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DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗

DOE OSTI2013

Pore-Scale Simulation of Intragranular Diffusion: Effects of Incomplete Mixing on Macroscopic Manifestations

Diffusive mass transfer into and out of intragranular micropores ("intragranular diffusion") plays an important role in the large-scale transport of some groundwater contaminants. We are interested in understanding the combined effect of pore-scale advection and intragranular diffusion on solute transport at the effective porous medium scale. To study this problem, we have developed a three-dimensional pore-scale model of fluid flow and solute transport that incorporates diffusion into and out of intragranular pore spaces. Our model is based on the Smoothed Particle Hydrodynamics (SPH) simulation method, which represents fluid and solid phases by a mesh-free particle discretization. In the pore spaces, fluid flow is simulated by discretizing the Navier-Stokes equations using the SPH approach. Solute transport is represented by advection, diffusion within the fluid phase, and diffusion between the fluid and solid phases. Our model is implemented on large-scale parallel computing hardware, allowing us to simulate millions of computational particles and represent fully three-dimensional systems of pores and grains with arbitrarily complex physical geometry. We have used this model system to perform numerical experiments using various model porous media systems, which allows us to draw comparisons between macroscopic measures computed from the pore-scale simulations (such as breakthrough curves) and those predicted by macroscopic formulations that assume complete mixing over the representative volume. In this paper we present results of 3D simulations of pore-scale flow and transport, including cases with and without intragranular diffusion, in two model porous media, one with randomly-packed uniform spherical grains and a second with randomly-packed spheres drawn from a binary grain size distribution. Breakthrough curves were computed from the 3D simulations at various transport distances. Comparable breakthrough curves were computed using 1D macroscopic models with parameters determined independently to the degree possible. Based on comparisons of the pore-scale and macroscopic model results, we draw two primary conclusions. First, non-Fickian behavior is persistent and ubiquitous at the scales considered, and most cases are better represented by a multi-rate mass transfer model even when there is no distinct secondary porosity (i.e., no intragranular diffusion). This suggests that diffusive mass transfer processes between preferential flow paths and relatively immobile zones within the primary porosity may have significant impact on transport, particular in low-concentration tails. Second, the application of mass transfer rate parameters based on an assumption of well-mixed concentrations at the pore-scale tend to overestimate the amount of mass transfer that occurs in heterogeneous pore geometries in which preferential flow leads to incomplete pore-scale lateral mixing.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2018

Changes in ENSO amplitude under climate warming and cooling

The response of ENSO amplitude to climate warming and cooling is investigated using the Community Earth System Model (CESM), in which the warming and cooling scenarios are designed by adding heat fluxes of equal amplitude but opposite sign onto the ocean surface, respectively. Results show that the warming induces an increase of the ENSO amplitude but the cooling gives rise to a decrease of the ENSO amplitude, and these changes are robust in statistics. A mixed layer heat budget analysis finds that the increasing (decreasing) SST tendency under climate warming (cooling) is mainly due to an enhancement (weakening) of dynamical feedback processes over the equatorial Pacific, including zonal advective (ZA) feedback, meridional advective (MA) feedback, thermocline (TH) feedback, and Ekman (EK) feedback. As the climate warms, a wind anomaly of the same magnitude across the equatorial Pacific can induce a stronger zonal current change in the east (i.e., a stronger ZA feedback), which in turn produces a greater weakening of upwelling (i.e., a stronger EK feedback) and thus a larger thermocline change (i.e., a stronger TH feedback). In response to the climate warming, in addition, a slowdown of the subtropical cells (STCs) will result in a narrower meridional width of SST anomaly around the equator and thus a stronger MA feedback. And vice versa for the cooling case. Bjerknes linear stability (BJ) index is also evaluated for the linear stability of ENSO, with significantly larger (smaller) BJ index found for the warming (cooling) case.

