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At least 973 records · Page 54

Subgrid-Scale Mixing in Climate Models: A Novel Look at Diffusion, Accuracy, Stability and Climate Sensitivity

This project focuses on evaluating the role of subgrid-scale dissipation in the dynamical core of atmospheric models. All dynamical cores of atmospheric general circulation models (GCMs) employ some form of subgrid-scale dissipation, either explicitly specified or inherent in the chosen numerical schemes. The dissipation processes are needed to keep the simulation stable or to satisfy important physical properties, and the hope is that they capture and mimic in some poorly understood way the true processes at the unresolved subgrid scale. There is no physical basis that such dissipation can accomplish this. We originally posed a set of numerical test cases chosen or designed to isolate the role of the filters and fixers on both the dynamical variables (pressure, temperature, velocity, vorticity) and trace constituents. From these test case results, we synthesize the information to determine the impact of the subgrid-scale assumptions on weather and climate models.

54 ENVIRONMENTAL SCIENCES↗

A regularized deconvolution method for turbulent closure modeling in implicitly filtered large-eddy simulation

Turbulence closure models that are based on a regularized deconvolution method (RDM) are proposed for application to implicitly filtered Large-Eddy Simulation (LES). This method reconstructs sub-grid scale contributions by approximately recovering filtered quantities through an optimization approach. Physical principles on the boundedness and conservation of reconstructed quantities are preserved by constraining the optimization problem. Further, to account for effects of scales that are not resolved in implicitly filtered LES, a reconstruction method is proposed that combines sub-grid projection and energy-similarity to enrich unresolved scales. With this method, closure models are developed for turbulent scalar fluxes and turbulence–chemistry interaction that are intrinsically consistent with the LES formulation. These closure models are evaluated in application to a piloted turbulent jet flame with inhomogeneous inlet composition, in which combustion is represented by a two-scalar manifold model. The RDM-formulation is benchmarked against simulations obtained using a presumed PDF method and eddy diffusivity closure model. In partially-premixed flame regions, it is observed that RDM improves the prediction of turbulent mixing, and faster grid convergence is observed for results with RDM compared to simulations employing a presumed PDF method.

42 ENGINEERING↗

Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices

Variance-based sensitivity analysis provides a quantitative measure of how uncertainty in a model input contributes to uncertainty in the model output. Such sensitivity analyses arise in a wide variety of applications and are typically computed using Monte Carlo estimation, but the many samples required for Monte Carlo to be sufficiently accurate can make these analyses intractable when the model is expensive. This paper presents a multifidelity approach for estimating sensitivity indices that leverages cheaper low-fidelity models to reduce the cost of sensitivity analysis while retaining accuracy guarantees via recourse to the original, expensive model. This paper develops new multifidelity estimators for variance and for the Sobol' main and total effect sensitivity indices. We discuss strategies for dividing limited computational resources among models and specify a recommended strategy. Results are presented for the Ishigami function and a convection-diffusion-reaction model that demonstrate up to $10\times$ speedups for fixed convergence levels. Finally, for the problems tested, the multifidelity approach allows inputs to be definitively ranked in importance when Monte Carlo alone fails to do so.

97 MATHEMATICS AND COMPUTING↗

Quentin Faure Internship Report

During the internship, the student has studied and modeled hydrogen diffusion, desorption, and adsorption in ZrH and YH using Bison. The student will move towards coupling the model developed in Bison for hydrogen migration to the neutronic response obtained from Griffin for the unit cell of a prototypical microreactor. Due to the length of the report being short, only a small part of the YH modeling is being presented here.

36 MATERIALS SCIENCE↗

Atomistic modeling of metal–nonmetal interphase boundary diffusion

Atomistic computer simulations are applied to investigate the atomic structure, thermal stability, and diffusion processes in Al–Si interphase boundaries as a prototype of metal–ceramic interfaces in composite materials. Some of the most stable orientation relationships between the phases found in this work were previously observed in epitaxy experiments. Here, a non-equilibrium interface can transform to a more stable state by a mechanism that we call interface-induced recrystallization. Diffusion of both Al and Si atoms in stable Al–Si interfaces is surprisingly slow compared with diffusion of both elements in Al grain boundaries but can be accelerated in the presence of interface disconnections. A qualitative explanation of the sluggish interphase boundary diffusion is proposed. Atomic mechanisms of interphase boundary diffusion are similar to those in metallic grain boundaries and are dominated by correlated atomic rearrangements in the form of strings and rings of collectively moving atoms.

