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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

AN INTEGRATED MODEL FOR THE PRODUCTION OF X-RAY TIME LAGS AND QUIESCENT SPECTRA FROM HOMOGENEOUS AND INHOMOGENEOUS BLACK HOLE ACCRETION CORONAE

Many accreting black holes manifest time lags during outbursts, in which the hard Fourier component typically lags behind the soft component. Despite decades of observations of this phenomenon, the underlying physical explanation for the time lags has remained elusive, although there are suggestions that Compton reverberation plays an important role. However, the lack of analytical solutions has hindered the interpretation of the available data. In this paper, we investigate the generation of X-ray time lags in Compton scattering coronae using a new mathematical approach based on analysis of the Fourier-transformed transport equation. By solving this equation, we obtain the Fourier transform of the radiation Green’s function, which allows us to calculate the exact dependence of the time lags on the Fourier frequency, for both homogeneous and inhomogeneous coronal clouds. We use the new formalism to explore a variety of injection scenarios, including both monochromatic and broadband (bremsstrahlung) seed photon injection. We show that our model can successfully reproduce both the observed time lags and the time-averaged (quiescent) X-ray spectra for Cyg X-1 and GX 339-04, using a single set of coronal parameters for each source. The time lags are the result of impulsive bremsstrahlung injection occurring near the outer edge of the corona, while the time-averaged spectra are the result of continual distributed injection of soft photons throughout the cloud.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Y-type Brown Dwarfs: Estimates of Mass and Age from New Astrometry, Homogenized Photometry, and Near-infrared Spectroscopy

The survey of the mid-infrared sky by the Wide-field Infrared Survey Explorer ( WISE ) led to the discovery of extremely cold, low-mass brown dwarfs, classified as Y dwarfs, which extend the T class to lower temperatures. Twenty-four Y dwarfs are known at the time of writing. Here we present improved parallaxes for four of these, determined using Spitzer images. We give new photometry for four late-type T and three Y dwarfs and new spectra of three Y dwarfs, obtained at Gemini Observatory. We also present previously unpublished photometry taken from HST , ESO, Spitzer , and WISE archives of 11 late-type T and 9 Y dwarfs. The near-infrared data are put onto the same photometric system, forming a homogeneous data set for the coolest brown dwarfs. We compare recent models to our photometric and spectroscopic data set. We confirm that nonequilibrium atmospheric chemistry is important for these objects. Nonequilibrium cloud-free models reproduce well the near-infrared spectra and mid-infrared photometry for the warmer Y dwarfs with 425 ≤ T {sub eff} (K) ≤ 450. A small amount of cloud cover may improve the model fits in the near-infrared for the Y dwarfs with 325 ≤ T {sub eff} (K) ≤ 375. Neither cloudy nor cloud-free models reproduce the near-infrared photometry for the T {sub eff} = 250 K Y dwarf W0855. We use the mid-infrared region, where most of the flux originates, to constrain our models of W0855. We find that W0855 likely has a mass of 1.5–8 Jupiter masses and an age of 0.3–6 Gyr. The Y dwarfs with measured parallaxes are within 20 pc of the Sun and have tangential velocities typical of the thin disk. The metallicities and ages we derive for the sample are generally solar-like. We estimate that the known Y dwarfs are 3 to 20 Jupiter-mass objects with ages of 0.6–8.5 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Mechanism for the Efficient Homogeneous Nucleation of Ice in a Weakly Ionized, Ultracold Plasma

Abstract It is proposed that the rapid observed homogeneous nucleation of ice dust in a cold, weakly ionized plasma depends on the formation of hydroxide (OH − ) by fast electrons impacting water molecules. These OH − ions attract neutral water molecules because of the high dipole moment of the water molecules and so hydrates of the form (OH) − (H 2 O) n are formed. The hydrates continuously grow in the cold environment to become macroscopic ice grains. These ice grains are negatively charged as a result of electron impact and so continue to attract water molecules. Because hydroxide is a negative ion, unlike positive ions, it does not suffer recombination loss from collision with plasma electrons. Recombination with positive ions is minimal because positive ions are few in number (weak ionization) and slow-moving as result of being in thermal equilibrium with the cold background gas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Diffusional growth of cloud droplets in homogeneous isotropic turbulence: DNS, scaled-up DNS, and stochastic model

