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At least 19 records

Machine learning accelerated discrete element modeling of granular flows

Granular flows are widely encountered in many industrial processes and natural phenomena. Discrete Element Modeling (DEM) is a useful tool for understanding and troubleshooting devices, which handle granular materials. However, its applicability is significantly limited by the huge computational cost associated with detecting and computing collisions. In this research, the computation speed of DEM was accelerated by orders of magnitude using a convolutional neural network to replace the direct calculation of particle-particle and particle-boundary collisions. The MFiX software was used to generate the training and testing dataset. Additionally, a GPU accelerated TensorFlow model was used to train the neural network and test the results. The model fluctuations caused by different training steps were reduced with a multi-scale loss function. The accuracy was improved with more frames within one training step. The modeling of a rotating drum and a hopper demonstrated the accuracy and efficiency of this machine learning accelerated DEM in the simulation of granular flows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Micromechanical origin of heat transfer to granular flow

Heat transfer across a granular flow is comprised of two resistances in series : near the wall and within the bulk particle bed, neither of which is well understood due to the lack of experimental probes to separate their respective contribution. Here, we use a frequency modulated photothermal technique to separately quantify the thermal resistances in the near-wall and the bulk bed regions of particles in flowing states. Compared to the stationary state, the flowing leads to a higher near-wall resistance and a lower thermal conductivity of bulk beds. As a result, coupled with discrete element method simulation, we show that the near-wall resistance can be explained by particle diffusion in granular flows.

14 SOLAR ENERGY↗

Constitutive Relation in Transitional Granular Flows

To study the constitutive behavior of granular materials, the presence of gravity is detrimental. Although empirical relations have been obtained for engineering designs to control granular flows on Earth, it is not known how well these Earthbound relations can be used in another gravity field. Fundamental understanding must be derived to reliably design for granular flows in space exploration. There are two extremes of granular flows of which significant amount of knowledge is available. One deals with a dense and quasi-static situation where the deformation rate nearly vanishes. The other deals with dilute and rapidly fluctuating grain velocities where particle inertia dominates. This project, funded by the NASA Microgravity Fluid Physics Program, aims to study this transitional regime via physical experiments and computer simulations. A conceptual model has been established as described below. There are two natural time scales in a granular flow. One is the travel time between two consecutive collisions and the other is the duration of a collision contact. At a very low shear-rate, the shear-induced particle velocity is low. Hence the travel time between collisions is longer than the contact time between colliding particles. Binary collisions prevail. As the shear-rate increases, the traveling time between collisions reduces and the probability of multiple collisions goes up. These particle groups disperse shortly after and new groups form. When shear-rate is further increased, clusters grow in size due to an increasing chance for free particles to join before groups have the time to disperse. The maximum cluster size may depend on the global concentration and material properties. As the solid concentration approaches zero, the cluster size goes to one particle diameter. The maximum possible cluster size under any condition is the container size, provided that the shear flow is inside a container. The critical shear-rates that dictate the initiation of the multiple contacts, and the size and lifetime of the collision clusters, are functions of the concentration also. A 'regime' theory has been proposed by Babic et al. This theory suggested that both the solid concentration, C, and the non-dimensional shear-rate, B, are important in determining the regimes of the granular constitutive law. Additional information is included in the original extended abstract.

Shen, Hayley H.↗

Pseudo-viscous modeling of transport in dense granular flows for thermal energy storage applications

Dense, granular flows were examined to effectively capture and model bulk viscous properties in thin packed beds. A modified Couette cell with particle image velocimetry was used to experimentally determine pseudo-viscosity properties of four particulate media with varying morphologies: (1) iron oxide-coated SiO 2 particles, (2) CARBOBEAD CP30-60 particles, (3) CARBOBEAD CP40-100 particles, and (4) Al 2 O 3 beads. The pseudo-viscosity functions were fitted using a power law to correlate the measured shear stress as a function of measured shear rate. The pseudo-viscous functions were used as inputs to computation fluid dynamics models for a single-phase viscous fluid to predict granular flow profiles. Steady-state free surface velocity profiles at angular velocities <7 rad/s predicted by the model were in good agreement with the experimental particle image velocimetry measurements, resulting in Pearson correlation coefficients of 0.97 for iron-oxide coated SiO 2 particles and 0.95 for CP30-60 particles. As a result, this alternative approach to measuring pseudo-viscous properties under shearing and modeling bulk transport behavior of granular flow using computation fluid dynamics model offered significant reduction in computational load compared to discrete element methods.