36 MATERIALS SCIENCE↗

NUCLEAR X-RAY PROPERTIES OF THE PECULIAR RADIO-LOUD HIDDEN AGN 4C+29.30

We present results from a study of nuclear emission from a nearby radio galaxy, 4C+29.30, over a broad 0.5-200 keV X-ray band. This study used new XMM-Newton ({approx}17 ks) and Chandra ({approx}300 ks) data, and archival Swift/BAT data from the 58 month catalog. The hard (>2 keV) X-ray spectrum of 4C+29.30 can be decomposed into an intrinsic hard power law ({Gamma} {approx} 1.56) modified by a cold absorber with an intrinsic column density N {sub H,z} {approx} 5 Multiplication-Sign 10{sup 23} cm{sup -2}, and its reflection (|{Omega}/2{pi}| {approx} 0.3) from a neutral matter including a narrow iron K{alpha} emission line at a rest-frame energy {approx}6.4 keV. The reflected component is less absorbed than the intrinsic one with an upper limit on the absorbing column of N {sup refl} {sub H,z} < 2.5 Multiplication-Sign 10{sup 22} cm{sup -2}. The X-ray spectrum varied between the XMM-Newton and Chandra observations. We show that a scenario invoking variations of the normalization of the power law is favored over a model with variable intrinsic column density. X-rays in the 0.5-2 keV band are dominated by diffuse emission modeled with a thermal bremsstrahlung component with temperature {approx}0.7 keV, and contain only a marginal contribution from the scattered power-law component. We hypothesize that 4C+29.30 belongs to a class of 'hidden' active galactic nuclei containing a geometrically thick torus. However, unlike the majority of hidden AGNs, 4C+29.30 is radio-loud. Correlations between the scattering fraction and Eddington luminosity ratio, and between black hole mass and stellar velocity dispersion, imply that 4C+29.30 hosts a black hole with {approx}10{sup 8} M {sub Sun} mass.

79 ASTRONOMY AND ASTROPHYSICS↗

MO-G-BRF-07: Anomalously Fast Diffusion of Carbon Nanotubes Carriers in 3D Tissue Model

Purpose: We aim to investigate and understand diffusion process of carbon nanotubes (CNTs) and other nanoscale particles in tissue and organs. Methods: In this research, we utilized a 3D model tissue of hepatocellular carcinoma (HCC)cultured in inverted colloidal crystal (ICC) scaffolds to compare the diffusivity of CNTs with small molecules such as Rhodamine and FITC in vitro, and further investigated the transportation of CNTs with and without targeting ligand, TGFβ1. The real-time permeation profiles of CNTs in HCC tissue model with high temporal and spatial resolution was demonstrated by using standard confocal microscopy. Quantitative analysis of the diffusion process in 3D was carried out using luminescence intensity in a series of Z-stack images obtained for different time points of the diffusion process after initial addition of CNTs or small molecules to the cell culture and the image data was analyzed by software ImageJ and Mathematica. Results: CNTs display diffusion rate in model tissues substantially faster than small molecules of the similar charge such as FITC, and the diffusion rate of CNTs are significantly enhanced with targeting ligand, TGFβ1. Conclusion: In terms of the advantages of in-vitro model, we were able to have access to measuring the rate of CNT penetration at designed conditions with variable parameters. And the findings by using this model, changed our understanding about advantages of CNTs as nanoscale drug carriers and provides design principles for making new drug carriers for both treatment and diagnostics. Additionally the fast diffusion opens the discussion of the best possible drug carriers to reach deep parts of cancerous tissues, which is often a prerequisite for successful cancer treatment. This work was supported by the Center for Photonic and Multiscale Nanomaterials funded by National Science Foundation Materials Research Science and Engineering Center program DMR 1120923. The work was also partially supported by NSF grant ECS-0601345; EFRI-BSBA 0938019; CBET 0933384; CBET 0932823; CBET 1036672, AFOSR MURI 444286-P061716 and NIH 1R21CA121841-01A2.

