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DOE OSTI2021

MFIX-Exa: A path toward exascale CFD-DEM simulations

MFIX-Exa is a computational fluid dynamics–discrete element model (CFD-DEM) code designed to run efficiently on current and next-generation supercomputing architectures. MFIX-Exa combines the CFD-DEM expertise embodied in the MFIX code—which was developed at NETL and is used widely in academia and industry—with the modern software framework, AMReX, developed at LBNL. The fundamental physics models follow those of the original MFIX, but the combination of new algorithmic approaches and a new software infrastructure will enable MFIX-Exa to leverage future exascale machines to optimize the modeling and design of multiphase chemical reactors.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Vortex Flow and Cavitation in Liquid Injection: A Comparison between High-Fidelity CFD Simulations and Experimental Visualizations on Transparent Nozzle Replicas

Experimental instantaneous shadowgraph visualizations on transparent glass nozzle replicas of high-pressure fuel injectors have been used to validate a novel in-house high-fidelity LES-VOF multiphase solver, to study the evolution of vortex flow and fuel cavitation. Both experiments and simulations capture the formation of an unsteady vapor structure inside the nozzle volume, which is referred to as 'string-cavitation'; strings are found at the core of the recirculation zones. Furthermore, high-fidelity simulations provide a very detailed insight into the vortex generation in the injector nozzle; strings appear within the time scales that are relevant for fast injection events (on the order of 0.1 milliseconds) and, for the problem under consideration, their generation seems mostly related to the flow pattern in the sac. It is also shown that vortexes interact, merge till they disrupt and favor the temporary inception of shear cavitation.

3-phase LES-VOF solver↗

DOE OSTI2025

Advanced Computational Modeling of High-Level Waste Vitrification at the Hanford Site

The U.S. Department of Energy (DOE) has selected vitrification for stabilizing legacy tank waste at the Hanford site, where radioactive waste from plutonium production was historically stored in underground tanks. This waste will be separated into low-activity waste (LAW) and high-level waste (HLW) fractions and processed at the Waste Treatment and Immobilization Plant (WTP). At WTP, glass melters are used for the vitrification of radioactive tank waste, transforming it into a stable borosilicate glass form for safe long-term storage. The melter vessel is constructed from highly durable and heat-resistant materials, where the vitrification process occurs. The main regions that are modeled are the melt pool, plenum, cold cap, riser/discharge chamber, and surrounding structure with insulation layers. Forced convection induced by air bubblers at the base of the melter ensure uniform temperature distribution and provide heat to the cold cap layer. The cold cap is a region of reacting batch feed that floats on top of the molten glass and is where the batch-to-glass reactions occur. Joule heating provided by electrodes mounted along the vertical walls of the melter and immersed directly in the glass, generates the necessary heat for the net endothermic conversion processes that occur in the cold cap. The high temperatures, radioactivity, and opaque nature of the glass prevent direct observation inside the melters. Therefore, computational models are essential for providing insight into factors that affect melter throughput. Thermocouples in the plenum provide operators with plenum temperature measurements. Operational adjustments include bubbling rate, voltage supplied to the electrodes, feed adjustments, and glass removal rate. Different computational fluid dynamics (CFD) models have been developed, each serving a specific purpose. There are CFD models of different scale melters, as well as models that capture the two-phase flow interfaces of rising bubbles in the molten glass or models with a simplified molten glass region so that the surrounding structure and plenum can be feasibly incorporated. Pilot-scale melter models have been developed to serve as validation of the methods employed in the simulation of the full-scale WTP melters. Models incorporating resolved bubbling are used to develop momentum source terms to implement into a single phase, multi-region, steady-state flow model that is being validated by measured process parameters such as glass production rate, voltage, input power, plenum temperatures, etc. The resolved bubbling model uses the multiphase volume of fluid approach to model the system with a high-resolution interface capturing scheme to maintain sharp interfaces between the molten glass and the air phase. The suite of CFD models is continually being improved to incorporate more realistic physics and achieve faster turnaround time. For example, an incremental controller is implemented to automatically adjust electrode voltage within the simulation to a molten glass set point temperature of 1150°C. Newer models feature improved meshes to ensure conformal meshes between regions and eliminate unnecessary mesh refinement in areas that are not of interest (such as boundary layers in offgas ports). Instead of explicitly modeling the structural, refractory, and insulation layers of the melter, a thermal resistance approach is used with published correlations used for boundary conditions. The development of robust and efficient CFD models will be instrumental in enabling the WTP to successfully fulfill its mission of safely stabilizing legacy nuclear waste.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗

