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  1. The MFiX Particle-in-Cell Method (MFiX-PIC) Theory Guide

    MFiX (Multiphase Flow with Interphase eXchanges) is an open-source multiphase flow solver developed at the National Energy Technology Laboratory. Within the code, users have access to a single phase or interpenetrating continua-based multiphase two-fluid model (TFM), a discrete element model (DEM), and a particle-in-cell model (PIC). TFM, DEM, and PIC can all be used to create multiphase simulations that include hydrodynamics, chemical reactions, and heat transfer. This document presents the underlying theory for the MFiX-PIC model only. MFiX-PIC is a Lagrangian solids model that tracks the position and trajectory of computational parcels that represent groups of identical spherical particles withinmore » a Eulerian fluid. It is firmly coupled to the fluid flow solver previously described in Musser and Carney and imitates many of the same Lagrangian methods described in Boyalakuntla and Garg et al. Evolving from 1-dimensional and 2-dimensional implementations, the current 3-dimensional PIC formulation most resembles the work of Snider. MFiX-PIC is best suited for industrial-scale, semi-dense multiphase flow simulations where trend is more important than exactness of solution. The methodology utilizes statistical averaging techniques to advance simulations quickly and carries minimal particle-level overhead. Note that solutions do appear very realistic, and verification and validation studies confirm that the methodology predicts accurate flow characteristics. This document follows the notation and variable formats used in equations set forth in Musser and Carney. It is suggested that the active reader, truly trying to digest MFiX-PIC theory, use this document in determined cooperation with Musser and Carney and Snider.« less
  2. The MFiX Particle-in-Cell Method (MFiX-PIC) Theory Guide

    MFiX (Multiphase Flow with Interphase eXchanges) is an open-source multiphase flow solver developed at the National Energy Technology Laboratory. Within the code, users have access to a single phase or interpenetrating continua-based multiphase two-fluid model (TFM), a discrete element model (DEM), and a particle-in-cell model (PIC). TFM, DEM, and PIC can all be used to create multiphase simulations that include hydrodynamics, chemical reactions, and heat transfer.
  3. A PIC Bootstrapping Strategy for Exascale CFD-DEM Simulation

    The exascale computing era comes with the release of MFIX-Exa, a new code for studying gas-particle fluidization using CFD-DEM and PIC models on massively parallel, heterogeneous high-performance computing architectures. However, as compute resources continue to grow in scale and complexity, so too does the impetus to use them efficiently. Here, we propose a novel bootstrapping method to minimize neglected simulation time and cast the approach more broadly among a growing field of multi-fidelity methods.
  4. MFIX-Exa: CFD-DEM simulations of thermodynamics and chemical reactions in multiphase flows

    MFIX-Exa is a CFD-DEM code for the numerical solution of chemically reacting multiphase flows (fluid and solids phases), specifically targeted for flows in complex reactor geometries. The fluid is modeled using a low Mach number formulation with a multicomponent ideal gas equation of state, which is imposed as a constraint of the velocity field. The fluid equations are discretized using an embedded boundary (EB) aware Godunov scheme with an approximate projection. The particles (that constitute the solids phase) are represented by a soft-sphere spring-dashpot model and evolved using a forward Euler method with subcycling. The fluid and particles models aremore » coupled through a volume fraction field in addition to interphase mass, momentum, and energy transfer. The mathematical model and numerical approach are benchmarked against three different verification tests and validated with two separate tests. Also, a scaling analysis is provided. This manuscript represents the current state-of-the-art of MFIX-Exa and describes the major extensions to the previous work presented in Musser et al. (2021), including the Godunov time integration algorithm for the fluid phase and the inclusion of thermodynamics and chemistry modeling to both the fluid and solids phases.« less
  5. Assessment of model parameters in MFiX particle-in-cell approach

    The limitations in numerical treatment of solids-phase in conventional methods like Discrete Element Model and Two-Fluid Model have facilitated the development of alternative techniques such as Particle-In-Cell (PIC). However, a number of parameters are involved in PIC due to its empiricism. In this work, global sensitivity analysis of PIC model parameters is performed under three distinct operating regimes common in chemical engineering applications, viz. settling bed, bubbling fluidized bed and circulating fluidized bed. Simulations were performed using the PIC method in Multiphase Flow with Interphase eXchanges (MFiX) developed by National Energy Technology Laboratory (NETL). A non-intrusive uncertainty quantification (UQ) basedmore » approach is applied using Nodeworks to first construct an adequate surrogate model and then identify the most influential parameters in each case. This knowledge will aid in developing an effective design of experiments and determine optimal parameters through techniques such as deterministic or statistical calibration.« less
  6. Sensitivity Analysis of Particle-In-Cell Modeling Parameters in Settling Bed, Bubbling Fluidized Bed and Circulating Fluidized Bed