60 APPLIED LIFE SCIENCES↗

Reduced-order modeling of parameterized multi-group diffusion k-eigenvalue problems

In this paper, a group-wise Reduced-Order Model, based on a Proper Orthogonal Decomposition (POD) technique, is presented for parameterized multi-group diffusion k-eigenvalue problems. The group-wise approach is shown to be more robust than model-order reduction based on monolithic multi-group POD modes. In addition, fewer POD modes are required. The method of snapshots is employed to generate the offline training set. Two Naïve and a Greedy snapshot-generation strategies are compared. The input parameter space is surveyed using Latin Hypercube Sampling techniques. The effectiveness of the group-wise model-order reduction method is demonstrated on two reactor-physics benchmarks, a two-group 3D Pressurized Water Reactor problem with 26 uncertain input parameters and a seven-group UO 2 -MOX fuel 3D mini-core with 287 uncertain input parameters. In both examples the Reduced-Order Models built using the snapshots generated by the Greedy algorithm proved to be slightly better. Model-order reduction yields results that are within 1 pcm of the full-order model, with speed-up factors of about 1000–3000, depending upon the test case.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hydrophilic domain structure in polymer exchange membranes: Simulations of NMR spin diffusion experiments to address ability for model discrimination

Here, we detail the development of a flexible simulation program (NMR_DIFFSIM) that solves the nuclear magnetic resonance (NMR) spin diffusion equation for arbitrary polymer architectures. The program was used to explore the proton ( 1 H) NMR spin diffusion behavior predicted for a range of geometrical models describing polymer exchange membranes. These results were also directly compared with the NMR spin diffusion behavior predicted for more complex domain structures obtained from molecular dynamics (MD) simulations. The numerical implementation and capabilities of NMR_DIFFSIM were demonstrated by evaluating the experimental NMR spin diffusion behavior for the hydrophilic domain structure in sulfonated Diels-Alder Poly(Phenylene) (SDAPP) polymer membranes. The impact of morphology variations as a function of sulfonation and hydration level on the resulting NMR spin diffusion behavior were determined. These simulations allowed us to critically address the ability of NMR spin diffusion to discriminate between different structural models, and to highlight the extremely high fidelity experimental data required to accomplish this. A direct comparison of experimental double-quantum-filtered 1 H NMR spin diffusion in SDAPP membranes to the spin diffusion behavior predicted for MD-proposed morphologies revealed excellent agreement, providing experimental support for the MD structures at low to moderate hydration levels.

36 MATERIALS SCIENCE↗

DARK MATTER DECAY AND ANNIHILATION IN THE LOCAL UNIVERSE: CLUES FROM FERMI

We present all-sky simulated Fermi maps of {gamma}-rays from dark matter (DM) decay and annihilation in the local universe. The DM distribution is obtained from a constrained cosmological simulation of the neighboring large-scale structure provided by the CLUES project. The DM fields of density and density squared are then taken as an input for the Fermi observation simulation tool to predict the {gamma}-ray photon counts that Fermi would detect in 5 years of an all-sky survey for given DM models. Signal-to-noise ratio (S/N) sky maps have also been obtained by adopting the current Galactic and isotropic diffuse background models released by the Fermi Collaboration. We point out the possibility for Fermi to detect a DM {gamma}-ray signal in local extragalactic structures. In particular, we conclude here that Fermi observations of nearby clusters (e.g., Virgo and Coma) and filaments are expected to give stronger constraints on decaying DM compared to previous studies. As an example, we find a significant S/N in DM models with a decay rate fitting the positron excess as measured by PAMELA. This is the first time that DM filaments are shown to be promising targets for indirect detection of DM. On the other hand, the prospects for detectability of annihilating DM in local extragalactic structures are less optimistic even with extreme cross-sections. We make the DM density and density squared maps publicly available online.

