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At least 469 records · Page 26

Hybrid framework for the simulation of stochastic chemical kinetics

Stochasticity plays a fundamental role in various biochemical processes, such as cell regulatory networks and enzyme cascades. Isothermal, well-mixed systems can be modelled as Markov processes, typically simulated using the Gillespie Stochastic Simulation Algorithm (SSA) [25]. While easy to implement and exact, the computational cost of using the Gillespie SSA to simulate such systems can become prohibitive as the frequency of reaction events increases. This has motivated numerous coarse-grained schemes, where the “fast” reactions are approximated either using Langevin dynamics or deterministically. While such approaches provide a good approximation when all reactants are abundant, the approximation breaks down when one or more species exist only in small concentrations and the fluctuations arising from the discrete nature of the reactions become significant. This is particularly problematic when using such methods to compute statistics of extinction times for chemical species, as well as simulating non-equilibrium systems such as cell-cycle models in which a single species can cycle between abundance and scarcity. In this paper, a hybrid jump-diffusion model for simulating well-mixed stochastic kinetics is derived. It acts as a bridge between the Gillespie SSA and the chemical Langevin equation. For low reactant reactions the underlying behaviour is purely discrete, while purely diffusive when the concentrations of all species are large, with the two different behaviours coexisting in the intermediate region. A bound on the weak error in the classical large volume scaling limit is obtained, and three different numerical discretisations of the jump-diffusion model are described. The benefits of such a formalism are illustrated using computational examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Charge Carrier Transport and Deep Levels Recharge in Avalanche S-Diodes Based on GaAs

Carrier transport and deep-level recharging in semiconductor avalanche S-diode structures have been investigated. Gallium-arsenide n{sup +}–π–ν–n structures with the diffusion distribution of deep iron acceptors have been studied. It has been found by solving the continuity and Poisson equations with the use of a commercial software that the electron injection affects the avalanche breakdown voltage and the spacecharge region broadens due to capture of avalanche holes on negative iron ions in the π-region. It is demonstrated by comparing the results of numerical calculation with the experimental data that the S-shaped I–V characteristic of the diffusion avalanche S-diodes cannot be explained within the previously proposed mechanism of capture of avalanche holes on the deep iron levels.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Phase-Field Model for In-Space Manufacturing of Binary Alloys

The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface.

36 MATERIALS SCIENCE↗

Immobile Pore-Water Storage Enhancement and Retardation of Gas Transport in Fractured Rock

The effect of immobile pore-water on gas transport in fractured rock has implications for numerical modeling of soil vapor extraction, methane leakage, gaseous CO 2 leakage from sequestration operations, radionuclide transport from underground nuclear explosions, and nuclear waste disposal. While the ability for immobile pore-water storage to effect gas transport has been recognized in the past, the details and specific scenarios leading to enhanced, retarded, or unaffected gas transport have not been explored. In this paper, we performed numerical investigations into the enhancement and retardation of gas transport due to immobile pore-water storage in order to identify implications for gas transport applications. To do this, we developed a numerical approach to model gas transport with a single-phase flow solution coupled to the advection–dispersion equation modified to account for immobile pore-water storage. Other than the immobility of pore water, the formulation contains all other physics included in two-phase formulations (advective and diffusive gas transport in fractures and rock matrix and dissolution in immobile pore water). The assumption of immobile pore water is valid here since for many applications involving transport of soluble gases in fractured rock, the rate of aqueous transport is insignificant compared to gas transport. We verify our modeling approach with analytical solutions of: (1) 1D gas diffusion, (2) 1D gas advection, (3) barometric pumping of a fracture, and (4) gas transport with uniform fracture flow and diffusion into the matrix. We account for pore-water storage in our model by implementing a kinetic formulation of gas dissolution wherein the dissolved (aqueous) phase is considered an immobile constituent. Using this formulation, we model the effect of dissolution rate and saturation on the retardation of gas transport during pure diffusion and pure advection. We also demonstrate that although it is commonly believed that pore-water storage will always enhance gas transport in fractures during oscillatory flow (e.g., during reversing pressure gradients such as barometric pumping cycles), our simulations indicate that this may not always be the case. Our numerical investigations indicate that scenarios with lower effective diffusion coefficients ( &#x2A85;<!-- <≈ --> 10 &#x2212;<!-- - --> 5 &#xA0;m 2 / s ) and lower dissolution coefficients (i.e., the dissolution diffusion coefficient) ( &#x2A85;<!-- <≈ --> 10 &#x2212;<!-- - --> 11 &#xA0;m 2 / s ) will result in enhanced gas transport. Other combinations of gaseous diffusion and dissolution coefficients result in delayed gas transport or insignificant effect on gas transport. Based on these results, and given the fact that the free-air diffusion coefficients for many gases are slightly above 10 &#x2212;<!-- - --> 5 &#xA0;m 2 / s (near the boundary of enhanced/non-enhanced gas transport), tortuosity would have to be significant for gas transport enhancement to occur. Similarly, if we consider the free-water diffusion coefficient of gases (around 10 &#x2212;<!-- - --> 9 &#xA0;m 2 / s for many gases of interest) to be a maximum bound for the effective dissolution coefficients (i.e., the rate of diffusion into the water away from the air/water interface will limit the dissolution rate), the effective dissolution coefficient would have to be at least 2 orders of magnitude less for enhanced gas transport to occur. Otherwise, pore-water storage will delay or have negligible effect on the gas transport. The results also indicate that the assumption of instantaneous equilibrium, often invoked in numerical codes for dissolution processes (i.e., dissolution coefficient is effectively infinite), will fail to accurately capture important details of soluble gas transport. Finally, the implication of our results is that gas breakthrough times in fractured rock during oscillatory flow may be highly dependent on the effective gaseous diffusion and dissolution coefficients.

