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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

FACET: Future ATM Concepts Evaluation Tool

FACET (Future ATM Concepts Evaluation Tool) is an Air Traffic Management research tool being developed at the NASA Ames Research Center. This paper describes the design, architecture and functionalities of FACET. The purpose of FACET is to provide E simulation environment for exploration, development and evaluation of advanced ATM concepts. Examples of these concepts include new ATM paradigms such as Distributed Air-Ground Traffic Management, airspace redesign and new Decision Support Tools (DSTs) for controllers working within the operational procedures of the existing air traffic control system. FACET is currently capable of modeling system-wide en route airspace operations over the contiguous United States. Airspace models (e.g., Center/sector boundaries, airways, locations of navigation aids and airports) are available from databases. A core capability of FACET is the modeling of aircraft trajectories. Using round-earth kinematic equations, aircraft can be flown along flight plan routes or great circle routes as they climb, cruise and descend according to their individual aircraft-type performance models. Performance parameters (e.g., climb/descent rates and speeds, cruise speeds) are obtained from data table lookups. Heading, airspeed and altitude-rate dynamics are also modeled. Additional functionalities will be added as necessary for specific applications. FACET software is written in Java and C programming languages. It is platform-independent, and can be run on a variety of computers. FACET has been designed with a modular software architecture to enable rapid integration of research prototype implementations of new ATM concepts. There are several advanced ATM concepts that are currently being implemented in FACET airborne separation assurance, dynamic density predictions, airspace redesign (re-sectorization), benefits of a controller DST for direct-routing, and the integration of commercial space transportation system operations into the U.S. National Airspace System (NAS).

Bilmoria, Karl D.↗
NASA NTRS2009

Analysis of Trajectory Flexibility Preservation Impact on Traffic Complexity

The growing demand for air travel is increasing the need for mitigation of air traffic congestion and complexity problems, which are already at high levels. At the same time new information and automation technologies are enabling the distribution of tasks and decisions from the service providers to the users of the air traffic system, with potential capacity and cost benefits. This distribution of tasks and decisions raises the concern that independent user actions will decrease the predictability and increase the complexity of the traffic system, hence inhibiting and possibly reversing any potential benefits. In answer to this concern, the authors proposed the introduction of decision-making metrics for preserving user trajectory flexibility. The hypothesis is that such metrics will make user actions naturally mitigate traffic complexity. In this paper, the impact of using these metrics on traffic complexity is investigated. The scenarios analyzed include aircraft in en route airspace with each aircraft meeting a required time of arrival in a one-hour time horizon while mitigating the risk of loss of separation with the other aircraft, thus preserving its trajectory flexibility. The experiments showed promising results in that the individual trajectory flexibility preservation induced self-separation and self-organization effects in the overall traffic situation. The effects were quantified using traffic complexity metrics, namely dynamic density indicators, which indicated that using the flexibility metrics reduced aircraft density and the potential of loss of separation.

Idris, Husni↗
NASA NTRS2011

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗
NASA NTRS2016

A New Operational Snow Retrieval Algorithm Applied to Historical AMSR-E Brightness Temperatures

Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE) is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily). In this regard, the data recorded by the Advanced Microwave Scanning Radiometer-Earth Orbiting System (EOS) (AMSR-E) onboard the National Aeronautics and Space Administration's (NASA) AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical AMSR-E data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current AMSR-E operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC) and GlobSnow datasets. Our results show that the AMSR-E algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.

passive microwave↗
NASA NTRS2017

Thermosphere Global Time Response to Geomagnetic Storms Caused by Coronal Mass Ejections