79 ASTRONOMY AND ASTROPHYSICS↗

A transport-based model of material trends in nonproportionality of scintillators

Electron-hole pairs created by the passage of a high-energy electron in a scintillator radiation detector find themselves in a very high radial concentration gradient of the primary electron track. Since nonlinear quenching that is generally regarded to be at the root of nonproportional response depends on the fourth or sixth power of the track radius in a cylindrical track model, radial diffusion of charge carriers and excitons on the {approx}10 picosecond duration typical of nonlinear quenching can compete with and thereby modify that quenching. We use a numerical model of transport and nonlinear quenching to examine trends affecting local light yield versus excitation density as a function of charge carrier and exciton diffusion coefficients. Four trends are found: (1) nonlinear quenching associated with the universal 'roll-off' of local light yield versus dE/dx is a function of the lesser of mobilities {mu}{sub e} and {mu}{sub h} or of D{sub EXC} as appropriate, spanning a broad range of scintillators and semiconductor detectors; (2) when {mu}{sub e{approx_equal}{mu}h}, excitons dominate free carriers in transport, the corresponding reduction of scattering by charged defects and optical phonons increases diffusion out of the track in competition with nonlinear quenching, and a rise in proportionality is expected; (3) when {mu}{sub h} << {mu}{sub e} as in halide scintillators with hole self-trapping, the branching between free carriers and excitons varies strongly along the track, leading to a 'hump' in local light yield versus dE/dx; (4) anisotropic mobility can promote charge separation along orthogonal axes and leads to a characteristic shift of the 'hump' in halide local light yield. Trends 1 and 2 have been combined in a quantitative model of nonlinear local light yield which is predictive of empirical nonproportionality for a wide range of oxide and semiconductor radiation detector materials where band mass or mobility data are the determinative material parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

Here, we develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules, to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. Furthermore, by comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling the formation of methane hydrate-bearing intervals in fine-grained sediments

Sediment grain size exerts a fundamental control on how methane hydrates are distributed within the pore space. Fine-grained muds are the predominant sediments in continental margins, and hydrates in these sediments have often been observed in semi-vertical veins and fractures. In several instances, these hydrate veins/fractures are found in discrete depth intervals a few tens meters thick within the gas hydrate stability zone (GHSZ) surrounded by hydrate-free sediments above and below. As they are not obviously connected with free gas occurring beneath the base of the GHSZ, these isolated hydrate-bearing intervals have been interpreted as formed by microbial methane generated in situ. To investigate further the formation of these hydrate deposits, we applied a time-dependent advection-diffusion-reaction model that includes the effects of sedimentation, solute diffusion, and microbial methane generation. The microbial methane generation term depends on the amount of metabolizable organic carbon deposited at the seafloor, which is degraded at a prescribed rate resulting in methane formation beneath the sulfate reduction zone. In the model, methane hydrate precipitates once the dissolved methane concentration is greater than solubility, or hydrate dissolves if concentration goes below solubility. If the deposition of organic carbon at the seafloor is kept constant in time, we found that the predicted amounts of hydrate formed in discrete intervals within the GHSZ are much less than those estimated from observations. We then investigated the effect of temporal variations in the deposition of organic carbon. If greater amounts of organic carbon are deposited during some time interval, methane generation is enhanced during burial in the corresponding sediment interval. With variations in organic carbon deposition that are consistent with observations in continental margin sediments, we were able to reproduce the methane hydrate contents estimated in discrete depth intervals. Our results support the suggestion that in situ microbial methane generation is the source for hydrates within fine-grained sediments.

