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At least 1,387 records · Page 77

Oxidation of Carbon/Carbon through Coating Cracks

Reinforced carbon/carbon (RCC) is used to protect the wing leading edge and nose cap of the Space Shuttle Orbiter on re-entry. It is composed of a lay-up of carbon/carbon fabric protected by a SiC conversion coating. Due to the thermal expansion mismatch of the carbon/carbon and the SiC, the SiC cracks on cool-down from the processing temperature. The cracks act as pathways for oxidation of the carbon/carbon. A model for the diffusion controlled oxidation of carbon/carbon through machined slots and cracks is developed and compared to laboratory experiments. A symmetric cylindrical oxidation cavity develops under the slots, confirming diffusion control. Comparison of cross sectional dimensions as a function of oxidation time shows good agreement with the model. A second set of oxidation experiments was done with samples with only the natural craze cracks, using weight loss as an index of oxidation. The agreement of these rates with the model is quite reasonab

Jacobson, N. S.↗

Simple Analytical Forms of the Perpendicular Diffusion Coefficient for Two-component Turbulence. III. Damping Model of Dynamical Turbulence

In several astrophysical applications one needs analytical forms of cosmic-ray diffusion parameters. Some examples are studies of diffusive shock acceleration and solar modulation. In the current article we explore perpendicular diffusion based on the unified nonlinear transport theory. While we focused on magnetostatic turbulence in Paper I, we included the effect of dynamical turbulence in Paper II of the series. In the latter paper we assumed that the temporal correlation time does not depend on the wavenumber. More realistic models have been proposed in the past, such as the so-called damping model of dynamical turbulence. In the present paper we derive analytical forms for the perpendicular diffusion coefficient of energetic particles in two-component turbulence for this type of time-dependent turbulence. We present new formulas for the perpendicular diffusion coefficient and we derive a condition for which the magnetostatic result is recovered.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of a creep model informed by lower-length scale simulations to simulate creep in doped UO 2

Using molecular dynamics, we predict information at the atomistic scale used to develop a mechanistic UO 2 creep model for use in higher length-scale fuel performance codes. The ultimate objective of the model is to better describe the grain size dependence and therefore impact of doping on creep rates in UO 2 . In a previous NEAMS milestone, we found that Nabarro-Herring (bulk diffusional) creep was too low to capture the experimentally observed creep rates in standard UO 2 . Moreover, in that milestone, other mechanisms were explored, such as Coble (grain boundary) creep and dislocation climb, with each mechanism exhibiting different grain size dependencies. Again, these were orders of magnitude too low to describe the experimental creep rates. In this work, we address the previous assumptions made for the Coble creep mechanism by investigating the diffusivity of various defects at grain boundaries in UO 2 and, critically, to determine if enhanced grain boundary diffusivity allows the model to better reproduce experimental results. The diffusivity as a function of temperature for different concentrations of uranium vacancies and interstitials for bulk UO 2 have also been examined using cluster dynamics. Furthermore, using a concentration dependent segregation model, the concentration of defects at the grain boundary were predicted. This atomistic data was then input into the various creep mechanisms and the creep rates compared to the empirical MATPRO correlation (used in BISON) and experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Designing, Modeling, Constructing, and Testing a Flat Panel Speaker and Sound Diffuser for a Simulator

The goal of this project was to design, model, build, and test a flat panel speaker and frame for a spherical dome structure being made into a simulator. The simulator will be a test bed for evaluating an immersive environment for human interfaces. This project focused on the loud speakers and a sound diffuser for the dome. The rest of the team worked on an Ambisonics 3D sound system, video projection system, and multi-direction treadmill to create the most realistic scene possible. The main programs utilized in this project, were Pro-E and COMSOL. Pro-E was used for creating detailed figures for the fabrication of a frame that held a flat panel loud speaker. The loud speaker was made from a thin sheet of Plexiglas and 4 acoustic exciters. COMSOL, a multiphysics finite analysis simulator, was used to model and evaluate all stages of the loud speaker, frame, and sound diffuser. Acoustical testing measurements were utilized to create polar plots from the working prototype which were then compared to the COMSOL simulations to select the optimal design for the dome. The final goal of the project was to install the flat panel loud speaker design in addition to a sound diffuser on to the wall of the dome. After running tests in COMSOL on various speaker configurations, including a warped Plexiglas version, the optimal speaker design included a flat piece of Plexiglas with a rounded frame to match the curvature of the dome. Eight of these loud speakers will be mounted into an inch and a half of high performance acoustic insulation, or Thinsulate, that will cover the inside of the dome. The following technical paper discusses these projects and explains the engineering processes used, knowledge gained, and the projected future goals of this project