14 SOLAR ENERGY↗

Martian Slope Streaks and Gullies: Origins as Dry Granular Flows

Streaks and gullies are common on Martian slopes, and are geologically young; slope streaks have formed during the last few years of Mars Global Surveyor imaging. Both slope streaks and gullies involve flow of granular material, but it is not clear whether liquid water (or another suspending agent) was involved. The possibility that liquid water was involved makes gullies and slope streaks important for understanding Mars recent climate and for the hope of extant life near its surface. Here, we show that significant features of slope streaks and gullies are consistent with dry flows of granular material. Liquid water may not be required.

Treiman, A. H.↗

An adaptive, data-driven multiscale approach for dense granular flows

The accuracy of coarse-grained continuum models of dense granular flows is limited by the lack of high-fidelity closure models for granular rheology. One approach to addressing this issue, referred to as the hierarchical multiscale method, is to use a high-fidelity fine-grained model to compute the closure terms needed by the coarse-grained model. The difficulty with this approach is that the overall model can become computationally intractable due to the high computational cost of the high-fidelity model. In this work, we describe a multiscale modeling approach for dense granular flows that utilizes neural networks trained using high-fidelity discrete element method (DEM) simulations to approximate the constitutive granular rheology for a continuum incompressible flow model. Our approach leverages an ensemble of neural networks to estimate predictive uncertainty that allows us to determine whether the rheology at a given point is accurately represented by the neural network model. Additional DEM simulations are only performed when needed, minimizing the number of additional DEM simulations required when updating the rheology. This adaptive coupling significantly reduces the overall computational cost of the approach while controlling the error. In addition, the neural networks are customized to learn regularized rheological behavior to ensure well-posedness of the continuum solution. We first validate the approach using two-dimensional steady-state and decelerating inclined flows. We then demonstrate the efficiency of our approach by modeling three-dimensional sub-aerial granular column collapse for varying initial column aspect ratios, where our multiscale method compares well with the computationally expensive computational fluid dynamics (CFD)-DEM simulation.

Dense granular flows↗

Modeling of dense reactive granular flows

A general model of dense granular flows derived elsewhere is here assessed to understand the validity of some of the assumptions embedded in the derivation.

granular↗

Experimental characterization of extreme temperature granular flows for solar thermal energy transport and storage

High-temperature, dense granular flows along an inclined plane were considered for solar thermal energy transport and storage with sintered bauxite particles. A series of experiments was performed for particle inlet temperatures of ~ 200, 400, 600, and 800 °C to understand the mechanisms of granular flows at extreme temperatures. Mass flow rates were measured using a load cell and free-surface velocities were measured and computed using particle image velocimetry. Surface temperatures were measured using infrared cameras. A significant decrease in steady-state particle mass flow rate was observed with increasing temperature due to changing flow properties. A decrease in bulk particle free-surface velocities was observed at higher temperatures. Free-surface velocity measurement error between experiments were within 20% of the average. The particle surface temperatures decreased from inlet to outlet with larger gradients at higher temperatures observed due to increasing convection and radiative heat losses. Here, a decrease in temperature was observed along the side walls due to a decrease in particle velocities.

14 SOLAR ENERGY↗

Impact of Janssen effect on thermal transport in granular flow

Using a modulated photothermal radiometry (MPR) technique capable of measuring thermal transport in particle beds, we find asymptotically increasing effective thermal conductivity and decreasing near-wall thermal resistance along gravity-driven downward granular flows through a 1-meter-long narrow vertical channel owing to the Janssen effect. The Janssen effect is confirmed by similar asymptotic trends from particle bed apparent mass measurements as well as separate MPR heat transfer measurements on stationary particle beds under compression at different heights of the channel with and without pressure screening. Furthermore, local heat transfer coefficient along the 1-meter-long channel was modeled based on measured spatially resolved thermal conductivity and near-wall thermal resistance due to the Janssen effect. This work reveals for the first time the impact of the over century-old Janssen effect on heat transfer in granular media. Furthermore, the results from this work can lead to a better understanding of heat transfer in granular flow.