ENSO amplitude, Climate Warming, Climate cooling, ↗

DOE OSTI2018

Kinetic Simulation of Collisional Magnetized Plasmas with Semi-implicit Time Integration

Plasmas with varying collisionalities occur in many applications, such as tokamak edge regions, where the flows are characterized by significant variations in density and temperature. While a kinetic model is necessary for weakly-collisional high-temperature plasmas, high collisionality in colder regions render the equations numerically stiff due to disparate time scales. In this study, we propose an implicit–explicit algorithm for such cases, where the collisional term is integrated implicitly in time, while the advective term is integrated explicitly in time, thus allowing time step sizes that are comparable to the advective time scales. This partitioning results in a more efficient algorithm than those using explicit time integrators, where the time step sizes are constrained by the stiff collisional time scales. Finally, we implement semi-implicit additive Runge–Kutta methods in COGENT, a high-order finite-volume gyrokinetic code and test the accuracy, convergence, and computational cost of these semi-implicit methods for test cases with highly-collisional plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

An Experimental Method to Measure Gaseous Diffusivity in Tight and Partially Saturated Porous Media via Continuously Monitored Mass Spectrometry

Detection of radioxenon and radioargon produced by underground nuclear explosions is one of the primary methods by which the Comprehensive Nuclear-Test–Ban Treaty (CTBT) monitors for nuclear activities. However, transport of these noble gases to the surface via barometric pumping is a complex process relying on advective and diffusive processes in a fractured porous medium to bring detectable levels to the surface. To better understand this process, experimental measurements of noble gas and chemical surrogate diffusivity in relevant lithologies are necessary. However, measurement of noble gas diffusivity in tight or partially saturated porous media is challenging due to the transparent nature of noble gases, the lengthy diffusion times, and difficulty maintaining consistent water saturation. Here, the quasi-steady-state Ney–Armistead method is modified to accommodate continuous gas sampling via effusive flow to a mass spectrometer. An analytical solution accounting for the cumulative sampling losses and induced advective flow is then derived. Experimental results appear in good agreement with the proposed theory, suggesting the presence of retained groundwater reduces the effective diffusivity of the gas tracers by 10–1000 times. Finally, by using a mass spectrometer, the method described herein is applicable to a broad range of gas species and porous media.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Phenomenological Model of Nonlinear Dynamics and Deterministic Chaotic Gas Migration in Bentonite: Experimental Evidence and Diagnostic Parameters

Understanding gas migration in compacted clay materials, e.g., bentonite and claystone, is important for the design and performance assessment of an engineered barrier system of a radioactive waste repository system, as well as many practical applications. Existing field and laboratory data on gas migration processes in low-permeability clay materials demonstrate the complexity of flow and transport processes, including various types of instabilities, caused by nonlinear dynamics of coupled processes of liquid–gas exchange, dilation, fracturing, fracture healing, etc., which cannot be described by classical models of fluid dynamics in porous media. We here show that the complexity of gas migration processes can be explained using a phenomenological concept of nonlinear dynamics and deterministic chaos theory. To do so, we analyzed gas pressure and gas influx (i.e., input) and outflux (i.e., output), recorded during the gas injection experiment in the compact Mx80-D bentonite sample, and calculated a set of the diagnostic parameters of nonlinear dynamics and chaos, such a global embedding dimension, a correlation dimension, an information dimension, and a spectrum of Lyapunov exponents, as well as plotted 2D and 3D pseudo-phase-space strange attractors, based on the univariate influx and outflux time series data. These results indicate the presence of phenomena of low-dimensional deterministic chaotic behavior of gas migration in bentonite. In particular, during the onset of gas influx in the bentonite core, before the breakthrough, the development of gas flow pathways is characterized by the process of chaotic gas diffusion. After the breakthrough, with inlet-to-outlet movement of gas, the prevailing process is chaotic advection. During the final phase of the experiment, with no influx to the sample, the relaxation pattern of gas outflux is resumed back to a process of chaotic diffusion. The types of data analysis and a proposed phenomenological model can be used to establish the basic principles of experimental data-gathering, modeling predictions, and a research design.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Derivation of heterogeneous material distributions and their sensitivity to HM-coupled two-phase flow models exemplified with the LASGIT experiment

Abstract Advective gas transport in bentonite, a possible buffer material in repositories for radioactive materials, is difficult to simulate in numerical continuum models, partly due to the complicated microstructure of bentonite. To generate reliable models of repositories nevertheless, spatially distributed heterogeneous material properties can be used to allow localization of gas flow. In this study, a pore-size-dependent stochastic approach of the gas entry pressure is derived from Mercury Intrusion Porosimetry, which is used to replicate measurements from the LASGIT experiment. In addition, three benchmark tests are simulated to investigate the dependence of heterogeneous distributions of material properties on the mesh discretization, the temporal dependence, and the coupling between the processes influenced by the heterogeneous parameters. The numerical modeling results of the LASGIT experiment show that the onset of gas flow into the system and the subsequent increase in pressure and stress can be well reproduced using heterogeneous distributions. Compared to a model with homogeneous material properties, heterogeneous distributions may allow the generation of dilatancy-controlled microfractures—an important feature with regard to the advective gas flow in bentonites. However, it can be observed that the heterogeneous distributions in LASGIT are less significant, as technical gaps or differences in material types could have a greater impact.