Dillon, Christina↗

Methane Diffusion and Adsorption in Shale Rocks: A Numerical Study Using the Dusty Gas Model in TOUGH2/EOS7C-ECBM

Gas production from shale gas reservoirs plays a significant role in satisfying increasing energy demands. Compared with conventional sandstone and carbonate reservoirs, shale gas reservoirs are characterized by extremely low porosity, ultra-low permeability and high clay content. Slip flow, diffusion, adsorption and desorption are the primary gas transport processes in shale matrix, while Darcy flow is restricted to fractures. Understanding methane diffusion and adsorption, and gas flow and equilibrium in the low-permeability matrix of shale is crucial for shale formation evaluation and for predicting gas production. Modeling of diffusion in low-permeability shale rocks requires use of the Dusty gas model (DGM) rather than Fick’s law. The DGM is incorporated in the TOUGH2 module EOS7C-ECBM, a modified version of EOS7C that simulates multicomponent gas mixture transport in porous media. Also included in EOS7C-ECBM is the extended Langmuir model for adsorption and desorption of gases. In this study, a column shale model was constructed to simulate methane diffusion and adsorption through shale rocks. The process of binary CH 4 - N 2 diffusion and adsorption was analyzed. A sensitivity study was performed to investigate the effects of pressure, temperature and permeability on diffusion and adsorption in shale rocks. The results show that methane gas diffusion and adsorption in shale is a slow process of dynamic equilibrium, which can be illustrated by the slope of a curve in CH4mass variation. The amount of adsorption increases with the pressure increase at the low pressure, and the mass change by gas diffusion will decrease due to the decrease in the compressibility factor of the gas. With the elevated temperature, the gas molecules move faster and then the greater gas diffusion rates make the process duration shorter. The gas diffusion rate decreases with the permeability decrease, and there is a limit of gas diffusion if the permeability is less than 1.0×10 -15 m 2 . In conclusion, the results can provide insights for a better understanding of methane diffusion and adsorption in the shale rocks so as to optimize gas production performance of shale gas reservoirs.

04 OIL SHALES AND TAR SANDS↗

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗

Absence of a charge diffusion pole at finite energies in an exactly solvable interacting flat-band model in $d$ dimensions

Motivated by recent bounds for charge diffusion in critical matter, we investigate the following question: What sets the scale for the velocity for diffusing degrees of freedom in a scale-invariant system? To make our statements precise, here we analyze the diffusion pole in an exactly solvable model for a Mott transition in the presence of a long-range interaction term. To achieve scale invariance, we limit our discussion to the flat-band regime. We find in this limit that the diffusion pole, which would normally obtain at finite energy, is pushed to zero energy, resulting in a vanishing of the diffusion constant. This occurs even in the presence of interactions in certain limits, indicating the robustness of this result to the inclusion of a scale in the problem. Consequently, scale invariance precludes any reasonable definition of the diffusion constant. Nonetheless, we do find that a scale can be defined, albeit irrelevant to diffusion, which is the product of the squared band velocity and the density of states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Loci/STREAM Sharp Interface Model Validation of Cryogenic Propellant Tank Self-Pressurization