We investigate, for the first time with a spatial superposed epoch analysis study, the thermosphere global time response to 159 geomagnetic storms caused by coronal mass ejections (CMEs) observed in the solar wind at Earth's orbit during the period of September 2001 to September 2011. The thermosphere neutral mass density is obtained from the CHAMP (CHAllenge Mini-Satellite Payload) and GRACE (Gravity Recovery Climate Experiment) spacecraft. All density measurements are intercalibrated against densities computed by the Jacchia-Bowman 2008 empirical model under the regime of very low geomagnetic activity. We explore both the effects of the pre-CME shock impact on the thermosphere and of the storm main phase onset by taking their times of occurrence as zero epoch times (CME impact and interplanetary magnetic field Bz southward turning) for each storm. We find that the shock impact produces quick and transient responses at the two high-latitude regions with minimal propagation toward lower latitudes. In both cases, thermosphere is heated in very high latitude regions within several minutes. The Bz southward turning of the storm onset has a fast heating manifestation at the two high-latitude regions, and it takes approximately 3 h for that heating to propagate down to equatorial latitudes and to globalize in the thermosphere. This heating propagation is presumably accomplished, at least in part, with traveling atmospheric disturbances and complex meridional wind structures. Current models use longer lag times in computing thermosphere density dynamics during storms. Our results suggest that the thermosphere response time scales are shorter and should be accordingly adjusted in thermospheric empirical models.

mass ejections↗
DOE OSTI2024

INL Poster - Juan Barrera Salazar

Generation IV nuclear reactors introduce several advantages and benefits in terms of safety and efficiency when compared with their predecessors from previous generation. This is due, among many things, to the use of innovative forms of fuel and coolant, different from the conventional ones used in the last decades. Given that these upcoming designs utilize emerging technologies, the related instrumentation is also in the process of being developed; therefore, it is necessary to establish the sensitivity requirements and the effects of uncertainty on different properties of the components and elements of the reactor designs. This report presents the results of simulations that quantify the impacts of the uncertainties of four thermophysical properties of the refrigerant salt (LiF-BeF2) for the Kairos Power benchmark model (g-FHR) for steady state making use of the Sobol’ method through polynomial chaos surrogate modeling. The properties of the salt to which uncertainty was evaluated were density, dynamic viscosity, thermal conductivity and heat capacity. This study was carried out using the Griffin/Pronghorn multiphysics model under the computational resources of the Idaho National Laboratory (INL) High Performance Computing (HPC). The results indicate a weak dependence of the uncertainty of thermal conductivity on the quantities of core pressure drop and core outlet temperature.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2020

Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO 3

In order to provide a comprehensive theoretical description of MgSiO 3 at extreme conditions, we combine results from path integral Monte Carlo and density functional molecular dynamics simulations and generate a consistent equation of state for this material. We consider a wide range of temperature and density conditions from 10 4 to 10 8 K and from 0.321 to 64.2 g/cm -3 (0.1- to 20-fold the ambient density). We study how the L and K shell electrons are ionized with increasing temperature and pressure. We derive the shock Hugoniot curve and compare with experimental results. Our Hugoniot curve is in good agreement with the experiments, and we predict a broad compression maximum that is dominated by the K shell ionization of all three nuclei while the peak compression ratio of 4.70 is obtained when the Si and Mg nuclei are ionized. To conclude, we analyze the heat capacity and structural properties of the liquid.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Density profile of dynamical halos

Among the most fundamental properties of a dark matter halo is its density profile. Motivated by the recent proposal by García et al . [Mon. Not. R. Astron. Soc. 521 , 2464 (2023)] to define a dynamical halo as the collection of orbiting particles in a gravitationally bound structure, we characterize the mean and scatter of the orbiting profile of dynamical halos as a function of their orbiting mass. Here, we demonstrate that the orbiting profile of individual halos at fixed mass depends on a single dynamical variable, the halo radius 𝑟 h , which characterizes the spatial extent of the profile. The scatter in halo radius at fixed orbiting mass is ≈16%. Only a small fraction of this scatter arises due to differences in halo formation time, with late-forming halos being more compact (smaller halo radii). Accounting for this additional correlation results in an ≈11% scatter in halo radius at fixed mass and halo formation time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Echo state network for coarsening dynamics of charge density waves

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer. Compared with other recurrent neural networks, one great advantage of ESN is the simplicity of its training process. Yet, despite the seemingly restricted learnable parameters, ESN has been shown to successfully capture the spatial-temporal dynamics of complex patterns. Here we build an ESN to model the coarsening dynamics of charge-density waves (CDWs) in a semiclassical Holstein model, which exhibits a checkerboard electron density modulation at half-filling stabilized by a commensurate lattice distortion. The inputs to the ESN are local CDW order parameters in a finite neighborhood centered around a given site, while the output is the predicted CDW order of the center site at the next time step. Special care is taken in the design of couplings between hidden layer and input nodes to ensure lattice symmetries are properly incorporated into the ESN model. Since the model predictions depend only on CDW configurations of a finite domain, the ESN is scalable and transferrable in the sense that a model trained on dataset from a small system can be directly applied to dynamical simulations on larger lattices. Furthermore, our work opens avenues for efficient dynamical modeling of pattern formations in functional electron materials.