DOE OSTI2022

CFD Simulation of Biomass Pyrolysis Vapor Upgrading over a Pt/TiO 2 Catalyst in Fixed and Moving Beds

This report presents a comprehensive computational fluid dynamics (CFD) study of the biomass pyrolysis vapor phase upgrading and the catalyst regeneration in different reactors under various operational conditions. This study used the open-source software Multiphase Flow with Interphase eXchanges (MFiX), developed at National Energy Technology Laboratory (NETL) for simulating hydrodynamics, heat transfer, and chemical reactions in multiphase systems. This simulation solved the conservation of mass, momentum, energy, species for gas and solid phases with chemical reactions.

09 BIOMASS FUELS↗

DOE OSTI2026

Two-Way Coupled CFD/DEM Simulation of Electromagnetic Heating in a Fluidized Bed Reactor

A set of tools has been developed to couple a multiphase reacting computational fluid dynamics solver (MFIX) with two computational electromagnetic solvers (COMSOL and Elmer). In contrast to several recent investigations, which calculate a single static EM field prior to the CFD calculation, in the present work the electromagnetic field is periodically updated during the simulation. This enables the EM field and associated EM heating predictions to reflect the effects of evolving material properties (temperature, composition, size etc.) and the evolving distribution of material in the system. The present work uses effective medium theory (EMT) for the electromagnetic field calculations since the goal is to apply the tool for industrial scale reacting systems. Predictions using MFIX/COMSOL and MFIX/Elmer are compared to in bed thermocouple measurements from a fluidized bed experiment and recent simulation predictions and recent experiments performed at NETL. The NETL experiments also include packed bed operating conditions. Coupled MFIX/COMSOL simulations at these conditions are compared with similar simulations using only COMSOL to measure errors due to the solver coupling approach.

CFD↗

DOE OSTI2026

Two-Way Coupled CFD/DEM Simulation of Electromagnetic Heating in a Fluidized Bed Reactor - Extended Abstract

CFD↗

DOE OSTI2025

Development of a conduction-based model for analyzing frozen startup of alkali-metal heat pipes

One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.

Microreactor↗

DOE OSTI2021

Temperature Homogeneity under Selective and Localized Microwave Heating in Structured Flow Reactors

Selective heating of different phases of multiphase systems via microwaves can result in energy savings and suppression of side reactions. However, materials properties and operating conditions that maximize temperature gradients are poorly understood. Here we utilize computational fluid dynamics (CFD) computations and temperature measurements in structured flow reactors (monoliths) in a monomodal microwave cavity to assess the temperature difference between the walls and the fluid and develop a simple lumped model to estimate when temperature gradients exist. We also explore the material’s thermal and electrical properties of structured reactors for isothermal catalyst conditions. We propose that CFD simulations can be used as a nonintrusive, predictive tool of temperature homogeneity. Importantly, we demonstrate that localized heating in the bed under several conditions rather than selective heating is responsible for the selectivity enhancement. Furthermore, our results indicate that structured beds made of high thermal conductivity materials avoid arcing and enable temperature homogeneity and low electrical conductivity materials allow microwaves to penetrate the domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Multicomponent gas mixture parametric CFD study of condensation heat transfer in small modular reactor system safety

Safety is always the primary concern for designing and analyzing nuclear reactor systems. The requirements for the safety margin for advanced small modular reactor (SMR) systems are targeted even higher than the conventional commercial large-scale nuclear reactors incorporating the passive and inherent safety systems. The SMR systems are designed with the condensation passive containment cooling system (PCCS), which plays a critical role in removing reactor heat during a steam release accident case. However, the presence of non-condensable gas (NCG), like air, reduces the heat transfer performance. This physics phenomenon becomes multifactorial for nuclear reactor containment during a fuel failure accident case that releases hydrogen gas. Besides, the mixture component of steam-air-hydrogen varies in reactor accident cases, which need simulation and validation keeping parameters of importance. Reviews showed that previous studies for SMR’s PCCCS did not cover the condensation heat transfer (CHT) in the presence of multicomponent NCG mixture parametric computational fluid dynamics (CFD) simulation and validation, making a research gap in the SMR design safety. A comprehensive CHT parametric CFD study was performed for SMR PCCS to fill this research gap. This study used experimental data as simulation 3D physics domain inlet and outlet boundary conditions. However, the wall boundary conditions were constant temperature, curve-fit, and annular coolant for verifying the turbulence models. Parametric simulations were performed, verified, and optimized for steam-NCGs mixtures. The multicomponent gases, multiphase mixtures, and fluid film condensation models were applied with associated turbulence models. The results of the parametric study were evaluated for realistic reactor conditions. Results showed that parametric study provided critical insight about the dependency of multicomponent gas mixture parameters that supports reactor safety design, analysis, and licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

