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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Star formation and spiral structure in M81

High resolution digitized images of M81 in the radio continuum, H alpha, H I, and I band are used to see how well various density wave models agree in detail with observations. It was found that the observed width of the nonthermal radio arms favors a cloudy version of a density wave model. The radial distribution of the set of giant radio H II regions disagrees with the simple expression of Shu and Visser for star formation by a density wave. The observed displacements of the giant radio H II regions from the spiral velocity shock indicate that some revisions in the details of the ballistic particle model of Leisawitz and Bash are necessary.

Kaufman, Michele↗
NASA NTRS1982

Computing the Power-Density Spectrum for an Engineering Model

Computer program for calculating of power-density spectrum (PDS) from data base generated by Advanced Continuous Simulation Language (ACSL) uses algorithm that employs fast Fourier transform (FFT) to calculate PDS of variable. Accomplished by first estimating autocovariance function of variable and then taking FFT of smoothed autocovariance function to obtain PDS. Fast-Fourier-transform technique conserves computer resources.

Dunn, H. J.↗
DOE OSTI2025

Cryogenic thermal modeling of microwave high density signaling

Superconducting quantum computers require microwave control lines running from room temperature to the mixing chamber of a dilution refrigerator. Adding more lines without preliminary thermal modeling to make predictions risks overwhelming the cooling power at each thermal stage. In this paper, we investigate the thermal load of SC-086/50-SCN-CN semi-rigid coaxial cable, which is commonly used for the control and readout lines of a superconducting quantum computer, as we increase the number of lines to a quantum processor. We investigate the makeup of the coaxial cables, verify the materials and dimensions, and experimentally measure the total thermal conductivity of a single cable as a function of the temperature from cryogenic to room temperature values. We also measure the cryogenic DC electrical resistance of the inner conductor as a function of temperature, allowing for the calculation of active thermal loads due to Ohmic heating. Fitting this data produces a numerical thermal conductivity function used to calculate the static heat loads due to thermal transfer within the wires resulting from a temperature gradient. The resistivity data is used to calculate active heat loads, and we use these fits in a cryogenic model of a superconducting quantum processor in a typical Bluefors XLD1000-SL dilution refrigerator, investigating how the thermal load increases with processor sizes ranging from 100 to 225 qubits. We conclude that the theoretical upper limit of the described architecture is approximately 200 qubits. However, including an engineering margin in the cooling power and the available space for microwave readout circuitry at the mixing chamber, the practical limit is approximately 140 qubits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Partially averaged Navier-Stokes closure modeling for variable-density turbulent flow

We report this work extends the framework of the partially averaged Navier-Stokes (PANS) equations to variable-density flow, i.e., multimaterial and/or compressible mixing problems with density variations and production of turbulence kinetic energy by both shear and buoyancy mechanisms. The proposed methodology is utilized to derive the PANS BHR-LEVM closure. This includes a priori testing to analyze and develop guidelines toward the efficient selection of the parameters controlling the physical resolution and, consequently, the range of resolved scales of PANS. Two archetypal test-cases involving transient turbulence, hydrodynamic instabilities, and coherent structures are used to illustrate the accuracy and potential of the method: the Taylor-Green vortex at Reynolds number Re = 3000, and the Rayleigh-Taylor flow at Atwood number 0.5 and (Re) max ≈ 500. These representative problems, for which turbulence is generated by shear and buoyancy processes, constitute the initial validation space of the new model, and their results are comprehensively discussed in two subsequent studies. The computations indicate that PANS can accurately predict the selected flow problems, resolving only a fraction of the scales of large-eddy simulation and direct numerical simulation strategies. The results also reiterate that the physical resolution of the PANS model must guarantee that the key instabilities and coherent structures of the flow are resolved. The remaining scales can be modeled through an adequate turbulence scale-dependent closure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A 1D coupled transport/cold plasma wave model for parallel ponderomotive density modification near RF actuators

The plasma density profile close to RF actuators plays a vital role in the efficiency of power coupling from the antenna to the core plasma of fusion devices. Nonlinear interactions can be significant when considering the interaction of applied RF power and the tenuous SOL plasma, and the inclusion of this region in computational analysis is essential to providing robust predictive simulations of plasma response to RF application. Of particular interest is the observed density modification during RF operation. Here we present a self consistent description of the nonlinear ponderomotive force in the antenna near field region, via coupling a 1D field aligned transport model with a 1D cold plasma wave model. Results are presented, which show a parallel electric field of 300 Vm -1 drove a density reduction of ~ 20% over 25 RF periods.

