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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Smoothed particle hydrodynamics model for Landau-Lifshitz-Navier-Stokes and advection-diffusion equations

We propose a novel smoothed particle hydrodynamics (SPH) discretization of the fully coupled Landau-Lifshitz-Navier-Stokes (LLNS) and stochastic advection-diffusion equations. The accuracy of the SPH solution of the LLNS equations is demonstrated by comparing the scaling of velocity variance and the self-diffusion coefficient with kinetic temperature and particle mass obtained from the SPH simulations and analytical solutions. The spatial covariance of pressure and velocity fluctuations is found to be in a good agreement with theoretical models. To validate the accuracy of the SPH method for coupled LLNS and advection-diffusion equations, we simulate the interface between two miscible fluids. We study formation of the so-called “giant fluctuations” of the front between light and heavy fluids with and without gravity, where the light fluid lies on the top of the heavy fluid. We find that the power spectra of the simulated concentration field are in good agreement with the experiments and analytical solutions. In the absence of gravity, the power spectra decay as the power −4 of the wavenumber—except for small wavenumbers that diverge from this power law behavior due to the effect of finite domain size. Gravity suppresses the fluctuations, resulting in much weaker dependence of the power spectra on the wavenumber. Finally, the model is used to study the effect of thermal fluctuation on the Rayleigh-Taylor instability, an unstable dynamics of the front between a heavy fluid overlaying a light fluid. The front dynamics is shown to agree well with the analytical solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Simulation of fission gas diffusion in UO{sub 2} by vacancy clusters

The low solubility of fission gas in nuclear fuel leads to inter- and intra-granular bubbles. These bubbles affect performance of the fuel rod and increase the fuel temperature through the increase of porosity in the fuel pellets and decreased thermal conductivity across the pellet-clad gap as gas is released into the plenum. The nucleation, growth, and inter-connectivity of the fission gas bubbles ultimately depend on the diffusivity of gas atoms through the fuel matrix. Using mechanisms and data previously established from density functional theory (DFT) and empirical potential calculations, diffusion and reaction models have been derived for xenon atoms, uranium atoms, and vacancies in the substitutional and interstitial locations. Although similar to previous models, the diffusion and reaction rates have been re-derived in a more robust manner. Previous studies have under-predicted the experimentally observed diffusivity of xenon atoms in UO{sub 2}, however it has been previously shown that by including xenon atoms bound to two vacancies, the calculated diffusivity approaches the measured data. The derived model for species diffusion and inter-species reactions has been implemented in the MARMOT phase-field code in a modular structure so as to capture the enhanced diffusion of xenon due to bound gas + vacancy-cluster movement. The MARMOT code allows for the diffusion, reaction, and source rates to be solved simultaneously, resulting in steady state or transient concentrations of each species, and ultimately the diffusion behavior of xenon atoms. By including the diffusion of clusters of different combinations of xenon and vacancies, the calculated diffusivity more closely captures the measured diffusivity of xenon when using preliminary parameters. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

The Nature of Electrochemical Delithiation of Li-Mg Alloy Electrodes: Neutron Computed Tomography and Modeling of Li Diffusion and Delithiation Phenomenon

Li-Mg alloys are promising as positive electrodes (anodes) for Li-ion batteries due to the high Li storage capacity and the relatively lower volume change during the lithiation/delithiation process. They also present a unique opportunity to image the Li distribution through the electrode thickness at various delithiation states. In this work, spatial distributions of Li in electrochemically delithiated Li-Mg alloy electrodes have been quantitatively determined using neutron tomography. Specifically, the Li concentration profiles along thickness direction are determined. A rigorous analytical model to quantify the diffusion-controlled delithiation, accompanied by phase transition and boundary movement, has also been developed to explain the delithiation mechanism. The analytical modeling scheme successfully predicted the Li concentration profiles which agreed well with the experimental data. It is demonstrated that during discharge Li is removed by diffusion through the solid solution Li-Mg phases and this proceeds with β→α phase transition and the associated phase boundary movement through the thickness of the electrode. This is also accompanied by electrode thinning due to the change in molar volume during delithiation. In conclusion, following the approaches developed here, one can develop a rigorous and quantitative understanding of electrochemical delithiation in electrodes of electrochemical cells, similar to that in the present Li-Mg electrodes.

