces, which may be sensed by UV/IR mapping. Imaging combined with the moons’ densities may reveal whether the moons formed in Uranus’ circumplanetary disk, rings, or from ejecta of a giant impact on Uranus. Satellite Geology: Imaging investigations, including stereo imaging to obtain topography, will enable constraining each satellite’s geologic history by investigating the distributions and morphologies of impact craters, tectonic and potential cryovolcanic features, and regolith and mass wasting deposits. These records will help unravel the past complex history of orbital resonances that occurred between Uranian satellites, which may have driven geologic activity. Analyses of these features will also point to resurfacing styles and modification processes important for understanding each moon’s thermal evolution, and any present-day geological activity, including potential subsurface deep oceans or possible current activity. Additionally, hyperspectral imaging will enable mapping the surface composition and identifying the potential presence of material that may point to a subsurface ocean, such as ammonia-bearing species. Rings and Small Moons: Imaging observations elucidate the physical processes that contribute to the complex ring-moon system’s inferred unstable state. Imaging surveys will seek smaller moons and other debris that could provide evidence of past collisions, while precise astrometric data of moons will determine the current dynamical state of the system. Many of Uranus' rings are exceptionally narrow, and images of the rings covering a broad range of longitudes, and high-resolution images of features within the rings will reveal how these rings are confined and maintained, as well as illustrating the rings' internal structure and dynamics. Images of the rings and moons obtained at a variety of wavelengths and lighting conditions are also needed to quantify the composition and the size distribution of the small satellites and ring particles.

K M Sayanagi↗
NASA NTRS2000

Computing Needs for Astrobiology: Models of Planetary Formation

Theories of planet formation indicate that a diverse range of physical and chemical processes determine the characteristics of a planetary system. Extensive numerical modeling is required to understand how planetary systems form, and to make quantitative assessments of the factors which determine the masses, spacings and volatile compound inventories of planets and small bodies within a planetary system. Fluid flow problems associated with the formation and evolution of protoplanetary disks include specific local calculations to provide physical insight, which are best performed on workstations, and large multifaceted simulations which require supercomputers with large memories. Formation and early growth of planetesimals display a similar range of computational requirements. Modeling the late stages of planetary accumulation is very CPU intensive, as it requires following a simple system of approx. hundreds of bodies for millions of dynamical (orbital) times. These varied computational needs could be met in the most cost-effective manner by a diverse set of computers, including workstations for individual PI's and dedicated time on various types of supercomputers which are specialized for differing tasks.

Lissauer, Jack J.↗
NASA NTRS1990

Coupling of Coastal Zone Color Scanner data to a physical-biological model of the southeastern U.S. continental shelf ecosystem. I - CZCS data description and Lagrangian particle tracing experiments. II - An Eulerian model. III - Nutrient and phytoplankton fluxes and CZCS data assimilation

Surface phytoplankton biomass of the southeastern U.S. continental shelf area is discussed based on coastal zone color scanner (CZCS) images obtained in April 1980. Data of chlorophyll distributions are analyzed in conjunction with concurrent flow and temperature fields. Lagrangian particle tracing experiments show that the particles move consistently with the evolution of the chlorophyll patterns. A four-component physical-biological model for a horizontal plane at a nominal depth of 17 m is presented. Model simulations using various physical-biological dynamics and boundary conditions show that the variability of chlorophyll distributions is controlled by horizontal advection. Phytoplankton and nutrient fluxes, calculated using the model, show considerable variability with time. The chlorophyll distributions obtained from the CZCS images are assimilated into the model to improve the phytoplankton flux estimates.

Ishizaka, Joji↗
NASA NTRS2019

The Physics of Accretion Onto Highly Magnetized Neutron Stars

Studying the physical processes occurring in the region just above the magnetic polesof strongly magnetized, accreting binary neutron stars is essential to our understanding of stellarand binary system evolution. Perhaps more importantly, it provides us with a natural laboratoryfor studying the physics of high temperature and density plasmas exposed to extreme radiation,gravitational, and magnetic fields. Observations over the past decade have shed new light on themanner in which plasma falling at near the speed of light onto a neutron star surface is halted. Recentadvances in modeling these processes have resulted in direct measurement of the magnetic fieldsand plasma properties. On the other hand, numerous physical processes have been identified thatchallenge our current picture of how the accretion process onto neutron stars works. Observationand theory are our essential tools in this regime because the extreme conditions cannot be duplicatedon Earth. This white paper gives an overview of the current theory, the outstanding theoreticaland observational challenges, and the importance of addressing them in contemporary astrophysicsresearch.

Wolff, Michael T.↗
DOE OSTI2026

Subseasonal Forecasting and MJO Teleconnections in Machine Learning Weather Prediction Models