Environmental Sciences & Ecology↗

DOE OSTI2019

A MUSCL-SCNI approach for meshfree modeling of shock waves in fluids

Here, a stable and nodally integrated meshfree formulation for modeling shock waves in fluids is developed. The reproducing kernel approximation is employed to discretize the conservation equations for compressible flow, and a flux vector splitting approach is applied to allow proper numerical treatments for the advection and pressure parts, respectively, based on the characteristics of each flux term. To capture the essential shock physics in fluids, including the Rankine–Hugoniot jump conditions and the entropy condition, local Riemann enrichment is introduced under the stabilized conforming nodal integration (SCNI) framework. Meanwhile, numerical instabilities associated with the advection flux are eliminated by adopting a modified upwind scheme. To further enhance accuracy, a MUSCL-type method is introduced in conjunction with an oscillation limiter to avoid Gibbs phenomenon and ensure monotonic piecewise linear reconstruction in the smooth region. The present meshfree formulation is free from tunable artificial parameters and is capable of capturing shock and rarefaction waves without over/undershoots. Finally, several numerical examples are analyzed to demonstrate the effectiveness of the proposed MUSCL-SCNI approach in meshfree modeling of complex shock phenomena, including shock diffraction, shock–vortex interaction, and high energy explosion processes.

42 ENGINEERING↗

DOE OSTI2013

Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under conditions in which one or more nutrients were limiting. The fitted Monod kinetic model was also applied at the Darcy scale; that is, to simulate average reaction processes at the scale of the entire pore-scale model domain. As we expected, even under excess nutrient conditions for which the Monod and genome-scale models predicted equal reaction rates at the pore scale, the Monod model over-predicted the rates of biomass growth and iron and acetate utilization when applied at the Darcy scale. This discrepancy is caused by an inherent assumption of perfect mixing over the Darcy-scale domain, which is clearly violated in the pore-scale models. These results help to explain the need to modify the flux constraint parameters in order to match observations in previous applications of the genome-scale model at larger scales. These results also motivate further investigation of quantitative multi-scale relationships between fundamental behavior at the pore scale (where genome-scale models are appropriately applied) and observed behavior at larger scales (where predictions of reactive transport phenomena are needed).

bioremediation↗

DOE OSTI2019

Coupled supercritical CO2 dissolution and water flow in pore-scale micromodels

Dissolution trapping is one of the most important mechanisms for geological carbon storage (GCS). Recent laboratory and field experiments have shown non-equilibrium dissolution of supercritical CO2 (scCO2) and coupled scCO2 dissolution and water flow, i.e., scCO2 dissolution at local pores/pore throats creating new water-flow paths, which in turn enhance dissolution by increased advection and interfacial area. However, the impacts of pore-scale characteristics on these coupled processes have not been investigated. In this study, imbibition and dissolution experiments were conducted under 40°C and 9?MPa using a homogeneous/isotropic hexagonal micromodel, two homogeneous elliptical micromodels with low or high anisotropy, and a heterogeneous sandstone-analog micromodel. The four micromodels, initially saturated with deionized (DI)-water, were drained by injecting scCO2 to establish a stable scCO2 saturation. DI water was then injected at different rates with logCa (the capillary number) ranging from -6.56 to -4.34. Results show that bypass of scCO2 by displacing water is the dominant mechanism contributing to the residual CO2 trapping, triggered by heterogeneity in pore characteristics or pore-scale scCO2-water distribution. Bypass can be enhanced by pore heterogeneity or reduced by increasing transverse permeability, resulting in relatively low (<2% of CO2 solubility) or high (9–13% of CO2 solubility) dissolved CO2 concentration in displacing water. The overall dissolution of residual scCO2 increases with decreasing Ca, and approaches to their solubility at low Ca value with sufficient residence time. This main trend is similar to a capillary desaturation curve that represents the relationship between the residual saturation and Ca. Spatially, dissolution initiates along the boundary of bypassed scCO2 cluster(s) in a non-equilibrium manner, and the coupling of water flow and dissolution occurs which fragments the bypassed scCO2 clusters and enhance scCO2 dissolution.