2-dimensional systems↗
DOE OSTI2025

Al–W gradient density materials—Processing and dynamic ramp compression

Materials with high-density gradients are desired for controlling loading paths in dynamic compression, important for studying material properties in extreme conditions and inertial confinement fusion. The large density difference between Al and W makes them ideal choices for producing gradient density materials, but their extremely different melting temperatures make them challenging to fabricate simultaneously. We report a method for producing Al–W porosity-free materials with a fourfold increase in density (2.7–11 g/cm 3 ) across the composition range, from Al-rich to W-rich, without intermetallic phase formation. This was achieved by understanding the aluminum-dominated densification behavior and examining the influence of pressure and temperature on the densification of Al–W composites. Dynamic compression experiments conducted with the Al–W gradient density material produced shock ramp compressions as expected based on the designed composition, and the performed hydrodynamics simulations showed excellent agreement with experimental results. The results demonstrate that current activated pressure-assisted densification allows for the easy and rapid fabrication of gradient density materials with significant density gradients and tailored compositions, facilitating precise control of the loading paths. These materials have the potential to create customized pressure drives for advancing the fields of material science in extreme environments and dynamic compression.

Alloys↗
DOE OSTI2021

Directional locking and the influence of obstacle density on skyrmion dynamics in triangular and honeycomb arrays

In this work, we numerically examine the dynamics of a single skyrmion driven over triangular and honeycomb obstacle arrays at zero temperature. The skyrmion Hall angle θ sk , defined as the angle between the applied external drive and the direction of the skyrmion motion, increases in quantized steps or continuously as a function of the applied drive. For the obstacle arrays studied in this work, the skyrmion exhibits two main directional locking angles of θ sk = –30° and –60°. We show that these directions are privileged due to the obstacle landscape symmetry, and coincide with channels along which the skyrmion may move with few or no obstacle collisions. Here we investigate how changes in the obstacle density can modify the skyrmion Hall angles and cause some dynamic phases to appear or grow while other phases vanish. This interesting behavior can be used to guide skyrmions along designated trajectories via regions with different obstacle densities. For fixed obstacle densities, we investigate the evolution of the locked θ sk = –30° and –60° phases as a function of the Magnus force, and discuss possibilities for switching between these phases using topological selection.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Characterization of the molten salt FMgNaK through ab initio molecular dynamics and experimental density measurements

The selection of a salt species for use in a molten salt reactor MSR is a key part of any MSR design. However, many salts have sparse or no thermophysical property data sets, especially those with higher melting points. One such salt is the eutectic mixture of (NaF)0.345(KF)0.59(MgF 2 )0.065, or FMgNaK, and is explored here through ab initio molecular dynamics (AIMD) simulation (1023-1273K) as well as experimental measurement of the liquid density using the Archimedean method (973-1223K). Predicted densities from AIMD are similar to experimentally-measured densities, though with more noise, suggesting that the small scale necessitated by AIMD simulations may be problematic for simulating FMgNaK in particular. Here the coefficient of thermal expansion is predicted from simulation, and salt structure is characterized. Mg-F-Mg chaining is observed in the salt network, though the low concentration of Mg inhibits chaining on the scale that is observed in (LiF) 0.67 (BeF 2 ) 0.33 , or FLiBe.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Here, our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Post-Flight Assessment of Low Density Supersonic Decelerator Flight Dynamics Test 2 Simulation

NASA's Low Density Supersonic Decelerator (LDSD) project conducted its second Supersonic Flight Dynamics Test (SFDT-2) on June 8, 2015. The Program to Optimize Simulated Trajectories II (POST2) was one of the flight dynamics tools used to simulate and predict the flight performance and was a major tool used in the post-flight assessment of the flight trajectory. This paper compares the simulation predictions with the reconstructed trajectory. Additionally, off-nominal conditions seen during flight are modeled in the simulation to reconcile the predictions with flight data. These analyses are beneficial to characterize the results of the flight test and to improve the simulation and targeting of the subsequent LDSD flights.