This paper documents a model validation effort for the prediction of cryogenic propellant tank selfpressurization physics using the Loci/STREAM sharp interface CFD model developed at NASA MSFC. Cryogenic fluid management (CFM) applications for long duration spaceflight missions require accurate modeling of heat transfer and thermodynamics. Therefore, detailed validation of those physics is important to ensure simulation accuracy. In the past, the MSFC Propulsion Fluid Dynamics Branch has validated and used the Loci/STREAM Volume of Fluid (VOF) module extensively for propellant slosh applications, which are dominated by fluid motion. For cases where the interface gas/liquid interface is essentially static, the Loci/STREAM sharp interface was developed for more rapid and efficient CFM analysis. In the present study, Loci/STREAM sharp interface simulations were compared with the NASA K-site self-pressurization experiment of a flight weight, partially full, LH2 tank in normal gravity. This study investigated several parametric effects and made a number of important observations on the performance of the Loci/STREAM sharp interface method: - First, a homogeneous model was derived to verify the CFD model. The homogeneous model assumes both gas and liquid phases are uniform and are at saturation temperature. The predicted pressure rise rates at 3.5 W/m2 and 2.0 W/m2 with a 49% fill level are all lower than the experimental measurement. This is expected due to the observed temperature stratification near the gas-liquid interface during testing. - The k-w and k-e turbulence models predict comparable pressurization rates, which are much lower than the experiment measurement. On the other hand, the pressure values and pressurization rates from both models are almost the same as those of the homogeneous model. The current turbulence model is too diffusive and is not capable of capturing the thermal stratification in the liquid and ullage. - When using the laminar flow model, the pressurization rate is found to be very close to the experimental value when a quasi-steady flow field is allowed to develop by continuously venting the tank prior to pressurization as was done during testing. On the other hand, without initial venting, the rate is not constant. Additionally, the development time to reach a quasi-steady flow field differed from the experiment due to the lack of turbulent mixing away from the gas-liquid interface that is expected in reality. - Using the laminar flow model and appropriate initial conditioning, the pressurization rate is within 15% of the experimental value for 49% fill level at 3.5 W/m 2 and is within 18% for 2.0 W/m 2 heat loading. - Using the laminar flow model and appropriate initial conditioning, the pressurization rate is within 18% of the experimental value for a 29% fill level and within 15% for an 83% fill level.

H. Q. Yang↗

Computational Modeling of Molten Salt Infiltration and Oxidation in Nuclear Graphite

Graphite is utilized as a moderator and reflector in advanced nuclear reactor designs due to its high thermal conductivity, neutron moderation properties, and resistance to radiation damage. However, its longterm performance and reliability are challenged by degradation mechanisms such as molten salt infiltration in molten salt reactors (MSRs) and oxidation in gas-cooled reactors (GCRs). These mechanisms can compromise the structural integrity and operational lifetime of graphite components, necessitating a more detailed assessment of their physical behavior. This report focuses on the development of computational models for molten salt infiltration and oxidation of graphite to aid the design and performance analysis of graphite components. For molten salt infiltration, a computational framework is developed that couples incompressible Navier-Stokes and phase-field model to simulate the penetration of molten salt into graphite?s interconnected pore structure. Initial model verification is performed using two-phase flows in two dimensions, demonstrating the models ability to capture fundamental physical behavior and agree with analytical solution. This framework is then applied to a realistic IG110 nuclear graphite , where a computed tomography extracted pore geometry is used to analyse the infiltration behavior of FLiNaK molten salt. This model provides insights into how the microstructure and other relevant parameters influence the transport pathways of molten salt into graphite, potentially offering a means to rapidly evaluate a graphite grade?s resistance to infiltration. For oxidation, the report details pore-scale mass and heat transport models, describing the diffusion of gases, reaction kinetics, and thermal effects. Additionally, this report highlights inconsistencies in the existing volume-averaged macroscopic model, particularly in upscaling of reaction kinetics and flux terms, and surface to volume transformations. These inconsistencies suggest that current formulations may not accurately capture the experimentally observed graphite oxidation process, highlighting the need for improved model development. This work advances the development of physics-based computational models for graphite degradation, contributing to improved predictive models for next-generation nuclear reactor designs. Future efforts will focus on refining the infiltration model to address non-physical behaviors and enhance its robustness. Additionally, for oxidation, further studies will employ the principles of volume averaging to rigorously derive the upscaled equations, potentially in collaboration with subject matter experts.