58 GEOSCIENCES↗

High-Throughput Study of Diffusion and Phase Transformation Kinetics of Magnesium-Based Systems for Automotive Cast Magnesium Alloys

The objective of the proposed study is to establish a scientific foundation on kinetic modeling of diffusion, phase precipitation, and casting/solidification, in order to accelerate the design and optimization of cast magnesium (Mg) alloys for weight reduction of U.S. automotive fleet. The team has performed the following tasks: 1) study diffusion kinetics of various Mg-containing binary systems using high-throughput diffusion multiples to establish reliable diffusivity and mobility databases for the Mg-aluminum (Al)-zinc (Zn)-tin (Sn)-calcium (Ca)-strontium (Sr)-manganese (Mn) systems; 2) study the precipitation kinetics (nucleation, growth and coarsening) using both innovative dual-anneal diffusion multiples and cast model alloys to provide large amounts of kinetic data (including interfacial energy) and microstructure atlases to enable implementation of the Kampmann-Wagner numerical model to simulate phase transformation kinetics of non-spherical/non-cuboidal precipitates in Mg alloys; 3) implement a micromodel to take into account back diffusion in the solid phase in order to predict microstructure and microsegregation in multicomponent Mg alloys during dendritic solidification especially under high pressure die-casting (HPDC) conditions; and, 4) widely disseminate the data, knowledge and information using the Materials Genome Initiative infrastructure (http://www.mgidata.org) as well as publications and digital data sharing to enable researchers to identify new pathways/routes to better cast Mg alloys.

36 MATERIALS SCIENCE↗

Dephasing enhanced spin transport in the ergodic phase of a many‐body localizable system

We study high temperature spin transport in a disordered Heisenberg chain in the ergodic regime when bulk dephasing is present. We find that while dephasing always renders the transport diffusive, there is nonetheless a remnant of the diffusive to sub‐diffusive transition found in a system without dephasing manifested in the behaviour of the diffusion constant with the dephasing strength. By studying finite‐size effects we show numerically and theoretically that this feature is caused by the competition between large crossover length scales associated to disorder and dephasing that control the dynamics observed in the thermodynamic limit. We demonstrate that this competition may lead to a dephasing enhanced transport in this model. image

Žnidarič, Marko↗

A high-order adaptive algorithm for multispecies gaseous flows on mapped domains

We report a fourth-order accurate finite-volume method is developed and verified for solving strongly nonlinear, time-dependent, compressible, thermally perfect, and multispecies gaseous flows on mapped grids that are adaptively refined in space and time. The algorithm introduces a new scheme for numerical flux calculations in order to cope with the nonlinear, spatially and temporally varying thermodynamic and transport properties of the gaseous mixture. The fourth-order numerical error convergence and solution accuracy are verified using Couette flow, species mass diffusion bubble, and vortex convection and diffusion problem. The thermally perfect, multispecies functionality is validated using a one-dimensional shock tube and two-dimensional shock box problem. Results are obtained for the Mach reflection problem where a strong shock propagates in the multispecies gaseous flow along a ramp and are compared to the solution of the shock propagation in a single species, calorically perfect, gaseous flow over the same ramp. The validated algorithm is then applied to simulate a relatively complex flow configuration to examine the secondary flow mixing due to the double air jets along with the main inlet where a premixed fuel mixture flows in. Future investigations will focus on three-dimensional configurations.