14 SOLAR ENERGY↗

Grain size reduction in granular flows of spheres - The effects of critical impact energy

Methods employed to derive recent kinetic theories for rapid noncomminuting granular flows are extended to homogeneous flows in which a fraction of the repeated collisions produce tiny fractures on the particles' peripheries and gradually reduce their effective diameters. The theory consists of balance equations for mass, momentum, and energy, as well as constitutive relations for the presence tensor and collisional rates of mass and energy lost. The work of Richman and Chou (1989) is improved by incorporating into the constitutive theory the critical impact energy below which no mass loss occurs in a binary collision. The theory is applied to granular shear flows and, for fixed shear rates, predicts the time variations of the solid fraction granular temperature, and induced stresses, as well as their extreme sensitivities to small changes in the critical impact energy.

Richman, M. W.↗

SPH Modeling of Biomass Granular Flow: Engineering Application in Hoppers and Augers

Numerical modeling of granular biomass material flow in handling operations is indispensable to decipher flow upsets, commonly manifested as clogging and jamming in hoppers and augers. With a computational tool developed based on smoothed particle hydrodynamics (SPH), we simulated the hopper flow and auger feeding of six granular biomass materials. The good agreement between the experimental and numerical flow rates demonstrated the capability of the developed SPH solver in modeling the complicated flow of granular biomass materials. Further, the impact of physical and numerical parameters is investigated, and the major results show that the hopper flow pattern is controlled by shear band evolution; hopper clogging is collectively influenced by the opening size, wall friction, and material packing, and the impact of material compressibility on the auger feed rate is minimal. These parametric studies validate the solver’s robustness in simulating biomass flow in handling equipment and demonstrate that the SPH computational tool can provide insights about granular flow mechanics to facilitate handling equipment design and optimize handling operations.

09 BIOMASS FUELS↗

Shear rate dependency on flowing granular biomass material

The commercialization of bioenergy has been significantly limited by various material handling issues due to the poor flowability of granular biomass materials. A good understanding of flow physics and robust constitutive models to predict flow behavior across multiple regimes are essential to address these issues. In this study, we investigated the multi-regime flow behavior of loblolly pine chips, a widely used bioenergy feedstock, through comprehensive inclined plane flow experiments and simulations. A quasi-static hypoplastic model and a cross-regime Drucker-Prager-µ(I) model were calibrated and validated against the physical experiments to investigate the quasi-static and dense flow behavior. The results show that for granular biomass, 1) plane flow (iso-thickness along the plane) exists within a smaller range of inclination while heap flow (varying thickness along the plane) exists within a broader range of inclination, as compared with conventional granular materials (e.g., glass beads); 2) the scaling law of granular biomass flowing on an inclined plane (Froude Number versus dimensionless thickness) forms a bi-linear trend with the turning point governed by the quasi-static and dense flow regimes; 3) the multi-regime DP-µ(I) model can capture the flow behavior in both regimes well at the cost of extra calibration. In conclusion, these findings advance the scientific understanding of the multi-regime flow behavior of granular biomass materials and shed light on formulating novel constitutive models to assist granular biomass handling in the bioenergy industry.

09 BIOMASS FUELS↗

Assessment of Models of Chemically Reacting Granular Flows

A report presents an assessment of a general mathematical model of dense, chemically reacting granular flows like those in fluidized beds used to pyrolize biomass. The model incorporates submodels that have been described in several NASA Tech Briefs articles, including "Generalized Mathematical Model of Pyrolysis of Biomass" (NPO-20068) NASA Tech Briefs, Vol. 22, No. 2 (February 1998), page 60; "Model of Pyrolysis of Biomass in a Fluidized-Bed Reactor" (NPO-20708), NASA Tech Briefs, Vol. 25, No. 6 (June 2001), page 59; and "Model of Fluidized Bed Containing Reacting Solids and Gases" (NPO- 30163), which appears elsewhere in this issue. The model was used to perform computational simulations in a test case of pyrolysis in a reactor containing sand and biomass (i.e., plant material) particles through which passes a flow of hot nitrogen. The boundary conditions and other parameters were selected for the test case to enable assessment of the validity of some assumptions incorporated into submodels of granular stresses, granular thermal conductivity, and heating of particles. The results of the simulation are interpreted as partly affirming the assumptions in some respects and indicating the need for refinements of the assumptions and the affected submodels in other respects.