Computational Modeling of Molten Salt Infiltration↗

Modeling aerosol bolus inhalations in the human lung with the multiple path particle deposition model: Comparison with experimental data

Existing one-dimensional (1D) models of aerosol dosimetry often ignore mixing mechanisms of inhaled aerosols during their transport in the lung. This mixing or aerosol dispersion results from different physical mechanisms in different regions of the lung. It is a higher order effect, which cannot be directly captured in 1D modeling approaches, and thus is sometimes modeled as a diffusive process. Here, in this study, we improved our recently developed alveolar mixing module incorporated in the multiple path particle dosimetry model (MPPD) to account for flow irreversibility and particle trapping in the alveolar spaces, as well as mixing occurring in the tracheobronchial region. This new version of MPPD was coupled with CFPD-based predictions of aerosol bolus dispersion in the oral airway. The model was used to predict the deposition, dispersion, and mode shift of aerosol bolus inhaled at different penetration depths within the lung for breathing patterns and particle size matching those used in a previous experimental study (Darquenne et al., 2016). Even though a quite simplified approach was used, the computations appear to describe subject-specific and test-specific experimental data reasonably well. The proposed combined dispersion-deposition model can be a useful tool for targeted drug delivery and also for exposure health risk assessment.

MPPD↗

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

97 MATHEMATICS AND COMPUTING↗

A Lagrangian Simulation of Subsonic Aircraft Exhaust Emissions

To estimate the effect of subsonic and supersonic aircraft exhaust on the stratospheric concentration of NO(y), we employ a trajectory model initialized with air parcels based on the standard release scenarios. The supersonic exhaust simulations are in good agreement with 2D and 3D model results and show a perturbation of about 1-2 ppbv of NO(y) in the stratosphere. The subsonic simulations show that subsonic emissions are almost entirely trapped below the 380 K potential temperature surface. Our subsonic results contradict results from most other models, which show exhaust products penetrating above 380 K, as summarized. The disagreement can likely be attributed to an excessive vertical diffusion in most models of the strong vertical gradient in NO(y) that forms at the boundary between the emission zone and the stratosphere above 380 K. Our results suggest that previous assessments of the impact of subsonic exhaust emission on the stratospheric region above 380 K should be considered to be an upper bound.

Schoeberl, M. R.↗

Modeling of the SiC chemical vapor deposition process and comparison with experimental results

A model of the NASA Lewis SiC CVD process is described, and the results presented. A key feature of the model is the direct coupling of gas-phase chemical kinetics with diffusion. A deposition chemistry model using reactive sticking coefficients for each gas-phase species provides the diffusion boundary conditions. SiC deposition rates predicted by the model agree reasonably well with experimentally observed rates.

Annen, K. D.↗

ISD3: a particokinetic model for predicting the combined effects of particle sedimentation, diffusion and dissolution on cellular dosimetry for in vitro systems

The development of particokinetic models describing the delivery of insoluble or poorly soluble nanoparticles to cells in liquid cell culture systems has improved the basis for dose-response analysis, hazard ranking from high-throughput systems, and now allows for translation of exposures across in vitro and in vivo test systems. Complimentary particokinetic models that address processes controlling delivery of both particles and released ions to cells, and the influence of particle size changes from dissolution on particle delivery for cell-culture systems would help advance our understanding of the role of particles ion dosimetry on cellular toxicology. We developed ISD 3 , an extension of our previously published model for insoluble particles, by deriving a specific formulation of the Population Balance Equation for soluble particles. ISD3 describes the time, concentration and particle size dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is modular, and can be adapted by application of any empirical model of dissolution, alternative approaches to calculating sedimentation rates, and cellular uptake or treatment of boundary conditions. We apply the model to calculate the particle and ion dosimetry of nanosilver and silver ions in vitro after calibration of two empirical models, one for particle dissolution and one for ion uptake. The results demonstrate utility and accuracy of the ISD 3 framework for dosimetry in these systems. Total media ion concentration, particle concentration and total cell-associated silver time-courses were well described by the model, across 2 concentrations of 20 and 110 nm particles. ISD 3 was calibrated to dissolution data for 20 nm particles as a function of serum protein concentration, but successfully described the media and cell dosimetry time-course for both particles at all concentrations and time points. We also report the finding that protein content in media has effects both on the initial rate of dissolution and the resulting near-steady state ion concentration in solution.