25 ENERGY STORAGE↗
DOE OSTI2015

A hybrid pore‐scale and continuum‐scale model for solute diffusion, reaction, and biofilm development in porous media

Abstract It is a challenge to upscale solute transport in porous media for multispecies bio‐kinetic reactions because of incomplete mixing within the elementary volume and because biofilm growth can change porosity and affect pore‐scale flow and diffusion. To address this challenge, we present a hybrid model that couples pore‐scale subdomains to continuum‐scale subdomains. While the pore‐scale subdomains involving significant biofilm growth and reaction are simulated using pore‐scale equations, the other subdomains are simulated using continuum‐scale equations to save computational time. The pore‐scale and continuum‐scale subdomains are coupled using a mortar method to ensure continuity of solute concentration and flux at the interfaces. We present results for a simplified two‐dimensional system, neglect advection, and use dual Monod kinetics for solute utilization and biofilm growth. The results based on the hybrid model are consistent with the results based on a pore‐scale model for three test cases that cover a wide range of Damköhler (Da = reaction rate/diffusion rate) numbers for both homogeneous (spatially periodic) and heterogeneous pore structures. We compare results from the hybrid method with an upscaled continuum model and show that the latter is valid only for cases of small Damköhler numbers, consistent with other results reported in the literature.

Tang, Youneng↗
DOE OSTI2018

Modeling gas-diffusion electrodes for CO 2 reduction

CO 2 reduction conducted in electrochemical cells with planar electrodes immersed in an aqueous electrolyte is severely limited by mass transport across the hydrodynamic boundary layer. This limitation can be minimized by use of vapor-fed, gas-diffusion electrodes (GDEs), enabling current densities that are almost two orders of magnitude greater at the same applied cathode overpotential than what is achievable with planar electrodes in an aqueous electrolyte. The addition of porous cathode layers, however, introduces a number of parameters that need to be tuned in order to optimize the performance of the GDE cell. In this study, we develop a multiphysics model for gas diffusion electrodes for CO 2 reduction and used it to investigate the interplay between species transport and electrochemical reaction kinetics. The model demonstrates how the local environment near the catalyst layer, which is a function of the operating conditions, affects cell performance. Finally, we also examine the effects of catalyst layer hydrophobicity, loading, porosity, and electrolyte flowrate to help guide experimental design of vapor-fed CO 2 reduction cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Development of a diffusive wave shallow water model with a novel stability condition and other new features

Traditionally, one of the approaches to flood modelling is numerical simulation of the diffusive wave approximation of the shallow water equations. Improving these models in various aspects is still an open area of research. In this study, a new diffusive wave model with explicit time integration was developed which includes some novel features: (1) time steps are determined using a novel stability criterion which resulted in more dynamic time steps (i.e., broader range) compared to the conventional Courant-Friedrichs-Lewy stability condition; (2) stability constraints are reduced, considering the flow processes within surface ponds; (3) besides Manning's formula, which is the common equation for computing velocities in diffusive wave models, the free fall velocity and a new equation for wave-front velocity are employed; and (4) the influence of upstream surface ponds on downstream flow is considered. This paper introduces the enhanced diffusive wave model, the socalled Overland Flow Simulator Cellular Automata (OFS-CA), and its results for five test cases. Available analytical solutions and an experimental study were used for verification. Two other shallow water models were used for comparison and benchmarking. Overall, good agreements were observed and OFS-CA was computationally less expensive compared to the other two shallow water models.

42 ENGINEERING↗
DOE OSTI2016

Coarse-grained model of water diffusion and proton conductivity in hydrated polyelectrolyte membrane

Using dissipative particle dynamics (DPD), we simulate nanoscale segregation, water diffusion, and proton conductivity in hydrated sulfonated polystyrene (sPS). We employ a novel model [Lee et al. J. Chem. Theory Comput. 11(9), 4395-4403 (2015)] that incorporates protonation/deprotonation equilibria into DPD simulations. The polymer and water are modeled by coarse-grained beads interacting via short-range soft repulsion and smeared charge electrostatic potentials. The proton is introduced as a separate charged bead that forms dissociable Morse bonds with the base beads representing water and sulfonate anions. Morse bond formation and breakup artificially mimics the Grotthuss mechanism of proton hopping between the bases. The DPD model is parameterized by matching the proton mobility in bulk water, dissociation constant of benzenesulfonic acid, and liquid-liquid equilibrium of water-ethylbenzene solutions. The DPD simulations semi-quantitatively predict nanoscale segregation in the hydrated sPS into hydrophobic and hydrophilic subphases, water self-diffusion, and proton mobility. As the hydration level increases, the hydrophilic subphase exhibits a percolation transition from isolated water clusters to a 3D network. The analysis of hydrophilic subphase connectivity and water diffusion demonstrates the importance of the dynamic percolation effect of formation and breakup of temporary junctions between water clusters. The proposed DPD model qualitatively predicts the ratio of proton to water self-diffusion and its dependence on the hydration level that is in reasonable agreement with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Phase-field model for diffusion-induced grain boundary migration: An application to battery electrodes