Dutta, Soumyo↗
DOE OSTI2022

Off-harmonic optical probing of high intensity laser plasma expansion dynamics in solid density hydrogen jets

Due to the non-linear nature of relativistic laser induced plasma processes, the development of laser-plasma accelerators requires precise numerical modeling. Especially high intensity laser-solid interactions are sensitive to the temporal laser rising edge and the predictive capability of simulations suffers from incomplete information on the plasma state at the onset of the relativistic interaction. Experimental diagnostics utilizing ultra-fast optical backlighters can help to ease this challenge by providing temporally resolved inside into the plasma density evolution. We present the successful implementation of an off-harmonic optical probe laser setup to investigate the interaction of a high-intensity laser at 5.4 x 10 21 W/cm 2 peak intensity with a solid-density cylindrical cryogenic hydrogen jet target of 5μm diameter as a target test bed. The temporal synchronization of pump and probe laser, spectral filtering and spectrally resolved data of the parasitic plasma self-emission are discussed. The probing technique mitigates detector saturation by self-emission and allowed to record a temporal scan of shadowgraphy data revealing details of the target ionization and expansion dynamics that were so far not accessible for the given laser intensity. Plasma expansion speeds of up to (2.3 ± 0.4)x 10 7 m/s followed by full target transparency at 1.4ps after the high intensity laser peak are observed. A three dimensional particle-in-cell simulation initiated with the diagnosed target pre-expansion at -0.2ps and post processed by ray tracing simulations supports the experimental observations and demonstrates the capability of time resolved optical diagnostics to provide quantitative input and feedback to the numerical treatment within the time frame of the relativistic laser-plasma interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Statistics of internal stress fluctuations in dislocated crystals and relevance to density-based dislocation dynamics models

A statistical analysis of internal stress fluctuations, defined as the difference between the local mean stress and stress on dislocations, is presented for deforming crystals with 3D discrete dislocation systems. Dislocation realizations are generated using dislocation dynamics simulations and the associated stress field is computed as a superposition of a regularized stress field of dislocation lines within the domain of the solution and a complementary stress field computed via a finite-element boundary value problem. The internal stress fluctuations of interest are defined by an ensemble of the difference between the stress on dislocation lines and the local mean field stress in the crystal. The latter is established in a piecewise fashion over small voxels in the crystal thus allowing the difference between the local average stress and stress on segments to be easily estimated. The results show that the Schmid stress (resolved shear stress) and Escaig stress fluctuations on various slip systems sampled over a random set of points follow a Cauchy (Lorentz) distribution at all strain levels, with the amplitude and width of the distribution being dependent on the strain. Finally, the implications of the Schmid and Escaig internal stress fluctuations are discussed from the points of view of dislocation cross-slip and the dislocation motion in continuum dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Associative polymers with controlled sticker placement: How reversible bond distribution and density govern polymer dynamics

Associative polymers with precisely arranged stickers offer opportunities to program material properties with molecular precision. Yet, it remains unclear how the placement and fraction of stickers dictate structure, dynamics, and macroscopic properties. By developing a model unentangled polymer system with hydrogen-bonding stickers, we show that randomly distributed stickers neither form clusters nor change flow properties, whereas stickers placed at chain ends drive nanocluster formation even at low concentrations. Adding more end stickers produces a rubbery plateau spanning eight decades in frequency with two distinct relaxation timescales, in contrast to the single plateau predicted by the classic sticky Rouse model. These results demonstrate that sticker distribution dictates whether associative polymers undergo nanocluster formation or microphase separation, while substantial alterations in dynamics and viscoelasticity require both sticker aggregation and thermomechanical stability of associated domains. Our findings resolve a longstanding debate on associative polymer dynamics and provide molecular design rules for programmable soft materials.

36 MATERIALS SCIENCE↗