Malinverno, Alberto↗

Factors Controlling Short-Range Methane Migration of Gas Hydrate Accumulations in Thin Coarse-Grained Layers

Natural gas hydrate is often found in marine sediment in heterogeneous distributions in different sediment types. Diffusion may be a dominant mechanism for methane migration and affect hydrate distribution. We use a 1–D advection–diffusion–reaction model to understand hydrate distribution in and surrounding thin coarse–grained layers to examine the sensitivity of four controlling factors in a diffusion–dominant gas hydrate system. These factors are the particulate organic carbon content at seafloor, the microbial reaction rate constant, the sediment grading pattern, and the cementation factor of the coarse–grained layer. We use available data at Walker Ridge 313 in the northern Gulf of Mexico where two ~3–m–thick hydrate–bearing coarse–grained layers were observed at different depths. The results show that the hydrate volume and the total amount of methane within thin, coarse–grained layers are most sensitive to the particulate organic carbon of fine–grained sediments when deposited at the seafloor. The thickness of fine–grained hydrate free zones surrounding the coarse–grained layers is most sensitive to the microbial reaction rate constant. Furthermore, it may be possible to estimate microbial reaction rate constants at other locations by studying the thickness of the hydrate free zones using the Damköhler number. In addition, we note that sediment grading patterns have a strong influence on gas hydrate occurrence within coarse–grained layers.

54 ENVIRONMENTAL SCIENCES↗

Reduced Artifact Approach for Determining Diffusion Coefficients in Time-Resolved Microscopy

Ultrafast microscopy methods traditionally assume a Gaussian profile to extract excited state diffusivities from transport measurements. Although this fitting method recovers accurate diffusion coefficients when the point spread function is well-represented by a Gaussian, even minor spatial aberrations introduced by the imaging system cause significant errors in the determined value. To provide a more accurate measure of excited state transport in nano- and microscale materials systems, in this work an alternative analysis protocol is proposed that numerically convolves the Green’s function solution to the diffusion equation with the experimentally measured point spread function. In contrast to the Gaussian fitting approach, the numerical convolution is shown to be robust against artifacts caused by nonideal point spread functions. Furthermore, the numerical convolution approach is highly effective at resolving anisotropic diffusion in modeled data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An efficient approach for treating composition-dependent diffusion within organic particles

Mounting evidence demonstrates that under certain conditions the rate of component partitioning between the gas and particle phase in atmospheric organic aerosol is limited by particle-phase diffusion. To date, however, particle-phase diffusion has not been incorporated into regional atmospheric models. An analytical rather than numerical solution to diffusion through organic particulate matter is desirable because of its comparatively small computational expense in regional models. Current analytical models assume diffusion to be independent of composition and therefore use a constant diffusion coefficient. To realistically model diffusion, however, it should be composition-dependent (e.g. due to the partitioning of components that plasticise, vitrify or solidify). This study assesses the modelling capability of an analytical solution to diffusion corrected to account for composition dependence against a numerical solution. Results show reasonable agreement when the gas-phase saturation ratio of a partitioning component is constant and particle-phase diffusion limits partitioning rate (<10% discrepancy in estimated radius change). However, when the saturation ratio of the partitioning component varies, a generally applicable correction cannot be found, indicating that existing methodologies are incapable of deriving a general solution. Until such time as a general solution is found, caution should be given to sensitivity studies that assume constant diffusivity. Furthermore, the correction was implemented in the polydisperse, multi-process Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and is used to illustrate how the evolution of number size distribution may be accelerated by condensation of a plasticising component onto viscous organic particles.

54 ENVIRONMENTAL SCIENCES↗

Analysis based on global model of nitrogen plasma produced by pulsed microwave at low pressure

This paper analyzes certain evolution processes in nitrogen plasmas discharged using pulsed microwaves at low pressure. Comparing the results obtained from the global model incorporating diffusion and the microwave transmission method, the temporal variation of the electron density is analyzed. With a discharge pressure of 300 Pa, the results obtained from experiments and the global model calculation show that when the discharge begins the electron density in the plasma rises quickly, to a level above the critical density corresponding to the discharge microwave frequency, but falls slowly when the discharge microwave pulse is turned off. The results from the global model also show that the electron temperature increases rapidly to a peak, then decays after the electron density reaches the critical density, and finally decreases quickly to room temperature when the discharge microwave pulse is turned off. In the global model, the electron density increases because the high electron temperature induces a high ionization rate. The decay of the electron density mainly comes from diffusion effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Kinetic Monte Carlo Simulation of Hydrogen Diffusion in Tungsten