Bellan, Josette↗

Dense granular flows with MFIX-Exa

This report extends the linear spring dashpot collision model the discrete element method available in MFIX-Exa to include static a static tangential friction force. Additionally, two rolling friction models frequently used in the literature are also implemented. The governing equations are provided with an emphasis on the new terms. The new model is validated by comparison to existing experimental data of single particle oblique collisions. The model is then tested on three dense granular flow problems: the formation of static piles, the discharge from a flat-bottom hopper and the self-induced granular Rayleigh-Taylor instability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

BDEM (Discrete-element-simulator for high-solids granular flows) [SWR-22-72]

BDEM is a discrete element method based simulation tool developed specifically for modeling high-solids granular flows that include polydispersity, heat-transfer, moving boundaries and chemistry. Our solver provides facilities for simulating spherical/non-spherical particles with modified contact and friction models in complex dynamic geometries defined using level-sets or triangulated files. The solver is developed on top of NREL's open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Simulations at the scale of several millions to billion particles have been performed using this software on large scale computing resources. This software can be applied to non-reacting solids dominant flows in silos, hoppers and screw conveyors as well as in high temperature reacting systems such as screw kilns and auger reactors.

Sitaraman, Hariswaran↗

SPH modeling of biomass granular flow: Theoretical implementation and experimental validation

The commercialization of biomass-derived energy is impeded by flowability challenges arising from the feeding and handling of granular biomass materials in full-scale biorefineries. To overcome these obstacles, a robust and accurate model to simulate the flow of granular biomass is indispensable. However, conventional mesh-based numerical codes are limited by inherent mesh distortion in simulating large deformation that commonly occurs in granular biomass handling. Here, in this study, we propose a graphics processing unit (GPU)-accelerated meshless Smoothed Particle Hydrodynamics (SPH) code to model the flow of granular biomass materials. A modified void ratio-based mass conversation, a hybrid particle-to-particle/surface frictional boundary treatment, and a hypoplastic constitutive model are implemented. Four numerical examples, an elastic block sliding on inclined planes, sand column collapse, Angle of Repose, and axial compression tests for pine chips, were simulated using the developed SPH code. The results demonstrate good agreement between numerical predictions and analytical and experimental data for all four examples, validating the SPH code and increasing confidence that it can be applied to simulate more complex granular biomass handling processes, such as hopper feeding or auger conveyance.

09 BIOMASS FUELS↗

Initial Validation of a Gas-Granular Flow Solver Using a Subscale, Reduced Pressure Plume Surface Interaction Ground Test

With NASA’s goal to land the next humans on the lunar surface in the next few years, it is vitally important to have a better understanding of the plume surface interaction (PSI) between the landing vehicles and the lunar regolith. The Fluid Dynamics Branch at NASA/MSFC has previously used the gas-granular flow solver Loci/GGFS to qualitatively predict crater formation due to PSI effects in a lunar (near vacuum) ambient environment. In this paper, validation of Loci/GGFS crater width and depth predictions in ambient near-lunar conditions are provided using experimental data collected at MSFC during the Physics-Focused Ground Test 1 (PFGT-1) campaign in 2022. To observe sensitivity to soil models, simulations were conducted with both monodisperse glass bead (MGB) and BP-1 lunar regolith simulant soil models in Loci/GGFS. Crater depth and width comparisons are made with PFGT-1 Run 56, which used BP-1 soil. The Loci/GGFS BP-1 soil model performed slightly better with a mean predicted crater depth within 10% of the experiment. Both soil models predicted crater width within 10%. Cratering occurred more quickly with the MGB soil model. Mesh and spatial order sensitivity are also examined for the BP-1 soil model.

Validation↗

Validation Assessment of Loci/GGFS Gas Granular Flow Solver Predictions of Ejecta from Physics Focused Ground Test

NASA is preparing to return humans to the Moon to establish a sustained Lunar presence through the Artemis program. One area of concern for Lunar landers is the plume surface interaction (PSI) environment that poses several risks during a propulsive landing. Understanding the PSI environment caused by the landers is therefore important to designing successful landing missions. Towards this end, a two-phase, gas granular flow solver, Loci/GGFS, has been developed to predict the cratering and ejecta physics expected during a Lunar landing. The focus of this paper is on a validation assessment of Loci/GGFS predictions of ejecta with monodisperse glass beads (MGB). The validation assessment is performed with respect to the Physics Focused Ground Test 1 (PFGT1) conducted at NASA Marshall Space Flight Center (MSFC) in 2021. It is found that Loci/GGFS predicts similar initial cratering and ejecta features, with predictions of average velocities that are within 25% of experimental values.

Plume Surface Interaction↗