Diffusion-induced grain boundary migration is a phenomenon in which a grain boundary moves in response to the driving forces generated by diffusing solute species. For example, diffusing solute species change the atomic volume in the host material, either by filling a vacancy with a misfitting solute atom or by expanding host lattices through interstitial diffusion. These volume changes are inhomogeneous and are stored as elastic energy in the material that drives grain boundaries. In this paper, we introduce our previously developed Cahn-Hilliard–phase-field-crystal model (CH-PFC) as a computational tool to investigate diffusion-induced grain boundary migration in crystalline materials. This multiscale phase-field model couples the composition field of a diffusing species with the crystallographic texture of a host material. We apply the CH-PFC model to battery electrodes and investigate whether interstitial solute diffusion induces grain growth in FePO 4 /LiFePO 4 electrodes. To this end, we compute grain growth in 60 FePO 4 electrodes by conducting two parallel trials: In the first trial, we cycle the electrode and calculate diffusion-induced grain growth. In the second trial, we do not cycle the electrode and calculate curvature-driven grain growth. We find a statistically significant grain growth in the cycled electrodes and negligible grain growth in the noncycled electrodes. Altogether, we show that the CH-PFC model not only predicts electrode microstructures as a function of the Li composition, but also predicts the crystallographic features of an electrode during battery operation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A quantitative study of the structure-activity relationship in hierarchical zeolites using liquid-phase reactions

Micro/meso/macroporous (hierarchical) zeolites show remarkable catalytic performance for reactions involving bulky reactants. However, quantitative assessment of the microstructural characteristics contributing to the observed performance remains elusive. Here, structure–activity relationships are established for a set of micro/mesoporous self-pillared pentasil (SPP) zeolites using two parallel liquid-phase reactions (benzyl alcohol alkylation and self-etherification) based on analysis of mass transport and reaction kinetics. A reaction–diffusion mathematical model is developed that quantitatively assigns the catalytic contributions of the external surface and micropores of SPP zeolites for these reactions. In addition, the effect of the zeolite external surface structure on the corresponding catalytic activity is quantitatively assessed by comparing SPP zeolites (with MFI structure) with MCM-22 (with MWW structure). This work demonstrates that reaction–diffusion modeling allows quantitative description of the catalytic performance of hierarchical zeolites and provides a model reaction to assess nm-sized characteristic diffusion lengths in MFI.

bio-inspired↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
DOE OSTI2012

Formation of silver nanoparticles inside a soda-lime glass matrix in the presence of a high intensity Ar{sup +} laser beam

Formation and motion of the silver nanoparticles inside an ion-exchanged soda-lime glass in the presence of a focused high intensity continuous wave Ar{sup +} laser beam (intensity: 9.2 x 10{sup 4} W/cm{sup 2}) have been studied in here. One-dimensional diffusion equation has been used to model the diffusion of the silver ions into the glass matrix, and a two-dimensional reverse diffusion model has been introduced to explain the motion of the silver clusters and their migration toward the glass surface in the presence of the laser beam. The results of the mentioned models were in agreement with our measurements on thickness of the ion-exchange layer by means of optical microscopy and recorded morphology of the glass surface around the laser beam axis by using a Mirau interferometer. SEM micrographs were used to extract the size distribution of the migrated silver particles over the glass surface.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advancing earth system model calibration: a diffusion-based method