Nuclear fusion is considered as the most promising sustainable energy source. If achieved, it could provide electricity to the mankind for millions of years. During the reaction, the fusion ash is continuously removed from the magnetic gap, the divertor region, and the divertor facing component is subjected to intense plasma bombardment. It is proposed to use tungsten as the divertor facing material, because it has low physical sputtering yield and superior thermomechanical properties. However, the high mobility of hydrogen in tungsten and the high bombardment flux bring the hydrogen isotopes deep into the tungsten tile. The presence of hydrogen in tungsten tends to weaken the gram boundaries and produce surface blistering. The ejection of tungsten particulates into the plasma core will cool the reaction and cease the fusion reactions. Therefore, it is important to have a detailed understanding of the hydrogen diffusion in tungsten bulk. The KMC method is a stochastic computer simulation to predict the time evolution of a certain system. Typically, at a given time, the system will evolve through a few possible paths with known probabilities. In each step, the KMC method analyzes the entire system and randomly determines the system evolving events based on all transition rates of all possible events and advance the physical time. This process is repeated till the simulation of the entire physical time is completed. In previous work, the authors developed a kinetic Monte Carlo (KMC) algorithm and program to simulate hydrogen diffusion process on tungsten reconstructed surface. In this article, this KMC method is extended to model the hydrogen diffusion in tungsten bulk. The diffusion coefficients are calculated and fitted to the Arrhenius equation. The result matches the experiment measurement very well. KMC diffusion simulation needs the locations of the hydrogen trapping sites, diffusion paths and the corresponding diffusion energy barriers. The hydrogen interstitial sites in tungsten crystal have been thoroughly studied by density function theory (DFT) and molecular dynamics (MD). Johnson and Carter used DFT to determine the preferred location of the hydrogen interstitial sites m tungsten crystal, which are the tetrahedral sites (T-sites) in body-centered-cubic (bcc) lattice surfaces. All T-sites are located on the surfaces of a lattice cell. There are four T-sites per surface and twelve T-sites per lattice cell. The hydrogen atoms diffuse by traveling from one T-site to one of its nearest four T-site neighbors. Thus, each T-site is surrounded by two neighbors on the same surface, and one neighbor on each of the two adjacent surfaces perpendicular to the surface holding the center T-site. The diffusion barrier between two neighboring T-sites was calculated to be 0.38 eV. Knowing the diffusion path, energy barrier, and the crystal structure, the KMC simulation is readily to be performed. Based on other researchers' DFT calculations, the hydrogen stable interstitial site in tungsten bulk is determined as the tetrahedral site on the surface of the bee lattice. Each T-site has 4 neighbors and the energy barrier between two adjacent T-sites are estimated to be 0.38 eV. Based on those facts and the KMC theory, a MATLAB program is developed to model the hydrogen diffusion in tungsten bulk. In the MATLAB program, substrate temperature, hydrogen concentration, physical time to be simulated, and the number of cycles are all customizable. To compare the KMC determined diffusion coefficients with experiment results in the literature, the simulations are performed for temperature 300 K - 2500 K and low hydrogen concentration (0.1%), mimicking the experiment condition. The calculated diffusion coefficients match the reference values measured by the experiment under low hydrogen concentration condition. The results are also fitted to the Arrhenius equation. The pre-exponential factor and the average activation energy in Arrhenius equation are obtained. The good agreement between simulation and experiment proves that the developed KMC algorithm truly reflect the well-established theory of interstitial hydrogens in tungsten. The developed program could easily be used to model the diffusion process and predict the diffusion coefficients under other concentrations and temperatures. This work is part of the ongoing development of hydrogen diffusion in tungsten integrating surface diffusion (previous work), bulk diffusion (this work), and adsorption/desorption on surface (future work)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