Barnett, Rhea↗
DOE OSTI2019

Accurate Density Calculation for Molten Slags in SiO{sub 2}-Al{sub 2}O{sub 3}-CaO-MgO-‘FeO’-‘Fe{sub 2}O{sub 3}’ Systems

A simple and accurate density calculation model for molten slags containing iron oxides in SiO{sub 2}-Al{sub 2}O{sub 3}-CaO-MgO-‘FeO’-‘Fe{sub 2}O{sub 3}’ systems is established in the present study, by extending a previous model developed for SiO{sub 2}-Al{sub 2}O{sub 3}-CaO-MgO systems. To quantitate the iron oxides in slags, a new method is proposed to recalculate all the iron oxides as ‘FeO’ and ‘Fe{sub 2}O{sub 3},’ which represent the iron oxides in equilibrium with metallic iron and the air atmosphere, respectively. This method is essentially different from most of the other models that dealt with ferrous (FeO) and ferric (Fe{sub 2}O{sub 3}) iron oxides. A total of 860 experimental data points for iron oxide-containing melts are critically collected for the optimization of the model parameters. The model achieves an excellent agreement with literature values with an average error of 1.96 pct and an overall absolute error of 0.092 g/cm{sup 3}. The compositional dependences from unary to multicomponent systems are discussed using the present model. The results show that the densities always increase with the increasing ‘FeO’ or ‘Fe{sub 2}O{sub 3},’ and the substitution of ‘FeO’ by ‘Fe{sub 2}O{sub 3}’ will cause a decrease in density. In the multicomponent systems, SiO{sub 2} tends to have a larger impact on the density of ‘Fe{sub 2}O{sub 3}’-containing systems compared with ‘FeO’-containing systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

First-principles thermodynamic assessment of Sr-containing secondary phase formation in strontium-substituted lanthanum manganites for solid oxide cell applications

Sr-secondary phase formation is a potentially significant degradation mode with direct impact upon solid-oxide cell (SOC) commercial viability. A first-principles based thermodynamic study was performed for La 1−x Sr x MnO 3±δ (LSM) perovskites to assess their stability against formation of different Sr-secondary phases, including SrO, SrCrO 4 , SrSO 4 , SrCO 3 , and Sr(OH) 2 , for SOC applications. The Sr-secondary phase formation reaction free energies were determined via a thermodynamic model by combining ab initio lattice dynamics calculations for the solid phases and ab initio thermodynamic data for the gas phases. The current approach expands the previously reported thermodynamic modeling studies by integrating first-principles based point defect equilibria into the thermodynamic analysis. The modeling results obtained using this new approach indicate an increased tendency to form the SrO oxide upon decreasing the oxygen partial pressure. Additionally, the enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with the contaminant gas species as a function of temperature and pressure.

defect thermodynamics modeling↗
DOE OSTI2025

Comparison of removal and spatial mark‐resight models for estimating wild pig density

