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DOE OSTI2020

A conservative phase-space moving-grid strategy for a 1D-2V Vlasov–Fokker–Planck Solver

In this work, we develop a conservative configuration- and velocity-space (i.e., phase-space) moving-grid strategy for the Vlasov–Fokker–Planck (VFP) equation in a planar geometry. The velocity-space grid is normalized and shifted in terms of the thermal speed and the bulk-fluid velocity, respectively. The configuration-space grid is moved according to a mesh-motion-partial-differential equation (MMPDE), which equidistributes a monitor function that is inversely proportional to the gradient-length scales of the macroscopic plasma quantities. The resulting inertial terms in the transformed VFP equations are discretized to ensure the discrete conservation of mass, momentum, and energy. To satisfy the discrete conservation theorems in the presence of phase-space mesh motion, we employ the method of discrete nonlinear constraints – explored in previous studies – but the underlying symmetries are determined in a much more efficient manner than before. The conservative grid-adaptivity strategy provides an efficient scheme that resolves important physical structures in the phase-space while controlling the computational complexity at all times. We demonstrate the favorable features of the proposed algorithm through a set of test cases of increasing complexity. The problems test independent components of the algorithms, as well as the integrated capability on settings relevant to inertial confinement fusion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Field theory and a structure-preserving geometric particle-in-cell algorithm for drift wave instability and turbulence

A field theory and the associated structure-preserving geometric particle-in-cell (PIC) algorithm are developed to study low frequency electrostatic perturbations with fully kinetic ions and adiabatic electrons in magnetized plasmas. The algorithm is constructed by geometrically discretizing the field theory using discrete exterior calculus, high-order Whitney interpolation forms, and non-canonical Hamiltonian splitting method. The discretization preserves the non-canonical symplectic structure of the particle-field system, as well as the electromagnetic gauge symmetry. As a result, the algorithm is charge-conserving and possesses long-term conservation properties. Because drift wave turbulence and anomalous transport intrinsically involve multi time-scales, simulation studies using fully kinetic particles demand algorithms with long-term accuracy and fidelity. The structure-preserving geometric PIC algorithm developed adequately serves this purpose. The algorithm has been implemented in the code, tested and benchmarked using the examples of ion Bernstein waves and drift waves. We apply the algorithm to study the ion temperature gradient (ITG) instability and turbulence in a 2D slab geometry. Simulation results show that at the early stage of the turbulence, the energy diffusion is between the Bohm scaling and gyro-Bohm scaling. Finally, at later time, the observed diffusion is closer to the gyro-Bohm scaling, and density blobs generated by the rupture of unstable modes are the prominent structures of the fully developed ITG turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Customized multi-group cross section generation with NJOY for discrete ordinates X-ray computed tomography and radiography simulation - 25589

The purpose of this work was to explore the creation of photo-atomic multi-group cross section libraries to be used with a software package DOCTORS (Discrete Ordinates Computed Tomography and Radiography Simulator). This software solves the linear Boltzmann equation using the discrete ordinates method. To create these libraries, NJOY2016 was used, creating both fine and broad energy multi-group cross section files. The cross section's accuracy was tested against an equivalent Monte Carlo simulation using MCNP6. Two simulation geometries were used. The first, a cylindrical water phantom with a single source projection placed in front, simulating an X-ray radiography. The second used the same water phantom with 16 cone beam sources placed evenly around the phantom to simulate a computed tomography (CT) scan. The accuracy of the fine energy multi-group cross sections when used in DOCTORS has been verified. The accuracy of the broad energy multigroup cross sections when used in DOCTORS shows that more work must be done before they can be used reliably. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2012