Understanding of climate impact on ecosystems globally requires site-specific model calibration. Here we introduce a novel diffusion-based uncertainty quantification (DBUQ) method for efficient model calibration. DBUQ is a score-based diffusion model that leverages Monte Carlo simulation to estimate the score function and evaluates a simple neural network to quickly generate samples for approximating parameter posterior distributions. DBUQ is stable, efficient, and can effectively calibrate the model given diverse observations, thereby enabling rapid and site-specific model calibration on a global scale. This capability significantly advances Earth system modeling and our understanding of climate impacts on Earth systems. We demonstrate DBUQ's capability in E3SM land model calibration at the Missouri Ozark AmeriFlux forest site. Both synthetic and real-data applications indicate that DBUQ produces accurate parameter posterior distributions similar to those generated by Markov Chain Monte Carlo sampling but with 30X less computing time. This efficiency marks a significant stride in model calibration, paving the way for more effective and timely climate impact analyses.

Liu, Yanfang↗
DOE OSTI2012

Comparison of homogenized and enhanced diffusion solutions of model PWR problems

Model problem comparisons in slab geometry are made between two forms of homogenized diffusion theory and enhanced diffusion theory. The pin-cell discontinuity factors for homogenized diffusion calculations are derived from homogenized variational nodal P1 response matrices and from standard finite differencing. Enhanced diffusion theory consists of applying quasi-reflected interface conditions to reduce variational nodal Pn response matrices to one degree of freedom per interface, without homogenization within the cell. As expected both homogenized diffusion methods preserve reaction rates exactly if the discontinuity factors are derived from the P 11 reference solutions. If no reference lattice solution is available, discontinuity factors may be approximated from single cells with reflected boundary conditions; the computational effort is then comparable to calculating the enhanced diffusion response matrices. In this situation enhanced diffusion theory gives the most accurate results and finite difference discontinuity factors the least accurate. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Turbulent transport and mixing in transitional Rayleigh-Taylor unstable flow: A priori assessment of gradient-diffusion and similarity modeling

Data from a 1152×760×1280 direct numerical simulation of a Rayleigh-Taylor mixing layer modeled after a small-Atwood-number water-channel experiment is used to investigate the validity of gradient diffusion and similarity closures a priori. The budgets of the mean flow, turbulent kinetic energy, turbulent kinetic energy dissipation rate, heavy-fluid mass fraction variance, and heavy-fluid mass fraction variance dissipation rate transport equations across the mixing layer were previously analyzed at different evolution times to identify the most important transport and mixing mechanisms. Here a methodology is introduced to systematically estimate model coefficients as a function of time in the closures of the dynamically significant terms in the transport equations by minimizing the L2 norm of the difference between the model and correlations constructed using the simulation data. It is shown that gradient-diffusion and similarity closures used for the turbulent kinetic energy K, turbulent kinetic energy dissipation rate ε, heavy-fluid mass fraction variance S, and heavy-fluid mass fraction variance dissipation rate χ equations capture the shape of the exact, unclosed profiles well over the nonlinear and turbulent evolution regimes. Using order-of-magnitude estimates for the terms in the exact transport equations and their closure models, it is shown that several of the standard closures for the turbulent production and dissipation (destruction) must be modified to include Reynolds-number scalings appropriate for Rayleigh-Taylor flow at small to intermediate Reynolds numbers. The late-time, large Reynolds number coefficients are determined to be different from those used in shear flow applications and largely adopted in two-equation Reynolds-averaged Navier-Stokes (RANS) models of Rayleigh-Taylor turbulent mixing. In addition, it is shown that the predictions of the Boussinesq model for the Reynolds stress agree better with the data when additional buoyancy-related terms are included. It is shown that an unsteady RANS paradigm is needed to predict the transitional flow dynamics from early evolution times, analogous to the small Reynolds number modifications in RANS models of wall-bounded flows in which the production-to-dissipation ratio is far from equilibrium. Although the present study is specific to one particular flow and one set of initial conditions, the methodology could be applied to calibrations of other Rayleigh-Taylor flows with different initial conditions (which may give different results during the early-time, transitional flow stages, and perhaps asymptotic stage). Finally, the implications of these findings for developing high-fidelity eddy viscosity-based turbulent transport and mixing models of Rayleigh-Taylor turbulence are discussed.