Density estimation is critical to effectively manage invasive species and elucidate areas of highest concern. For wild pigs (Sus scrofa), the ability to estimate density is complicated because of their variable home range sizes and social structure. Common methods for estimating density (e.g., mark-recapture) may be unsuitable in management applications because additional data needs to be collected before and after management. Removal models offer a suitable alternative to estimate density changes following management and can be applied broadly across areas where management of wild pigs is ongoing. We collected wild pig removal and camera trap data from 25 private properties ranging in size from approximately 0.5 km 2 to 95 km 2 across 3 ecoregions in South Carolina, USA, from 2020–2023. We compared factors affecting consistency and precision of property-level density estimates between removal and spatial mark-resight (SMR) models. In general, excluding 1 large outlier, density estimates from removal models were between 0.60 and 15.85 wild pigs/km 2 (median = 5.34) with a median coefficient of variation (CV) of 0.76 and 95% confidence intervals for the CV between 0.70 and 0.94. Similarly, excluding 1 large outlier, density estimates from SMR were between 0.22 and 30.97 wild pigs/km 2 (median = 5.48) with a median CV of 0.39 and 95% confidence intervals for the CV between 0.38 and 1.20. We found the precision of removal models was affected primarily by the number of wild pigs dispatched in the removal period (3 months) and the ecoregion in which they were removed. None of the covariates, including the number of recaptures (a corresponding measure of sample size), influenced precision of the SMR models, although recaptures did influence the density estimates. At the individual property level, density estimates from our 2 estimators were dissimilar from each other in approximately 80% of instances, although none of the covariates we examined influenced dissimilarity. Our results provide unique insight into how sample size affects density estimates using 2 common methods and into novel SMR models that incorporate both marked and unmarked detections. In addition, the density estimates in this study can be used as a reference for wild pig densities in common land cover types throughout the southeastern United States.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1998

Methods to Improve the Maintenance of the Earth Catalog of Satellites During Severe Solar Storms

The objective of this thesis is to investigate methods to improve the ability to maintain the inventory of orbital elements of Earth satellites during periods of atmospheric disturbance brought on by severe solar activity. Existing techniques do not account for such atmospheric dynamics, resulting in tracking errors of several seconds in predicted crossing time. Two techniques are examined to reduce of these tracking errors. First, density predicted from various atmospheric models is fit to the orbital decay rate for a number of satellites. An orbital decay model is then developed that could be used to reduce tracking errors by accounting for atmospheric changes. The second approach utilizes a Kalman filter to estimate the orbital decay rate of a satellite after every observation. The new information is used to predict the next observation. Results from the first approach demonstrated the feasibility of building an orbital decay model based on predicted atmospheric density. Correlation of atmospheric density to orbital decay was as high as 0.88. However, it is clear that contemporary: atmospheric models need further improvement in modeling density perturbations polar region brought on by solar activity. The second approach resulted in a dramatic reduction in tracking errors for certain satellites during severe solar Storms. For example, in the limited cases studied, the reduction in tracking errors ranged from 79 to 25 percent.

Wilkin, Paul G.↗
NASA NTRS1979

Empirical models of the electron temperature and density in the nightside Venus ionosphere

Empirical models of the electron temperature and density of the late afternoon and nightside Venus ionosphere based on the Pioneer Venus measurements are presented. They describe the ionosphere conditions near 18 deg latitude between 150 and 700 km altitude for solar zenith angles of 80 to 180 deg, with a 10-fold decrease beyond 90 deg and a gradual decrease between 120 and 180 deg. The nightside electron density profile, the ion transport process, and electron precipitation are discussed. The high nocturnal temperatures and the well defined nightside ionopause suggest that energetic processes occur across the top of the entire nightside ionosphere, maintaining elevated temperatures.

Brace, L. H.↗
DOE OSTI2018

A systems-level analysis of drought and density response in the model C4 grass Setaria viridis