A study on the scale dependence of mixing indices for Eulerian multiphase models

Abstract Mixing can vary based on the scale at which the system is observed, and a mixing index that can capture the features at different length scales is desirable. In this article, we analyze the scale dependence of the mixing indices developed for Eulerian multiphase models. Relevant length scales are distinguished by filtering solid fraction fields. The scale‐dependence study is first done on manufactured fields of solid fraction to assess the performance of the mixing indices. The study is extended to a two‐dimensional CFD simulation of the segregation of a bidisperse gas–solid mixture. The local mixing index performs well in capturing the spatial variation of mixing at different scales. The scale dependence of two global mixing indices is considered in the study, where the state of mixing is defined based on statistical measures. We demonstrate that the choice of measures influences the sensitivity of mixing indices to mixing at different scales.

Nagawkar, Barlev R.↗

DOE OSTI2025

Multi-physics melt pool modeling and process optimization for laser direct energy deposition of Nb-based refractory C103: Defect formation, geometric precision, and process mapping

Recent developments in additive manufacturing (AM) technology have reignited interest in the fabrication of the Nb-based refractory C103 alloy offering solutions to the challenges posed by traditional manufacturing methods. However, the limited numerical and experimental studies on laser direct energy deposition (DED) of C103 have hindered the understanding of the relationships between process parameters and build quality. This has made it challenging to consistently produce parts with the desired quality and microstructure suitable for critical applications. In this study, we focus on optimizing the laser DED process for C103 by employing a hybrid approach that combines experimental techniques and computational fluid dynamics (CFD). This approach facilitates the development of process maps for defect detection and geometric precision. To achieve this, multi-layer C103 samples were fabricated using laser DED under various process parameters, enabling the creation of a process map for defect detection. Additionally, a multi-physics, multiphase simulation framework was developed within a high-performance computing (HPC) environment to establish process maps for geometric precision. Using these process maps, printability windows were identified for achieving both the desired geometric accuracy and defect-free prints. It was observed that prints with a power-to-velocity (P/V) ratio close to unity resulted in defect-free outcomes. This study provides a foundation for reducing design lead time and rejected parts, ultimately optimizing the laser DED process for C103.

Defect formation and geometric precision↗

DOE OSTI2022

A Review of Computational Capabilities and Requirements in High-Resolution Simulation of Nonferrous Pyrometallurgical Furnaces

We report that tremendous progress has been made over the last several decades in improving the pyrometallurgical processing routes of nonferrous metals, such as aluminum, copper, and lead. Advances in the numerical modeling of pyrometallurgical processes has aided in these improvements by providing a better understanding of the complex transport phenomena occurring in modern furnaces. However, there is a need for a comprehensive discussion of the numerical modeling of a primary and a secondary nonferrous pyrometallurgical furnaces. This review provides such a discussion by surveying recent attempts at capturing the physico-chemical phenomena occurring within these furnaces, including gas-phase combustion, melting/smelting, and multiphase heat- and mass-transfer with the molten phases. This work then identifies a complete set of approaches for simulating these types of furnaces and provides recommendations for applying high-resolution numerical tools towards full-furnace simulation. By identifying gaps in the current state of the art, this review offers suggestions for future developments in commercial codebases, outlining the path to fulfilling the promise of CFD-enabled pyrometallurgy.

36 MATERIALS SCIENCE↗

DOE OSTI2025

CFD Simulation of Aerobic Gas Fermentation to Enable Commercial Conversion of CO 2 into Aquaculture and Animal Feed: Cooperative Research and Development (Final Report)

NovoNutrients’ fermentation technology uses energy from hydrogen to transform industrial CO2 emissions into premium animal feed ingredients and other valuable products. A single NovoNutrients’ commercial manufacturing plant will capture and convert over 200,000 tons/yr of CO2 into over 100,000 tons/yr of high-protein feed. Key to the rapid and widespread deployment of the technology is maximization of its productivity and energy efficiency. Robust, physically based computational models of the technology will significantly increase productivity and efficiency, accelerating NovoNutrients’ technology to manufacturing scale. NREL has unique capabilities for creating and running such computational models. NREL's existing aerobic bioreaction computational fluid dynamics (CFD) models will be adapted to NovoNutrients’ gas fermentation (CO2, H2, O2) technology. The multiphysics CFD simulations require thousands of high-performance computing (HPC) node hours to simulate the complex geometries and contents of NovoNutrients’ industrial bioreactors. The experimentally validated CFD models were used to identify optimally efficient and productive bioreactor designs and operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Very small-scale, segregating-fluidized-bed experiments: A dataset for CFD-DEM validation and uncertainty quantification