42 ENGINEERING↗
DOE OSTI2020

Accelerated Modeling of Lithium Diffusion in Solid State Electrolytes using Artificial Neural Networks

Abstract Previous efforts to understand structure‐function relationships in high ionic conductivity materials for solid state batteries have predominantly relied on density functional theory (DFT‐) based ab initio molecular dynamics (MD). Such simulations, however, are computationally demanding and cannot be reasonably applied to large systems containing more than a hundred atoms. Here, an artificial neural network (ANN) is trained to accelerate the calculation of high accuracy atomic forces and energies used during such MD simulations. After carefully training a robust ANN for four and five element systems, nearly identical lithium ion diffusivities are obtained for Li 10 GeP 2 S 12 (LGPS) when benchmarking the ANN‐MD results with DFT‐MD. Applying the ANN‐MD approach, the effect of chlorine doping on the lithium diffusivity is calculated in an LGPS‐like structure and it is found that a dopant concentration of 1.3% maximizes ionic conductivity. The optimal concentration balances the competing consequences of effective atomic radii and dielectric constants on lithium diffusion and agrees with the experimental composition. Performing simulations at the resolution necessary to model experimentally relevant and optimal concentrations would be infeasible with traditional DFT‐MD. Systems that require a large number of simulated atoms can be studied more efficiently while maintaining high accuracy with the proposed ANN‐MD framework.

Rao, Karun K.↗
DOE OSTI2011

Model of boron diffusion from gas phase in silicon carbide

Boron diffusion from the gas phase in silicon carbide is described on the basis of a two-component model. 'Shallow' boron, i.e., boron at silicon sites, is a slow component with a high surface concentration. Its diffusivity is proportional to the concentration of positively charged intrinsic point defects, which are presumably interstitial silicon atoms. 'Deep' boron, i.e., impurity-defect pairs of boron-carbon vacancy, is a fast component with lower surface concentration. The ratio between the surface concentrations of the components depends on the pressure of silicon or carbon vapors in the gas phase. The diffusion and interaction of components are described by the set of diffusion-reaction equations. The diffusion retardation observed on the concentration-profile tail is related to the capture of impurity-defect pairs and excess vacancies by traps of background impurities and defects.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Local structure of Rb{sub 2}Li{sub 4}(SeO{sub 4}){sub 3}{center_dot}2H{sub 2}O by the modeling of X-ray diffuse scattering - from average-structure to microdomain model

Local structure of dirubidium tetralithium tris(selenate(VI)) dihydrate - Rb{sub 2}Li{sub 4}(SeO{sub 4}){sub 3}{center_dot} 2H{sub 2}O has been determined basing on the modeling of X-ray diffuse scattering. The origin of observed structured diffuse streaks is SeO{sub 4} tetrahedra switching between two alternative positions in two quasi-planar layers existing in each unit cell and formation of domains with specific SeO{sub 4} tetrahedra configuration locally fulfilling condition for C-centering in the 2a Multiplication-Sign 2b Multiplication-Sign c superstructure cell. The local structure solution is characterized by a uniform distribution of rather large domains (ca. thousand of unit cells) in two layers, but also monodomains can be taken into account. Inside a single domain SeO{sub 4} tetrahedra are ordered along ab-diagonal forming two-string ribbons. Inside the ribbons SeO{sub 4} and LiO{sub 4} tetrahedra share the oxygen corners, whereas ribbons are bound to each other by a net of hydrogen bonds and fastened by corner sharing SeO{sub 4} tetrahedra of the neighboring layers. - Graphical abstract: Experimental sections of the reciprocal space showing diffraction effects observed for RLSO. Bragg spots are visible on sections with integer indices (1 kl section - on the left), streaks - on sections with fractional ones (1.5 kl section - on the right). At the center: resulting local structure of the A package modeled as a microdomain: two-string ribbons of ordered oxygen-corners-sharing SeO{sub 4} and LiO{sub 4} terahedra extended along ab-diagonal are seen; ribbons are bound by hydrogen bonds (shown in pink); the multiplied 2a Multiplication-Sign 2b unit cell is shown. Highlights: Black-Right-Pointing-Pointer X-ray diffuse scattering in RLSO was registered and modeled. Black-Right-Pointing-Pointer The origin of diffuse streaks is SeO{sub 4} tetrahedra switching in two structure layers. Black-Right-Pointing-Pointer The local structure is characterized by a uniform distribution of microdomains. Black-Right-Pointing-Pointer Inside a single domain SeO{sub 4} tetrahedra are ordered along ab-diagonal forming ribbons. Black-Right-Pointing-Pointer The ribbons are bound to each other by a net of hydrogen bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