Chang, Chun↗

DOE OSTI2021

A Computational Information Criterion for Particle-Tracking with Sparse or Noisy Data

Traditional probabilistic methods for the simulation of advection-diffusion equations (ADEs) often overlook the entropic contribution of the discretization, e.g., the number of particles, within associated numerical methods. Many times, the gain in accuracy of a highly discretized numerical model is outweighed by its associated computational costs or the noise within the data. Herein, we address the question of how many particles are needed in a simulation to best approximate and estimate parameters in one-dimensional advective-diffusive transport. To do so, we use the well-known Akaike Information Criterion (AIC) and a recently-developed correction called the Computational Information Criterion (COMIC) to guide the model selection process. Random-walk and mass-transfer particle tracking methods are employed to solve the model equations at various levels of discretization. Numerical results demonstrate that the COMIC provides an optimal number of particles that can describe a more efficient model in terms of parameter estimation and model prediction compared to the model selected by the AIC even when the data is sparse or noisy, the sampling volume is not uniform throughout the physical domain, or the error distribution of the data is non-IID Gaussian.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

On the eigenstructure of spherical harmonic equations for radiative transport

The spherical harmonic equations for radiative transport are a linear, hyperbolic set of balance laws that describe the state of a system of particles as they advect through and collide with a material medium. For regimes in which the collisionality of the system is light to moderate, significant qualitative differences have been observed between solutions, based on whether the angular approximation used to derive the equations occurs in a subspace of even or odd degree. This difference can be traced back to the eigenstructure of the coefficient matrices in the advection operator of the hyperbolic system. In this paper, we use classical properties of the spherical harmonics to examine this structure. In particular, we show how elements in the null space of the coefficient matrices depend on the parity of the spherical harmonic approximation and we relate these results to observed differences in even and odd expansions.

Garrett, Charles K.↗

DOE OSTI2024

Weak-form latent space dynamics identification

Recent work in data-driven modeling has demonstrated that a weak formulation of model equations enhances the noise robustness of a wide range of computational methods. In this paper, we demonstrate the power of the weak form to enhance the LaSDI (Latent Space Dynamics Identification) algorithm, a recently developed data-driven reduced order modeling technique. We introduce a weak form-based version WLaSDI (Weak-form Latent Space Dynamics Identification). WLaSDI first compresses data, then projects onto the test functions and learns the local latent space models. Notably, WLaSDI demonstrates significantly enhanced robustness to noise. With WLaSDI, the local latent space is obtained using weak-form equation learning techniques. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form guarantees a robust and precise latent space recovery, hence allowing for a fast, robust, and accurate simulation. We demonstrate the efficacy of WLaSDI vs. LaSDI on several common benchmark examples including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in the case of 1D inviscid Burgers' simulations with the addition of up to 100% Gaussian white noise, the relative error remains consistently below 6% for WLaSDI, while it can exceed 10,000% for LaSDI. Similarly, for radial advection simulations, the relative errors stay below 15% for WLaSDI, in stark contrast to the potential errors of up to 10,000% with LaSDI. Moreover, speedups of several orders of magnitude can be obtained with WLaSDI. For example applying WLaSDI to 1D Burgers' yields a 140X speedup compared to the corresponding full order model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

A hybridized discontinuous Galerkin method on mapped deforming domains

Here in this paper we present a hybridized discontinuous Galerkin (HDG) discretization for unsteady simulations of convection-dominated flows on mapped deforming domains. Mesh deformation is achieved through an arbitrary Lagrangian-Eulerian transformation with an analytical mapping. We present details of this transformation applied to the HDG system of equations, with focus on the auxiliary gradient equation, viscous stabilization, and output calculation. We discuss conditions under which optimal unsteady output convergence rates can be attained, and we show that both HDG and discontinuous Galerkin (DG) achieve these rates in advection-dominated flows. Results for scalar advection-diffusion and the Euler equations verify the implementation of the mesh motion mapping for both discretizations, show that HDG and DG yield similar results on a given mesh, and demonstrate differences in output convergence rates depending on the choice of HDG viscous stabilization. We note that such similar results bode well for HDG, which has fewer globally-coupled degrees of freedom compared to DG. A simulation of the unsteady compressible Navier-Stokes equations demonstrates again very similar results for HDG and DG and illustrates a pitfall of using steady-state adapted meshes for accurate unsteady simulations.