42 ENGINEERING↗

Learning subgrid-scale models with neural ordinary differential equations

We propose a new approach to learning the subgrid-scale model when simulating partial differential equations (PDEs) solved by the method of lines and their representation in chaotic ordinary differential equations, based on neural ordinary differential equations (NODEs). Solving systems with fine temporal and spatial grid scales is an ongoing computational challenge, and closure models are generally difficult to tune. Machine learning approaches have increased the accuracy and efficiency of computational fluid dynamics solvers. In this approach neural networks are used to learn the coarse- to fine-grid map, which can be viewed as subgrid-scale parameterization. We propose a strategy that uses the NODE and partial knowledge to learn the source dynamics at a continuous level. Our method inherits the advantages of NODEs and can be used to parameterize subgrid scales, approximate coupling operators, and improve the efficiency of low-order solvers. Numerical results with the two-scale Lorenz 96 ODE, the convection-diffusion PDE, and the viscous Burgers' PDE are used to illustrate this approach.

97 MATHEMATICS AND COMPUTING↗

Asymptotic-preserving semi-implicit finite volume scheme for extended magnetohydrodynamics

A Finite Volume (FV) scheme is developed for solving the extended magnetohydrodynamic (XMHD) equations, yielding accurate results in the ideal, resistive, and Hall MHD limits. This is accomplished by first re-writing the XMHD equations such that it allows the algorithm to retain the use of ideal MHD Riemann solvers and the constrained transport method to preserve divergence-free magnetic fields. Incorporation of electron inertia and displacement current introduces additional numerical stiffness which motivates a semi-implicit FV scheme that re-formulates the XMHD model as a relaxation system. The equations are then advanced in time using an explicit 2nd-order Runge–Kutta scheme with operator splitting applied to the implicit source term updates at each sub-stage. For additional numerical stability, a density-dependent slope limiter is implemented to increase flux diffusivity at low density regions where non-ideal effects become significant. The algorithm is subsequently implemented in a scalable adaptive mesh refinement (AMR) framework. As the new algorithm retains many aspects of the ideal MHD formulations, it asymptotes naturally to the ideal MHD limit. Moreover, it shows promising results at the resistive and Hall MHD limits. This is verified against reference test problems for ideal, resistive and Hall MHD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Calculation of Last Closed Drift Shells for the 2013 GEM Radiation Belt Challenge Events

Radiation belt behavior is often analyzed in terms of adiabatic invariants, of which the third roughly characterizes the radial distance of particle drift shells. The outermost, or last closed drift shell, can be an important boundary for numerical modeling, especially for drift-averaged treatments such as three-dimensional diffusion codes. In this work, we discuss calculation of the last closed drift shell, using the widely used International Radiation Belt Environment Modeling (IRBEM) Library, the LanlGeoMag code, and a guiding center code named AFRL-Shell, in conjunction with a variety of current magnetic field models. Furthermore, we present results for the four events in 2013, comprising the radiation belt challenge organized by the Quantitative Assessment of Radiation Belt Modeling focus group of the Geospace Environment Modeling (GEM) program.

79 ASTRONOMY AND ASTROPHYSICS↗

A Unified Analytical Model for Pressure Solution With Fully Coupled Diffusion and Reaction

Abstract Geophysical models for pressure solution are typically developed for diffusion‐controlled or reaction‐controlled scenarios. We present a unified analytical model that considers fully coupled diffusion and reaction during pressure solution. The model recovers the diffusion‐controlled and reaction‐controlled models in the literature as specific limiting cases. When diffusion and reaction exhibit comparable influences, we validate the proposed model against independent numerical simulations. The proposed model is then employed in interpreting experimental measurements, demonstrating a better agreement compared to previous interpretations.

Wang, Ziyan [Energy Geosciences Division Lawrence ↗

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

54 ENVIRONMENTAL SCIENCES↗

GP-BayesOpInf

SAND2025-01851O GP-BayesOpInf is a software tool that uses algorithms to combine Gaussian process regression, principal component analysis, and linear Bayesian inference to produce a probabilistic reduced-order model for time-dependent systems. Numerical examples include the compressible Euler equations for an ideal gas, a heat diffusion process with a nonlinear reaction term, and a set of ordinary differential equations describing a compartmental model in epidemiology. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

Diffusion Bonded Hydrogen Pre-Cooler Pressure Testing

Diffusion bonded heat exchangers, also known as printed circuit heat exchangers (PCHEs), have numerous benefits over traditional shell and tube heat exchangers including high pressure containment, a compact size with 1000 to 5000 m 2 of surface area per unit volume, and lower costs. One emerging application is in hydrogen vehicle fueling stations as a hydrogen pre-cooler (H2PC™) where the hydrogen is cooled at pressures up to 900 bar. These pre-coolers must be able to withstand pressure cycling over 10 5 cycles during the fueling station lifetime without degradation of their pressure vessel integrity that could result in hydrogen leakage.