Open-source MFIX-DEM software for gas-solids flows: Part II — Validation studies

With rapid advancements in computer hardware and numerical algorithms, computational fluid dynamics (CFD) has been increasingly employed as a useful tool for investigating the complex hydrodynamics inherent in multiphase flows. An important step during the development of a CFD model and prior to its application is conducting careful and comprehensive verification and validation studies. Accordingly, efforts to verify and validate the open-source MFIX-DEM software, which can be used for simulating the gas–solids flow using an Eulerian reference frame for the continuum fluid and a Lagrangian discrete framework (Discrete Element Method) for the particles, have been made at the National Energy Technology Laboratory (NETL). In part I of this paper, extensive verification studies were presented and in this part, detailed validation studies of MFIX-DEM are presented. A series of test cases covering a range of gas–solids flow applications were conducted. In particular the numerical results for the random packing of a binary particle mixture, the repose angle of a sandpile formed during a side charge process, velocity, granular temperature, and voidage profiles from a bounded granular shear flow, lateral voidage and velocity profiles from a monodisperse bubbling fluidized bed, lateral velocity profiles from a spouted bed, and the dynamics of segregation of a binary mixture in a bubbling bed were compared with available experimental data, and in some instances with empirical correlations. In addition, sensitivity studies were conducted for various parameters to quantify the error in the numerical simulation.

42 ENGINEERING↗

DOE OSTI2022

Reverse scaling of a bonded-sphere DEM model: Formulation and application to lignocellulosic biomass microstructures

We explore scaling laws for adapting a bonded-sphere discrete element method (BS-DEM) model developed for woody structural mechanics at the millimeter scale to model the mechanics of realistic lignocellulosic biomass microstructures. Two scaling approaches, i.e., the reverse coarse graining (RCG) and equivalent bulk behavior (EBB), are proposed based on the classical mechanics principles and assessed in the single-particle compression and rectangular cuboid block tension tests. The EBB approach is recommended for BS-DEM models with general 3D geometries and is applied to simulate the microindentation test on a realistic microscale pinewood specimen. Simulations are performed to elucidate the impact of specimen thickness and loading position on the specimen’s force–deformation behavior. Furthermore, the range of Young’s modulus obtained from the calibrated BS-DEM simulations can match the experimental measurements. This is the first-of-its-kind study that has explored scale-bridging modeling approaches in biomass micromechanics and has proposed solutions based on BS-DEM models in the microscale.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

A Review of Computational Models for the Flow of Milled Biomass Part I: Discrete-Particle Models

Biomass is a renewable and sustainable energy resource. Current design of biomass handling and feeding equipment leverage both experiments and numerical modeling. This paper reviews the state-of-the-art discrete element methods (DEM) for the flow of milled biomass (Part I), accompanied by a comprehensive review on continuum-based computational models (Part II). The present review on DEM is primarily focused on the features and suitability of various particle shape models for different types of milled biomass because particle shape is the predominant attribute controlling the flow behavior of complex-shaped granular material. The general strengths and weaknesses in the applicability of those models for the milled biomass modeling are summarized. In particular, comments are provided to balance the numerical model capabilities and the computational cost for the development of DEM models. To our best knowledge, this is the first-of-its-kind review on DEM specifically for biomass. Our study indicates that the current DEM models require further development, calibration, and validation based on a deep understanding of biomass particle contact mechanics and experimental data support before they can be reliably used for predictive simulations in handling and feeding systems.

42 ENGINEERING↗

DOE OSTI2018

Dynamic simulation of powder packing structure for powder bed additive manufacturing

Here, powder packing structure is a critical parameter of powder bed-based additive manufacturing (AM). Experimental characterization of powder is typically limited to measuring bulk properties, whereas many numerical models of AM powder packing are based on geometrical consideration without accounting for particle-to-particle interactions. In the present paper, the powder packing dynamics is simulated using a discrete element method (DEM)-based model that solves the mechanical contact forces and moments between individual particles. As DEM uses explicit time integration, a main challenge in modeling dynamics of metallic powder packing is the need for extremely fine time increment size (e.g., in the order of 1 ns for a 10-μm-diameter particle). The effect of mass scaling, employed for speeding up the calculation, on the simulation results is examined in a test case of powder particles packed inside a box container. The calculated packing density for two different particle size distributions is validated against independent literature data for laser powder bed AM with AISI 316L stainless steel powder. The sensitivity of key input parameters (e.g., friction coefficient) is further evaluated in this test case. The powder packing model is then applied to a practical situation of binder jet AM involving rolling of multiple layers of IN718 powder particles onto a powder bed, for which the calculated packing density is also validated with independent literature data.