The need for novel crops in an emerging bioenergy economy presents many challenges and opportunities for plant scientists. Plant breeding has been successful at transforming weedy species into some of the highest yielding crops on the planet. The plant domestication has led, in part, to an anticipated delivery of up to 1 billion dry tons of lignocellulosic feedstocks into the energy economy by 2030. However, The success of modern food crop breeding suggests that even greater advances can be made by developing the next generation of bioenergy feedstocks from C4 grass species that have been to date subjected to little or no breeding. The challenge we face is to exponentially accelerate the crop improvement process so that we can meet this level of bioenergy feedstock production. To achieve this unprecedented goal, it will be necessary to rapidly advance the process of plant breeding through large-scale biology, computational biology and systems approaches. Therefore, the goal of this proposal was to understand how productivity, drought tolerance and water use efficiency (WUE) are regulated at the genomic level in order to inform metabolic engineering and molecular-assisted breeding efforts.This necessitates the use of a model species that is closely related to less genetically tractable feedstock grasses such as Sorghum, switchgrass and Miscanthus. To achieve this we have significantly enhanced the utility of Setaria viridis as a model C4 species for system biology. This was achieved through field, greenhouse and laboratory experiments to survey a breadth of environments and explore the potential of gene networks to predict physiological responses across environments. We challenged plants under abiotic stresses to examine the plasticity of the network and identify targets for future manipulation. Finally, we have identified promising new gene engineering technologies to modify genetic networks in this model C4 species to understand and enhance abiotic stress tolerance. The outcomes of this project led to 1) identification of gene regulatory and metabolic networks important for adaptation to low water availability and high-density plantings, which lead to a greater understanding of the physiology underlying these adaptations and 2) we developed technologies to measure important water use efficiency traits and to precisely control gene insertion and replacements events for large scale engineering of pathways in model and target feedstocks.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Photoionization Modeling and the K Lines of Iron

We calculate the efficiency of iron K line emission and iron K absorption in photoionized models using a new set of atomic data. These data are more comprehensive than those previously applied to the modeling of iron K lines from photoionized gases, and allow us to systematically examine the behavior of the properties of line emission and absorption as a function of the ionization parameter, density and column density of model constant density clouds. We show that, for example, the net fluorescence yield for the highly charged ions is sensitive to the level population distribution produced by photoionization, and these yields are generally smaller than those predicted assuming the population is according to statistical weight. We demonstrate that the effects of the many strongly damped resonances below the K ionization thresholds conspire to smear the edge, thereby potentially affecting the astrophysical interpretation of absorption features in the 7-9 keV energy band. We show that the centroid of the ensemble of K(alpha) lines, the K(beta) energy, and the ratio of the K(alpha(sub 1)) to K(alpha(sub 2)) components are all diagnostics of the ionization parameter of our model slabs.

Kallman, T. R.↗
NASA NTRS1999

Semiempirical Two-Dimensional Magnetohydrodynamic Model of the Solar Corona and Interplanetary Medium

We have developed a two-dimensional semiempirical MHD model of the solar corona and solar wind. The model uses empirically derived electron density profiles from white-light coronagraph data measured during the Skylub period and an empirically derived model of the magnetic field which is fitted to observed streamer topologies, which also come from the white-light coronagraph data The electron density model comes from that developed by Guhathakurta and coworkers. The electron density model is extended into interplanetary space by using electron densities derived from the Ulysses plasma instrument. The model also requires an estimate of the solar wind velocity as a function of heliographic latitude and radial component of the magnetic field at 1 AU, both of which can be provided by the Ulysses spacecraft. The model makes estimates as a function of radial distance and latitude of various fluid parameters of the plasma such as flow velocity V, effective temperature T(sub eff), and effective heat flux q(sub eff), which are derived from the equations of conservation of mass, momentum, and energy, respectively. The term effective indicates that wave contributions could be present. The model naturally provides the spiral pattern of the magnetic field far from the Sun and an estimate of the large-scale surface magnetic field at the Sun, which we estimate to be approx. 12 - 15 G. The magnetic field model shows that the large-scale surface magnetic field is dominated by an octupole term. The model is a steady state calculation which makes the assumption of azimuthal symmetry and solves the various conservation equations in the rotating frame of the Sun. The conservation equations are integrated along the magnetic field direction in the rotating frame of the Sun, thus providing a nearly self-consistent calculation of the fluid parameters. The model makes a minimum number of assumptions about the physics of the solar corona and solar wind and should provide a very accurate empirical description of the solar corona and solar wind Once estimates of mass density rho, flow velocity V, effective temperature T(sub eff), effective heat flux q(sub eff), and magnetic field B are computed from the model and waves are assumed unimportant, all other plasma parameters such as Mach number, Alfven speed, gyrofrequency, etc. can be derived as a function of radial distance and latitude from the Sun. The model can be used as a planning tool for such missions as Slar Probe and provide an empirical framework for theoretical models of the solar corona and solar wind The model will be used to construct a semiempirical MHD description of the steady state solar corona and solar wind using the SOHO Large Angle Spectrometric Coronagraph (LASCO) polarized brightness white-light coronagraph data, SOHO Extreme Ultraviolet Imaging Telescope data, and Ulysses plasma data.