08 HYDROGEN↗

Fluctuating hydrodynamics of reactive liquid mixtures

Fluctuating hydrodynamics (FHD) provides a framework for modeling microscopic fluctuations in a manner consistent with statistical mechanics and nonequilibrium thermodynamics. This paper presents an FHD formulation for isothermal reactive incompressible liquid mixtures with stochastic chemistry. Fluctuating multispecies mass diffusion is formulated using a Maxwell-Stefan description without assuming a dilute solution, and momentum dynamics is described by a stochastic Navier-Stokes equation for the fluid velocity. We consider a thermodynamically consistent generalization for the law of mass action for non-dilute mixtures and use it in the chemical master equation (CME) to model reactions as a Poisson process. The FHD approach provides remarkable computational efficiency over traditional reaction-diffusion master equation methods when the number of reactive molecules is large, while also retaining accuracy even when there are as few as ten reactive molecules per hydrodynamic cell. We present a numerical algorithm to solve the coupled FHD and CME equations and validate it on both equilibrium and nonequilibrium problems. We simulate a diffusively driven gravitational instability in the presence of an acid-base neutralization reaction, starting from a perfectly flat interface. We demonstrate that the coupling between velocity and concentration fluctuations dominates the initial growth of the instability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reaction rates for reaction-diffusion kinetics on unstructured meshes

The reaction-diffusion master equation is a stochastic model often utilized in the study of biochemical reaction networks in living cells. It is applied when the spatial distribution of molecules is important to the dynamics of the system. A viable approach to resolve the complex geometry of cells accurately is to discretize space with an unstructured mesh. Diffusion is modeled as discrete jumps between nodes on the mesh, and the diffusion jump rates can be obtained through a discretization of the diffusion equation on the mesh. Reactions can occur when molecules occupy the same voxel. Here in this paper, we develop a method for computing accurate reaction rates between molecules occupying the same voxel in an unstructured mesh. For large voxels, these rates are known to be well approximated by the reaction rates derived by Collins and Kimball, but as the mesh is refined, no analytical expression for the rates exists. We reduce the problem of computing accurate reaction rates to a pure preprocessing step, depending only on the mesh and not on the model parameters, and we devise an efficient numerical scheme to estimate them to high accuracy. We show in several numerical examples that as we refine the mesh, the results obtained with the reaction-diffusion master equation approach those of a more fine-grained Smoluchowski particle-tracking model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Compact Heat Exchanger Design and Testing for Advanced Reactors and Advanced Power Cycles

The goal of the proposed research is to demonstrate the thermal hydraulic performance of innovative surface geometries in compact heat exchangers used as intermediate heat exchangers (IHXs) and recuperators for the supercritical carbon dioxide (s-CO 2 ) Brayton cycle. Printed-circuit heat exchangers (PCHEs) are the primary compact heat exchangers of interest. The overall objectives are: To develop optimized PCHE designs for different working fluid combinations including helium to s-CO 2 , liquid salt to s-CO 2 , sodium to s-CO 2 , and liquid salt to helium; To experimentally and numerically investigate thermal performance, thermal stress and failure mechanism of PCHEs under various transients; and To study diffusion bonding techniques for elevated-temperature alloys and examine post-test material integrity of the PCHEs. The project objectives were accomplished by defining and executing five different tasks corresponding to these specific objectives. The first task involved a thorough literature review and a selection of IHX candidates with different surface geometries as well as a summary of prototypic operational conditions. The second task involved optimization of PCHE design with numerical analyses of thermal-hydraulic performances and mechanical integrity. The subsequent task dealt with the development of testing facilities and engineering design of PCHE to be tested in s-CO 2 fluid conditions. The next task involved experimental investigation and validation of the thermal-hydraulic performances and thermal stress distribution of prototype PCHEs manufactured with particular surface geometries. The last task involved an investigation of diffusion bonding process and posttest destructive testing to validate mechanical design methods adopted in the design process. The experimental work utilized the two test facilities at The Ohio State University (OSU) including one existing High-Temperature Helium Test Facility (HTHF) and the newly developed s-CO 2 test loop (STL) facility and s-CO 2 test facility at University of Wisconsin – Madison (UW).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