Abstract In recent years, machine‐learning (ML) models trained on reanalysis data have rivaled physics‐based forecast models in terms of performance skill for global weather forecasting. With increased rollout stability, the question of how these models perform for subseasonal to seasonal (S2S, week 3–8) forecasting has emerged. In this study we run a large set of subseasonal hindcasts over 2004–2023 to evaluate two ML weather forecast models at the S2S time scale, SFNO‐HENS (Nvidia, fully ML) and NeuralGCM (Google Research, hybrid). Corresponding hindcasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) are used as a baseline for comparison to a physics‐based model. Because our focus is on predicting moisture transport over the Western United States between October and March, we evaluate the models' prediction skill for the Madden‐Julian Oscillation (MJO) and its associated teleconnections in the North Pacific. We find that both ML models are competitive with the ECWMF model, with comparable skill in predicting the North Pacific large‐scale circulation and the MJO at week 3 and beyond. Even though overall the mid‐latitude subseasonal prediction skill remains low, the ML models exhibit interesting behavior such as a realistic propagation of the MJO across the Maritime Continent and realistic teleconnections. A SFNO‐HENS sensitivity experiment with altered initial conditions in the tropics demonstrates the stability of the model, and it illustrates the capability of ML models to represent important physical processes of the atmosphere at the S2S time scale. Plain Language Summary Predicting weather patterns and precipitation a few weeks in advance (subseasonal time scale) is of great interest for stakeholders such as water managers in the Southwest United States (US), where arid conditions prevail. Subseasonal forecasts from traditional weather forecast models exhibit low skill in the region, limiting their applicability. Here we examine whether the recent breakthrough in weather forecasting made with machine learning/artificial intelligence models can translate to improved subseasonal forecasts. Recently‐developed machine learning models exhibit comparable skill to a state‐of‐the‐art physics‐based model for predicting weather patterns in the North Pacific/North America region, and associated moisture transport. The same applies to their skill in predicting the tropical pattern, the Madden‐Julian Oscillation, and its important remote perturbations over the midlatitude East Pacific and Southwest US. Additionally, a perturbation experiment carried out with one of the machine learning models illustrates their ability to not only predict the evolution of atmospheric fields, but also to learn and represent physical processes such as tropics‐extratropics Rossby wave propagation. Key Points Two machine learning weather forecast models exhibit state‐of‐the‐art prediction skill at the subseasonal time scale in the Pacific sector The models equal ECWMF in terms of Madden‐Julian oscillation (MJO) prediction skill, and they accurately predict the MJO propagation and associated teleconnections The two machine‐learning models represent key physical processes for subseasonal prediction, despite being trained for weather forecasting

Peings, Yannick↗
DOE OSTI2024

Data-driven modeling of dislocation mobility from atomistics using physics-informed machine learning

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Recurrent convolutional neural networks for modeling nonadiabatic dynamics of quantum-classical systems

Recurrent neural networks (RNNs) have recently been extensively applied to model the time evolution in fluid dynamics, weather predictions, and even chaotic systems due to their ability to capture temporal dependencies and sequential patterns in data. Here we present an RNN model based on convolutional neural networks for modeling the nonlinear nonadiabatic dynamics of hybrid quantum-classical systems. The dynamical evolution of the hybrid systems is governed by equations of motion for classical degrees of freedom and von Neumann equation for electrons. The Physics-Aware Recurrent Convolution (PARC) neural network structure incorporates a differentiator-integrator architecture that inductively models the spatiotemporal dynamics of generic physical systems. Here, we apply our RNN approach to learn the space-time evolution of a one-dimensional semiclassical Holstein model after an interaction quench. For shallow quenches (small changes in electron-lattice coupling), the deterministic dynamics can be accurately captured using a single-CNN-based recurrent network. In contrast, deep quenches induce chaotic evolution, making long-term trajectory prediction significantly more challenging. Nonetheless, we demonstrate that the PARC-CNN architecture can effectively learn the statistical climate of the Holstein model under deep-quench conditions.

Holstein model↗
NASA NTRS2006

Exploring the Mineralogy of the Moon with M3

From the initial era or lunar exploration, we have learned that many processes active on the early Moon are common to most terrestrial planets, including the record of early and late impact bombardment. Since most major geologic activity ceased on the Moon approx. 3 Gy ago, the Moon's surface provides a record of the earliest era of terrestrial planet evolution. The type and composition of minerals that comprise a planetary surface are a direct result of the initial composition and subsequent thermal and physical processing. Lunar mineralogy seen today is thus a direct record of the early evolution of the lunar crust and subsequent geologic processes. Specifically, the distribution and concentration of specific minerals is closely tied to magma ocean products, lenses of intruded or remelted plutons, basaltic volcanism and fire-fountaining, and any process (e.g. cratering) that might redistribute or transform primary and secondary lunar crustal materials. The Moon Mineralogy Mapper (M3, or "m-cube") is a state-of-the-art imaging spectrometer that will fly on Chandrayaan-1, the Indian Space Research Organization (ISRO) mission to be launched late 2007 to early 2008. M3 is one of several foreign instruments chosen by ISRO to be flown on Chandrayaan-1 to complement the strong ISRO payload package. M3 was selected through a peer-review process as part of NASA s Discovery Program. It is under the oversight of PI Carle Pieters at Brown University and is being built by an experienced team at the Jet Propulsion Laboratory. Data analysis and calibration are carried out by a highly qualified and knowledgeable Science Team. To characterize diagnostic properties of lunar minerals, M3 acquires high spectral resolution reflectance data from 700 to 3000 nm (optional to 430 nm). M3 operates as a pushbroom spectrometer with a slit oriented orthogonal to the S/C orbital motion. Measurements are obtained simultaneously for 640 cross track spatial elements and 261 spectral elements. This translates to 70 m/pixel spatial resolution from a nominal 100 km polar orbit for Chandrayaan-1 . The primary science goal of M3 is to characterize and map lunar surface mineralogy in the context of its geologic evolution as outlined above. This translates into several sub-topics that focus on exploring the mineral character of the highland crust, characterizing the diversity basaltic volcanism, and identifying potential volatile concentrations near the poles. The primary exploration goal is to assess and map lunar mineral resources at high spatial resolution to support planning for future, targeted missions.

Pieters, C. M.↗