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Results for “Diffusion model”

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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Radiative diffusivity factors in cirrus and stratocumulus clouds: Application to two-stream models

A diffusion-like description of radiative transfer in clouds and the free atmosphere is often used. The two stream model is probably the best known example of such a description. The main idea behind the approach is that only the first few moments of radiance are needed to describe the radiative field correctly. Integration smooths details of the angular distribution of specific intensity and it is assumed that the closure parameters of the theory (diffusivity factors) are only weakly dependent on the distribution. The diffusivity factors are investigated using the results obtained from both Stratocumulus and Cirrus phases of FIRE experiment. A new theoretical framework is described in which two (upwards and downwards) diffusivity factors are used and a detailed multistream model is used to provide further insight about both the diffusivity factors and their dependence on scattering properties of clouds.

Stephens, Graeme L.↗
DOE OSTI2023

Influence of strong Coulomb coupling on diffusion in atmospheric pressure plasmas

Ion diffusion in atmospheric pressure plasmas is examined and particular attention is paid to the fact that ion–ion interactions can be influenced by strong Coulomb coupling. Three regimes are identified. At low ionization fractions (x i ≲ 10 —6 ), standard weakly correlated ion-neutral interactions set the diffusion rate. At moderate ionization fractions (10 —6 ≲ x i ≲ 10 —2 ) there is a transition from ion-neutral to ion–ion collisions setting the diffusion rate. In this regime, the effect of strong Coulomb coupling in ion–ion collisions is accounted for by applying the mean force kinetic theory. Since both ion-neutral and ion–ion interactions contribute a comparable amount to the total diffusion rate, models (such as particle-in-cell or fluid) must account for both contributions. At high ionization fractions (x i ≳ 10 —2 ), strongly correlated ion–ion collisions dominate and the plasma is heated substantially by a disorder-induced heating (DIH) process associated with strong correlations. The temperature increase due to DIH strongly influences the ion diffusion rate. This effect becomes even more important, and occurs at lower ionization fractions, as the pressure increases above atmospheric pressure. In addition to ion diffusion, DIH affects the neutral gas temperature, therefore influencing the neutral diffusion rate. Model predictions are tested using molecular dynamics simulations, which included a Monte Carlo collision routine to simulate the effect of ion-neutral collisions at the lowest ionization fractions. The model and simulations show good agreement over a broad range of ionization fractions. Importantly, the results provide a model for ion diffusion, on a wide range of ionization fractions and pressures, solely considering the elastic contribution to the diffusion coefficient—as an illustration of how strong Coulomb coupling influences diffusion processes in general.

fast neutral gas heating↗
NASA NTRS1987

Modeling and calculation of turbulent transport in free-shear flows

In this work the applicability of the combined bulk convection and gradient transport hypotheses for modeling turbulent diffusion is investigated. The resulting model equation, namely the one-equation model, is solved for free-shear flows by an implicit finite-difference method. Results indicate that significant improvements over previous models can be achieved with this new formulation of turbulent diffusion for both heat and momentum transport.

Biringen, S.↗
NASA NTRS1971

Numerical calculation of turbulent boundary layers including suction or injection with binary diffusion.

The modelling of turbulent transport processes with an eddy viscosity representation of the inner, wall region for cases with suction or injection is considered in detail. It is shown how the van Driest solid wall model can be logically extended for such cases. Further, a new inductive model is developed. Finite difference calculations using the new inductive model are shown to be in good agreement with experimental data over a wide range of conditions. Lastly, a new method for calculating the wall shear within a finite difference solution is developed. This procedure greatly relaxes the requirement for fine grid spacing in the vertical direction.

Schetz, J. A.↗
NASA NTRS1991

A computational model for the analysis of diffusive binary alloy solid/liquid phase change energy transport

A model is presented for the prediction of solid/liquid, binary alloy, phase change energy transport. The model incorporates only one-dimensional, diffusive transport of both energy and species but is not inherently limited in any way to such a restriction. The model incorporates a previously developed algorithm for single constituent phase change energy transport and is applied to the energy transport as well as the species transport aspects of the problem. The model is applied to four example cooling problems and is shown to perform exceedingly well from an algorithmic point of view.