    The objective of the work presented is to perform a preliminary sensitivity analysis of particle-in-cell (PIC) model parameters when applied to settling bed, bubbling fluidized bed, and circulating fluidized bed simulations. These examples correspond to widely different flow conditions commonly seen in chemical engineering applications. Simulations were performed using the PIC method in the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developed by the National Energy Technology Laboratory (NETL). As part of the non-intrusive uncertainty quantification (UQ) analysis, simulation campaigns were generated using Nodeworks. Sampling locations or settings for PIC model parameters were determined using the Latin Hypercube method.more » Response surfaces were created using radial basis functions (RBF), and Sobol’ indices were estimated to quantify the influence of model parameters on the quantities of interest (QoI). This study marks a first step towards systematically determining optimal ranges for model parameters used in MFiX-PIC. Based on limited experience, it is expected that these values would depend strongly on flow conditions. Given the complexity of the multiphase flow systems under analysis, a non-intrusive UQ based approach is used to identify the most influential parameters in each case. This prior knowledge will help in proposing an effective design of experiments (DoE) and determine optimal parameters through techniques such as deterministic or Bayesian calibration, which will be pursued in the future.« less
  7. Deterministic Calibration of MFiX-PIC, Part 1: Settling Bed

    The Particle-in-cell (PIC) numerical approach for modeling granular solids in fluid flow has gained significant interest in recent years. Valued for its often shorter time-to-solution, the PIC formulation relies on modeling statistical groupings of particles called parcels in cooperation with a solids stress model to affect local solids velocity. This is in contrast to the discrete element model (DEM) where every particle in a system is modelled individually and directly coupled to local solids velocity through Newtonian mechanics. The U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) develops and maintains Multiphase Flow with Interphase eXchanges (MFiX), a collectionmore » of open-source computational fluid dynamics (CFD) solvers. Included in the MFiX suite are traditional two-fluid model (TFM) and DEM solvers, and a recently added PIC solver (NETL, 2021). In general, PIC methodologies offer an accuracy trade-off in lieu of computational speed; and therefore, it is important to assess the credibility of MFiX-PIC simulations. For this purpose, a systematic verification, validation and uncertainty quantification (VVUQ) effort was initiated at NETL to assess the new PIC solver« less
  8. Fluidization of Group A Glass Particles: Experiments and Preliminary Validation

    This work is aimed at providing reliable high-quality data from fluidization experiments. Geldart Group A glass beads are used as bed material. The fluidizing medium is air at atmospheric pressure which enters the system at 40% relative humidity. The air inlet velocity is varied over a broad range from 2Umf to 26Umf, where the minimum fluidization velocity, Umf, is 0.608 cm/s. There is not a significant change in the mean values of differential pressure; however, there are noticeable trends in their standard deviation values. Preliminary validation studies are performed using the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developedmore » by the National Energy Technology Laboratory (NETL). The results from Eulerian-Eulerian (MFiX-TFM, two-fluid model) and Eulerian-Lagrangian (MFiX-PIC, particle-in-cell) formulations are compared. The work presented in this report highlights the applicability of MFiX-PIC for large-scale applications, and reveals that PIC simulation offers a suitable alternative to TFM simulation when effects due to multiple components or polydispersity are significant. PIC modeling provides a readily extendible framework for such systems. However, PIC models do rely on an empirical closure for inter-particle stress. Some solution discrepancies were evident in MFiX-PIC predictions which require further analysis. As such, the study underlines the need for a systematic approach to quantify the sources of numerical uncertainty within the PIC model. However, even with known empiricism, MFiX-PIC has demonstrated considerable potential in analyzing gas-solid systems. The results obtained are encouraging and warrant further investigation to improve the predictive capability of MFiX-PIC.« less
  9. Fluidization of Group A Glass Particles: Experiments and Preliminary Validation

    This work is aimed at providing reliable high-quality data from fluidization experiments. Geldart Group A glass beads are used as bed material. The fluidizing medium is air at atmospheric pressure which enters the system at 40% relative humidity. The air inlet velocity is varied over a broad range from 2Umf to 26Umf, where the minimum fluidization velocity, Umf, is 0.608 cm/s. There is not a significant change in the mean values of differential pressure; however, there are noticeable trends in their standard deviation values. Preliminary validation studies are performed using the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developedmore » by the National Energy Technology Laboratory (NETL). The results from Eulerian-Eulerian (MFiX-TFM, two-fluid model) and Eulerian-Lagrangian (MFiX-PIC, particle-in-cell) formulations are compared. The work presented in this report highlights the applicability of MFiX-PIC for large-scale applications, and reveals that PIC simulation offers a suitable alternative to TFM simulation when effects due to multiple components or polydispersity are significant. PIC modeling provides a readily extendible framework for such systems. However, PIC models do rely on an empirical closure for inter-particle stress. Some solution discrepancies were evident in MFiX-PIC predictions which require further analysis. As such, the study underlines the need for a systematic approach to quantify the sources of numerical uncertainty within the PIC model. However, even with known empiricism, MFiX-PIC has demonstrated considerable potential in analyzing gas-solid systems. The results obtained are encouraging and warrant further investigation to improve the predictive capability of MFiX-PIC.« less

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10.2172/1630414

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