42 ENGINEERING↗

DOE OSTI2020

An open source fast fluid dynamics model for data center thermal management

Although computational fluid dynamics (CFD) has been widely adopted to improve data center thermal management, the high computational demand limits its applications, such as multivariate optimal design and operation. Fast fluid dynamics (FFD), which has been applied for fast airflow simulation, shows great potential. However, few research applied FFD for optimal design and operation of data center thermal management. This research improves the FFD model for data centers and conducts a comprehensive evaluation and demonstration. First, the FFD model is improved by solving the advection and diffusion equations together using an upwind scheme instead of a semi-Lagrangian advection solver in the conventional FFD model. Second, new features for data centers are added, such as a pressure correction method to simulate plenum airflow and dynamic boundary conditions for IT racks. The new FFD model is first validated with two indoor environment cases and the results show that the new FFD model has slightly better overall prediction accuracy and faster speed compared to the conventional FFD model. It is also observed that both FFD models achieve acceptable accuracy, except for a few localized disparities with experimental data, which might be due to simplified handling of turbulence viscosity near the boundaries. Furthermore, validation with a real data center shows that the FFD model achieves a similar level of accuracy as CFD when compared to the experimental measurements with some level of uncertainties. It is then demonstrated for data center optimal design and operation, which saves 53.4–58.8% of annual energy while still meeting the thermal requirements. In conclusion, with a much faster speed and comparable accuracy compared to CFD, the FFD model parallelized on a graphics processing unit is promising for practical model-based data center early design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Toward more mechanistic representations of biogeochemical processes in river networks: Implementation and demonstration of a multiscale model

A recently introduced multiscale model for representing the effects of small-scale hyporheic-zone biogeochemical processes is extended from the reach scale to river network scales. The model uses advection-dispersion-reaction equations for the channel network and one-dimensional advection-reaction subgrid models for the hyporheic zone. We summarize implementation in the integrated surface/subsurface hydrology modeling system Amanzi-ATS. The extension uses topologically defined meshes to represent stream/river networks and associates a hyporheic subgrid model with each channel grid cell. Biogeochemical reaction modeling capability residing in community software is accessed through an application programming interface. The implementation is verified against independent numerical solutions on a single reach. Mesh convergence studies show that commonly used semi-distributed representations can introduce significant spatial discretization error. Denitrification of farm runoff in a subbasin of the Portage River Basin in Ohio, USA is used to demonstrate the general-purpose reactive transport capability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Effect of particle characteristics, kinetics and transport phenomena on the prediction of particle mass loss and products yields during biomass fast pyrolysis

Here a low computational cost model for the pyrolysis of biomass anisotropic particles was used to study the effect of thermal conductivity of the particle, CRECK kinetic scheme implementation, intraparticle secondary reactions, heats of reaction, and advection on particle conversion prediction. The model considers a shrinking anisotropic cylindrical particle with biomass pseudo-components, the appearance of liquid intermediates, intra-particle mass and heat transport and secondary reactions of volatiles. The model was validated against oak and birchwood single particle experiments. More accurate predictions for mass loss evolution are found when considering the change of the particle thermal conductivity anisotropy with conversion and the temperature dependency of the thermal conductivities of the biomass and the gas phase, compared to ignoring these phenomena. The CRECK biomass pyrolysis reaction scheme provides insights into the effect of biomass composition on the evolution of the liquid intermediate phase allowing future studies about the presence of heavy compounds in the bio-oil and other phenomena such as aerosol ejection. Secondary intraparticle vapor phase reactions showed a negligible effect in volatiles conversion while heterogeneous reactions slightly overestimate its conversion. Heats of reaction and product advection are important for accurate prediction of particle mass loss.

09 BIOMASS FUELS↗

DOE OSTI2015

Filament capturing with the Multimaterial Moment-of-Fluid method

A novel method for capturing two-dimensional, thin, under-resolved material configurations, known as “filaments,” is presented in the context of interface reconstruction. This technique uses a partitioning procedure to detect disconnected regions of material in the advective preimage of a cell (indicative of a filament) and makes use of the existing functionality of the Multimaterial Moment-of-Fluid interface reconstruction method to accurately capture the under-resolved feature, while exactly conserving volume. An algorithm for Adaptive Mesh Refinement in the presence of filaments is developed so that refinement is introduced only near the tips of filaments and where the Moment-of-Fluid reconstruction error is still large. Comparison to the standard Moment-of-Fluid method is made. It is demonstrated that using filament capturing at a given resolution yields gains in accuracy comparable to introducing an additional level of mesh refinement at significantly lower cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