This paper presents a novel methodology to use direct numerical simulation (DNS) to study the impact of isotropic homogeneous turbulence on the condensational growth of cloud droplets. As shown by previous DNS studies, the impact of turbulence increases with the computational domain size, that is, with the Reynolds number, because larger eddies generate higher and longer-lasting supersaturation fluctuations that affect growth of individual cloud droplets. The traditional DNS can only simulate a limited range of scales because of the excessive computational cost that comes from resolving all scales involved, that is, from large scales at which the turbulent kinetic energy (TKE) is introduced down to the Kolmogorov microscale, and from following every single droplet. The novel approach is referred to as the “scaled-up DNS”. The scaling up is done in two parts, first by increasing both the computational domain and the Kolmogorov microscale and second by using super-droplets instead of real droplets. To ensure proper dissipation of TKE and scalar variance at small scales, molecular transport coefficients are appropriately scaled up with the grid length. For the scaled-up domains, say, meters and tens of meters, one needs to follow billions of real droplets. This is not computationally feasible, and so-called super-droplets are applied in scaled-up DNS simulations. Each super-droplet represents an ensemble of identical real droplets, and the number of real droplets represented by a super-droplet is referred to as the multiplicity attribute. After simple tests showing the validity of the methodology, scaled-up DNS simulations are conducted for five domains, the largest of 64 3 m 3 volume using a DNS of 256 3 grid points and various multiplicities. All simulations are carried out with vanishing mean vertical velocity and with no mean supersaturation, similarly to past DNS studies. As expected, the supersaturation fluctuations as well as the spread in droplet size distribution increase with the domain size, with the droplet radius variance increasing in time t as t 1∕2 as identified in previous DNS studies. Scaled-up simulations with different multiplicities document numerical convergence of the scaled-up solutions. Finally, we compare the scaled-up DNS results with a simple stochastic model that calculates supersaturation fluctuations based on the vertical velocity fluctuations updated using the Langevin equation. Overall, the results document similar scaling to previous small-domain DNS simulations and support the notion that the stochastic subgrid-scale model is a valuable tool for the multi-scale simulation of droplet spectral evolution applying a large-eddy simulation model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cloud droplet diffusional growth in homogeneous isotropic turbulence: bin microphysics versus Lagrangian super-droplet simulations

The increase in the spectral width of an initially monodisperse population of cloud droplets in homogeneous isotropic turbulence is investigated by applying a finite-difference fluid flow model combined with either Eulerian bin microphysics or a Lagrangian particle-based scheme. The turbulence is forced applying a variant of the so-called linear forcing method that maintains the mean turbulent kinetic energy (TKE) and the TKE partitioning between velocity components. The latter is important for maintaining the quasi-steady forcing of the supersaturation fluctuations that drive the increase in the spectral width. We apply a large computational domain (64 3 m 3 ), one of the domains considered in Thomas et al. (2020). The simulations apply 1 m grid length and are in the spirit of the implicit large eddy simulation (ILES), that is, with small-scale dissipation provided by the model numerics. This is in contrast to the scaled-up direct numerical simulation (DNS) applied in Thomas et al. (2020). Two TKE intensities and three different droplet concentrations are considered. Analytic solutions derived in Sardina et al. (2015), valid for the case when the turbulence integral timescale is much larger than the droplet phase relaxation timescale, are used to guide the comparison between the two microphysics simulation techniques. The Lagrangian approach reproduces the scalings relatively well. Representing the spectral width increase in time is more challenging for the bin microphysics because appropriately high resolution in the bin space is needed. The bin width of 0.5 µm is only sufficient for the lowest droplet concentration (26 cm -3 ). For the highest droplet concentration (650 cm -3 ), an order of magnitude smaller bin size is barely sufficient. The scalings are not expected to be valid for the lowest droplet concentration and the high-TKE case, and the two microphysics schemes represent similar departures. Finally, because the fluid flow is the same for all simulations featuring either low or high TKE, one can compare point-by-point simulation results. Such a comparison shows very close temperature and water vapor point-by-point values across the computational domain and larger differences between simulated mean droplet radii and spectral width. The latter are explained by fundamental differences in the two simulation methodologies, numerical diffusion in the Eulerian bin approach and a relatively small number of Lagrangian particles that are used in the particle-based microphysics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1966

Stationary device produces homogeneous mixture of fluids

Stationary device produces a homogeneous mixture of two or more one-phase or two-phase fluids. The device contains two concentric flow guides with helical passageways through which the fluids are forced into turbulent flow by the system pressure differential.

Baker, D. I.↗