Lattice Boltzmann models for the convection-diffusion equation: D2Q5 vs D2Q9
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To compare 6 diffusion-weighted imaging (DWI) MRI models for response evaluation in patients with pancreatic ductal adenocarcinoma (PDAC).
In this work, we develop models for the gettering of metals in silicon by high phosphorus concentration. We first performed ab initio calculations to determine favorable configurations of complexes involving phosphorus and transition metals (Fe, Cu, Cr, Ni, Ti, Mo, and W). Our ab initio calculations found that the P{sub 4}V cluster, a vacancy surrounded by 4 nearest-neighbor phosphorus atoms, which is the most favorable inactive P species in heavily doped Si, strongly binds metals such as Cu, Cr, Ni, and Fe. Based on the calculated binding energies, we build continuum models to describe the P deactivation and Fe gettering processes with model parameters calibrated against experimental data. In contrast to previous models assuming metal-P{sub 1}V or metal-P{sub 2}V as the gettered species, the binding of metals to P{sub 4}V satisfactorily explains the experimentally observed strong gettering behavior at high phosphorus concentrations.
Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. Here, we introduce a new fractional operator characterized by a doubly-variable fractional order and possibly truncated interactions. Under certain conditions on the model parameters and on the regularity of the fractional order we show that the corresponding Poisson problem is well-posed. Additionally, we introduce a finite element discretization and describe an efficient implementation of the finite-element matrix assembly in the case of piecewise constant fractional order. Through several numerical tests, we illustrate the improved descriptive power of this new operator across media interfaces. Furthermore, we present one-dimensional and two-dimensional h-convergence results that show that the variable-order model has the same convergence behavior as the constant-order model.
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.
The energy balance in the lower transition region is analyzed by constructing theoretical models which satisfy the energy balance constraint. The energy balance is achieved by balancing the radiative losses and the energy flowing downward from the corona. This energy flow is mainly in two forms: conductive heat flow and hydrogen ionization energy flow due to ambipolar diffusion. Hydrostatic equilibrium is assumed, and, in a first calculation, local mechanical heating and Joule heating are ignored. In a second model, some mechanical heating compatible with chromospheric energy-balance calculations is introduced. The models are computed for a partial non-LTE approach in which radiation departs strongly from LTE but particles depart from Maxwellian distributions only to first order. The results, which apply to cases where the magnetic field is either absent, or uniform and vertical, are compared with the observed Lyman lines and continuum from the average quiet sun. The approximate agreement suggests that this type of model can roughly explain the observed intensities in a physically meaningful way, assuming only a few free parameters specified as chromospheric boundary conditions.
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)
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.
Gaseous purge is commonly used in sensitive spacecraft optical or electronic instruments to prevent infiltration of contaminants and/or water vapor. Typically, purge is sized using simplistic zero-dimensional models that do not take into account instrument geometry, surface effects, and the dependence of diffusive flux on the concentration gradient. For this reason, an axisymmetric computational fluid dynamics (CFD) simulation was recently developed to model contaminant infiltration and removal by purge. The solver uses a combined Navier-Stokes and Advection-Diffusion approach. In this talk, we report on updates in the model, namely inclusion of a particulate transport model.
Recent satellite observations of the distribution of galactic 100-MeV gamma rays and their interpretation are used as an independent test of the existence and extent of a cosmic-ray halo around the Galaxy. The cosmic-ray halo is defined, uniform and diffusion halo models are described, and the flat diffusion model is employed to investigate the effect of a diffusion halo on the galactic cosmic-ray distribution. Cosmic-ray source distributions that are perpendicularly uniform functions of galactocentric distance are adopted in the analysis. Possible longitudinal distributions of the gamma-ray line flux from neutral-pion decay are evaluated and compared with the fluxes observed by SAS-2 for goodness of fit. The results are shown to be consistent with a thick-disk or thin-halo model having a mean half-thickness of 1 to 3 kpc.
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.
The effects of gravity on methane diffusion flames were studied using a finite difference numerical model. Variables under consideration included velocity, pressure, temperature, enthalpy, reactive species, and inert carrier gas. Results obtained showed that flames in zero gravity were wider and taller than those in normal gravity. The use of a six reaction scheme produced similar predictions of flame width and height compared to those of the single reaction case. The numerical models predicted a considerable difference in the flame base region between normal gravity and low gravity. This region is considered to be beyond the boundaries of current analytical models.
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.
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.
A new frequency domain hot-electron bolometer (HEB) mixer model is described, which takes into account the non-uniform temperature distribution found in superconducting diffusion-cooled devices.
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.
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.