59 BASIC BIOLOGICAL SCIENCES↗

Observational constraints on an embedded cloud model for the soft X-ray diffuse background

The reason for the observed anticorrelation between soft X-ray diffuse background (SXRB) and neutral hydrogen column densities are considered. Using the B and C band data from an all-sky survey of the SXRB, as well as data in the Be band, it is shown that the Jakobsen and Kahn (1986) embedded cloud model, in which several statistical properties of the SXRB in the B and C bands were used to constrain their model parameters, cannot fit the observed band ratios, except in the limit in which virtually all of the emission originates in the near side of the absorbing gas. It was also shown that model parameters corresponding to appreciably mixed emission and absorption, as proposed by Bunner et al. (1969) and Davidsen et al. (1972), do not fit the data. Model parameters corresponding to the absorption models of Bowyer et al. (1968), Bunner et al. (1969), Davidsen et al. (1972), and Yentis et al. (1972), cannot fit the data unless the absorbing material is more strongly clumped than is permitted by 21-cm observations.

Burrows, D. N.↗

Cation–polymer interactions and local heterogeneity determine the relative order of alkali cation diffusion coefficients in PEGDA hydrogels

Current research efforts are focused on endowing polymer membranes with ion–ion selectivity by incorporating ion–polymer interactions into materials to bias the selective partitioning and or diffusivity of one species over another. However, little is known about the impact of such interactions on the mechanisms of ion transport. In this study, we probe the influence of cation–polymer interactions on cation, anion, and salt diffusivity in a model membrane material, poly(ethylene glycol) diacrylate (PEGDA) by modeling concentrated polyethylene oxide solutions via molecular dynamics simulations. These results are compared to published experimental data for LiCl, NaCl, and KCl diffusion in PEGDA. Experimentally, the order of salt and cation diffusion coefficients for LiCl, NaCl, and KCl deviate from the order in aqueous solutions. Here, simulations identify these deviations to arise from cation–polymer coordination in the membrane. Both the fraction of bound cations and the average binding lifetime increases with decreasing cation hydration free energy (moving down the alkali series), leading to different diffusivity trends in the membrane compared to solution. However, to recover the experimentally observed order of diffusivities cations and salt in our simulations, we needed to incorporate membrane heterogeneity explicitly via a polymer charge scaling procedure. Together, our results indicate that cation–polymer interactions, as well as spatial heterogeneity within the membrane, play a critical role in dictating the observed order of alkali cation and salt diffusion coefficients in membranes.

36 MATERIALS SCIENCE↗

Characteristics of acoustic-gravity waves in a diffusively separated atmosphere

The effects of wave-induced diffusion on the characteristics of plane acoustic gravity waves in the earth's thermosphere are investigated by means of a two fluid model atmosphere in diffusive equilibrium. At wave periods greater than the shortest characteristic diffusion time for the minor gas, diffusion induced by the wave is considered to act to eliminate amplitude and phase differences between the wave-induced density fluctuations of individual gases and restore the perturbed fluid to diffusive equilibrium. Vertical diffusion is most important at large scale sizes, but horizontal diffusion dominates for horizontal wavelengths of less than several hundred kilometers. As a result of wave-induced diffusion, AE-C satellite measurements of neutral density fluctuations of thermospheric constituents are only compatible with relatively small scale internal gravity waves. Velocity and temperature differences for acoustic-gravity waves are greatest at periods near the mean collision time and diffusion time and lead to the dissipation of wave energy. The predictions of the theory are consistent with a high latitude, low altitude source for the medium scale waves and a more localized random source for the waves observed by AE-C.

Del Genio, A. D.↗