Sittler, Edward C., Jr.↗
DOE OSTI2024

The invisible black widow PSR J1720−0534: implications for the electron density towards the North Polar Spur

Radio emission from pulsars can be used to map out their distances through dispersion measure (DM), which quantifies the amount of radio pulse dispersion. However, this method relies on accurately modelling the free electron density in the line of sight. Here, we present a detailed study of the multiwavelength emission from PSR J1720−0534, a black widow compact binary millisecond pulsar discovered in 2021, which the latest electron density model of the Galaxy places at only 191 pc. We obtained and analysed deep multiwavelength observations in the γ-ray ( Fermi -Large Area Telescope, 2008–2022), optical (Las Cumbres Observatory, 2.7 h), near-infrared (Nordic Optical Telescope, 3.5 h), and X-ray ( Swift -X-Ray Telescope, 10 ks) bands. We found no significant detection of γ-ray, optical, near-infrared, or X-ray counterparts around the radio-timing position of PSR J1720−0534, which we thus nickname ‘the invisible black widow’. Employing the most constraining near-infrared limit ( J > 23.4 mag), we established a lower limit on the source distance, d > 1.1 kpc, assuming conservative properties for the black widow companion star. This distance lower limit differs drastically (by a factor of more than 5) from the Yao et al. DM distance estimate. We attribute this difference to the inclusion in the Yao et al. model of a large and dense component towards the North Polar Spur. Considering our results and recent parallax distances to other pulsars in this direction, we argue that such a local and large component in the electron density model of the Galaxy is unnecessary.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Entanglement in massive Schwinger model at finite temperature and density

We evaluate the entanglement entropy and entropic function of massive two dimensional quantum electrodynamics (Schwinger model) at finite temperature, density, and θ -angle. In the strong coupling regime, the entropic function is dominated by the boson mass for large spatial intervals, and reduces to the conformal field theory result for small spatial intervals. We also discuss the entanglement spectrum at finite temperature and a finite θ -angle. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Effective $\mathbb{Z}_{3}$ model for finite-density QCD with tensor networks

The tensor renormalization group is a promising numerical method used to study lattice statistical field theories. However, this approach is computationally expensive in 2+1 and 3+1 dimensions. Here we use tensor renormalization group methods to study an effective three-dimensional $\mathbb{Z}_{3}$ model for the heavy-quark, high-temperature, strong-coupling limit of single-flavor 3+1 dimensional quantum chromodynamics. Our results are cross-checked using the worm Monte Carlo algorithm. We present the phase diagram of the model through the measurement of the Polyakov loop, the nearest-neighbor Polyakov loop correlator, and their susceptibilities. The tensor renormalization group results are in good agreement with the literature

Bloch, Jacques↗
DOE OSTI2022

Entanglement, partial set of measurements, and diagonality of the density matrix in the parton model

To study quantum properties of the hadron wavefunction at small x, we derived the reduced density matrix for soft gluons in the CGC framework. We explicitly showed that the reduced density matrix is not diagonal in the particle number basis. The off-diagonal components are usually ignored in the conventional parton model. We thus defined the density matrix of ignorance by keeping only the part of the reduced density matrix which can be probed in a limited set of experimental measurements. We calculated Von Neumann entropy for both the reduced and ignorance density matrices. The entropy of ignorance is always greater than the entanglement entropy (computed drom the reduced density matrix) of gluons. Finally, we showed that the CGC reduced density matrix for soft gluons can be diagonalized in a thermal basis with Boltzmann weights suggesting thermalization of new quasi-particle states which we dubbed entangolons.

Duan, Haowu↗