Schneider, G. E.↗
DOE OSTI2018

In Situ Observation of Calcium Aluminate Inclusions Dissolution into Steelmaking Slag

The dissolution rate of calcium aluminate inclusions in CaO-SiO{sub 2}-Al{sub 2}O{sub 3} slags has been studied using confocal scanning laser microscopy (CSLM) at elevated temperatures: 1773 K, 1823 K, and 1873 K (1500 °C, 1550 °C, and 1600 °C). The inclusion particles used in this experimental work were produced in our laboratory and their production technique is explained in detail. Even though the particles had irregular shapes, there was no rotation observed. Further, the total dissolution time decreased with increasing temperature and decreasing SiO{sub 2} content in the slag. The rate limiting steps are discussed in terms of shrinking core models and diffusion into a stagnant fluid model. It is shown that the rate limiting step for dissolution is mass transfer in the slag at 1823 K and 1873 K (1550 °C and 1600 °C). Further investigations are required to determine the dissolution mechanism at 1773 K (1500 °C). The calculated diffusion coefficients were inversely proportional to the slag viscosity and the obtained values for the systems studied ranged between 5.64 × 10{sup −12} and 5.8 × 10{sup −10} m{sup 2}/s.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Realistic galaxy image simulation via score-based generative models

ABSTRACT We show that a denoising diffusion probabilistic model (DDPM), a class of score-based generative model, can be used to produce realistic mock images that mimic observations of galaxies. Our method is tested with Dark Energy Spectroscopic Instrument (DESI) grz imaging of galaxies from the Photometry and Rotation curve OBservations from Extragalactic Surveys (PROBES) sample and galaxies selected from the Sloan Digital Sky Survey. Subjectively, the generated galaxies are highly realistic when compared with samples from the real data set. We quantify the similarity by borrowing from the deep generative learning literature, using the ‘Fréchet inception distance’ to test for subjective and morphological similarity. We also introduce the ‘synthetic galaxy distance’ metric to compare the emergent physical properties (such as total magnitude, colour, and half-light radius) of a ground truth parent and synthesized child data set. We argue that the DDPM approach produces sharper and more realistic images than other generative methods such as adversarial networks (with the downside of more costly inference), and could be used to produce large samples of synthetic observations tailored to a specific imaging survey. We demonstrate two potential uses of the DDPM: (1) accurate inpainting of occluded data, such as satellite trails, and (2) domain transfer, where new input images can be processed to mimic the properties of the DDPM training set. Here we ‘DESI-fy’ cartoon images as a proof of concept for domain transfer. Finally, we suggest potential applications for score-based approaches that could motivate further research on this topic within the astronomical community.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Non-Linear Langevin and Fractional Fokker–Planck Equations for Anomalous Diffusion by Lévy Stable Processes

The numerical solutions to a non-linear Fractional Fokker–Planck (FFP) equation are studied estimating the generalized diffusion coefficients. The aim is to model anomalous diffusion using an FFP description with fractional velocity derivatives and Langevin dynamics where Lévy fluctuations are introduced to model the effect of non-local transport due to fractional diffusion in velocity space. Distribution functions are found using numerical means for varying degrees of fractionality of the stable Lévy distribution as solutions to the FFP equation. The statistical properties of the distribution functions are assessed by a generalized normalized expectation measure and entropy and modified transport coefficient. The transport coefficient significantly increases with decreasing fractality which is corroborated by analysis of experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Multilayer interface tracking model of pure tungsten oxidation

Here, we present a numerical model to predict oxide scale growth on tungsten surfaces under exposure to oxygen at high temperatures. The model captures the formation of four thermodynamically-compatible oxide sublayers, WO 2 , WO 2.72 , WO 2.9 , and WO 3 , on top of the metal substrate. Oxide layer growth is simulated by tracking the oxide/oxide and oxide/metal interfaces using a sharp-interface Stefan model coupled to diffusion kinetics. The model is parameterized using selected experimental measurements and electronic structure calculations of the diffusivities of all the oxide subphases involved. We simulate oxide growth at temperatures of 600°C and above, extracting the power law growth exponents in each case, which we find to deviate from classical parabolic growth in several cases. We conduct a comparison of the model predictions with an extensive experimental data set, with reasonable agreement at most temperatures. While many gaps in our understanding still exist, this work is a first attempt at embedding the thermodynamic and kinetic complexity of tungsten oxide growth into a comprehensive mesoscale kinetic model that attempts to capture the essential features of tungsten oxidation to fill existing knowledge gaps and guide and enhance future tungsten oxidation models.