IWe report fluidization experiments were conducted on a small scale and with a rapid response (short duration) to enable corresponding simulations at low-computational cost. Rise times are reported for four or fewer polyethylene particles (intruders) in an air-fluidized bed of ~5000 group D glass beads. Experimental inputs were completely characterized—particle properties, system dimensions and operating conditions—which is necessary for validating computational fluid mechanics (CFD)-discrete element method (DEM) including a comprehensive uncertainty quantification (UQ) analysis. Input uncertainties are reported as bounds or cumulative distribution functions of measured values. The staggering number of simulations required to complete a UQ analysis (~O[10 4 ] simulations corresponding to ~5 uncertain inputs) motivates this study. These segregating-bed experiments are designed to permit analogous CFD-DEM simulations to complete in less than a day on a single (~2.5 GHz) computational processor unit (CPU). Segregation times are reported for several operating conditions, intruder sizes, and initial configurations, providing a rich dataset for numerical model testing, validation and UQ.

42 ENGINEERING↗

DOE OSTI2021

An Investigation of the Effects of Volume Fraction on Drag Coefficient of Non-Spherical Particles Using PR-DNS

Prediction of the drag coefficient is required in gas-particle multiphase flow modeling and simulation. Experimental data and correlations on the fixed-bed system of spherical particles with high volume fractions for various possible arrangements are available in the literature. However, the effect of volume fraction on the drag coefficient of non-spherical particles is not well studied. In solving the momentum equation, the volume fraction plays a vital role in determining the flow resistances. In this paper, we study the impact of volume fraction in the range of 0.069 to 0.65 on the drag coefficient using the computational fluid dynamics (CFD) simulation of air for Reynold number in the range of 10 to 10000 using particle resolved direct numerical solution (PR-DNS). Regular non-spherical particles such as a cube, tetrahedron, and spheroids are used in this study since their single particle’s drag coefficient data are available in the literature for comparison. For this work, the simulations are carried out in the Ansys Fluent using polyhedral mesh, which consumes significantly less computational time and power. The study showed the sphericity and volume fraction have significant impact on the bed pressure drop and average drag coefficient of the particles in the bed especially in high Reynolds number regime. The bed of the spheroid experiences the lowest drag being the most streamlined particle, and the particles with the edges result in a large drag coefficient due to flow separation at the discontinuity. The vector plots verify this behavior where large wake regions are observed behind the tetrahedron particle.

Mahyawansi, Pratik↗

DOE OSTI2024

MFiX Development Updates

This presentation discusses recent developments of the Multiphase Flow with Interphase eXchanges (MFiX) software. A brief review of all modeling approaches along with their cost versus accuracy is provided to guide users when selecting a model for a given application. The main new features of the past five official releases of MFiX are described. Improvement in chemistry management allow for easier simulation setup, and faster simulation speed. Progress in the implementation of a thin-wall boundary condition is presented. The major new model development over the past year is the release of the Glued Sphere Particle model (GSP), where component spheres are combined together to represent non-spherical particles. The integration of Machine Learning (ML) workflow in the CFD process is discussed with two applications: a surrogate model for stiff chemistry and the development of a PIC stress model using ML.

Dietiker, Jeff↗

DOE OSTI2023

Multiphysics Computational-Fluid-Dynamics (CFD) for Design and Scale-Up of Gas Bioreactors that Utilize CO2

Gas fermentation technology offers sustainable and high carbon-efficiency routes to fuels and chemicals. However, efficiently delivering low-solubility substrate gases to production-scale bioreactors is a significant technical challenge that could limit productivity. We perform fundamental and applied multiphysics computational fluid dynamics (CFD) research targeting specific challenges of gas delivery in fermentation systems that utilize varied gas-compositions, for e.g. CO2/CO/CH4/H2 substrates: bubble dynamics, coupled mass-transfer and reaction, that can lead to optimal reactor designs at scale. This work will support BETO goals towards greenhouse gas reduction, derisking technologies toward commercialization/deployment and sustainable-aviation-fuel synthesis targets.

BIOMASS FUELS↗

DOE OSTI2021

High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace

The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