36 MATERIALS SCIENCE↗
NASA NTRS2024

NASA HECC Geometry and Performance Review Part 1: Validation of a Computational Model for the Vaneless Diffuser Configuration with As-Manufactured Impeller Geometry

An investigation of the NASA High Efficiency Centrifugal Compressor (HECC) vaneless diffuser configuration was performed. This multipart investigation presents an extensive validation of the computational model against experimental data. The validated model was then used to explore the effects geometric differences between the as-manufactured and design-intent impellers. Lastly, the validated model was used for comparison against an experimental tip clearance study. Part I of the investigation focused on describing the HECC vaneless computational model and its validation against the experimental data published in GT2023-103128. To generate the model, a verification of the manufactured impeller was performed and was confirmed to match the impeller CAD. Section data from the impeller CAD, referred to as the As-Manufactured geometry, were used for development of the computational model. Steady RANS simulations utilizing the Wilcox K-Omega 98 turbulence model and a multiblock structured mesh were used to conduct a mesh convergence study. The resultant mesh was then used for simulations at both design-speed and off-design speed conditions. The simulations compared well to data in both 1D and 2D terms for the major performance metrics of efficiency, total pressure rise, and total temperature rise. Based on the observed results the model was deemed validated and was used in the latter two parts of the multipart investigation.

centrifugal compressor↗
NASA NTRS1974

Analysis of chromatograph systems using orthogonal collocation

Research is generating fundamental engineering design techniques and concepts for the chromatographic separator of a chemical analysis system for an unmanned, Martian roving vehicle. A chromatograph model is developed which incorporates previously neglected transport mechanisms. The numerical technique of orthogonal collocation is studied. To establish the utility of the method, three models of increasing complexity are considered, the latter two being limiting cases of the derived model: (1) a simple, diffusion-convection model; (2) a rate of adsorption limited, inter-intraparticle model; and (3) an inter-intraparticle model with negligible mass transfer resistance.

Woodrow, P. T.↗
NASA NTRS2007

Observations of the Li, Be, and B Isotopes and Constraints on Cosmic-ray Propagation

The abundance of Li, Be, and B isotopes in galactic cosmic rays (GCR) between E=50-200 MeV/nucleon has been observed by the Cosmic Ray Isotope Spectrometer (CRIS) on NASA's ACE mission since 1997 with high statistical accuracy. Precise observations of Li, Be, B can be used to constrain GCR propagation models. We find that a diffusive reacceleration model with parameters that best match CRIS results (e.g. B/C, Li/C, etc) are also consistent with other GCR observations. A approx. 15-20% overproduction of Li and Be in the model predictions is attributed to uncertainties in the production cross-section data. The latter becomes a significant limitation to the study of rare GCR species that are generated predominantly via spallation.

deNolfo, G. A.↗
NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗
NASA NTRS1978

The effect of nonlinear diffusive heat transport in a simple climate model

The effects of nonlinear diffusive heat transport in North's (1975) model is reexamined. By inserting the nonlinearity into the original energy balance equation rather than the spectrally transformed linear algebraic equations, and including one more mode in the spectral expansion, it is found that nonlinear diffusion does give a significantly different sensitivity for states near the current climate. For linear diffusion, an increase of 0.1% of the solar constant from the present value is sufficient to melt all the ice on the earth, whereas an increase of about five times as large is required for nonlinear diffusion. This difference in sensitivity shows the importance of dynamical modeling in simple climate models.

Lin, C. A.↗
NASA NTRS1993

Simulations of diffusion-reaction equations with implications to turbulent combustion modeling

An enhanced diffusion-reaction reaction system (DRS) is proposed as a statistical model for the evolution of multiple scalars undergoing mixing and reaction in an isotropic turbulence field. The DRS model is close enough to the scalar equations in a reacting flow that other statistical models of turbulent mixing that decouple the velocity field from scalar mixing and reaction (e.g. mapping closure model, assumed-pdf models) cannot distinguish the model equations from the original equations. Numerical simulations of DRS are performed for three scalars evolving from non-premixed initial conditions. A simple one-step reversible reaction is considered. The data from the simulations are used (1) to study the effect of chemical conversion on the evolution of scalar statistics, and (2) to evaluate other models (mapping-closure model, assumed multivariate beta-pdf model).

Girimaji, Sharath S.↗
DOE OSTI2021

Understanding copper diffusion in CuInSe 2 with first-principles based atomistic and continuum models

We investigate the diffusion of copper in CuInSe 2 using thermodynamic and kinetic models based on density functional theory calculations, attempting to reconcile large differences in reported experimental diffusivities. We find that observations of rapid chemical diffusion can be explained by large thermodynamic factors, which we calculate using a compositionally constrained model of intrinsic point defect formation. We further characterize how copper diffusion coefficients depend on material synthesis conditions and exhibit their variation across the CuInSe 2 secondary phase diagram. In doing so, we identify stable off-stoichiometries that are dominated by either vacancy- or interstitial-mediated diffusion mechanisms. These results are employed in the development of a continuum reaction–diffusion model, which we use to simulate experimental depth profiles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