42 ENGINEERING↗

DOE OSTI2017

Enhancing the physical modeling capability of open-source MFIX-DEM software for handling particle size polydispersity: Implementation and validation

Multiphase flows are ubiquitous in many industrial processes. The inherent coupling of different phases poses many unique challenges in predicting and effectively controlling these processes. Hence, computational modeling and simulation offers a viable approach to overcome these challenges. Here in this study, we present recent development efforts for enhancing the physical modeling capabilities of an open-source computational modeling tool for real life industrial multiphase processes by enabling particle-size polydispersity and demonstrating with an associated validation study. The proposed implementation was performed in MFIX open-source framework due to its unique feature of tightly integrated computational fluid dynamics and discrete element method solvers for simulating coupled continuum fluid and granular flows. We have implemented the polydispersity feature in a minimally invasive way and provided means to allow easy specification of an arbitrary particle size distribution function, which also enables the user to easily handle an arbitrary number of solid phases, each possessing a distinct arbitrary particle-size distribution. To establish the credibility of improvements, we have carried out a preliminary verification and validation (V&V) study for the polydispersity feature by employing a hopper bin discharge problem, which is frequently encountered in industrial applications. Specifically, two types of micro-glass beads with distinct size distributions are used to fill the hopper in two possible packing arrangements, i.e., well-mixed and layered configurations, with varying mass (particle number) ratios. The experimentally obtained discharge dynamics (e.g., normalized discharge mass fraction for one of the phases versus the overall discharge mass fraction) for different systems is found to be in excellent agreement with the corresponding simulation results.

42 ENGINEERING↗

NASA NTRS2022

Investigating Particle-Particle Electrostatic Effects on Charged Lunar Dust Transport via Discrete Element Modeling

NASA surface exploration missions have always seen negative effects of dust including the Apollo missions. The astronaut-witnessed unusual behavior of the dust particles that surround the vehicle after engine cutoff has the potential to have more of an influence on surface systems dust loading than the high velocity lunar rocket plume ejecta in the landing process. The levitation and transport of the fine components of regolith on lunar surface has been linked to electrostatic effects and electric field, but so far there is no accurate model considering the inter-particle electrostatic interactions, especially when the particles are charged by rocket plume or other mechanical interactions due to exploration activities. This study is proposed to investigate the dynamics of charged lunar regolith with a discrete element method (DEM) approach focusing on the inter-particle interactions and contact charge transfer. The grain dynamics is coupled with mechanical and electrical particle interactions, and both short- and long-range interactions between spherical particles are incorporated. A tribo-charging model based on instantaneous collisions between particles is adopted and validated by comparing the simulation results to existing experimental data. Sensitivity analysis is conducted to quantify the effects of initial charge, tribo-charging, and E-field on transport of lunar dust based on JSC-1 simulants with a radius of 50 lm. DEM simulations are also conducted in a near realistic lunar environment with the estimations of initial conditions that shows the difference in position and velocity distributions between charged particles and uncharged particles. The results indicate that the charged dust particles have higher dispersion of position and velocity by several orders of magnitude due to electrostatic effects. This provides a potential explanation for the phenomena of the approximately 30 s dust lofting following Apollo Lunar Module landing.

Lunar dust↗

DOE OSTI2025

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗

DOE OSTI2020

A numerical study of particle jetting in a dense particle bed driven by an air-blast

In this work, the particle jetting behavior in a blast-driven dense particle bed is studied at early times. Four-way coupled Euler–Lagrange simulations are performed using a high-order discontinuous Galerkin spectral element solver coupled with a high-order Lagrangian particle solver, wherein the inter-particle collisions are resolved using a discrete element method collision model. Following the experiments of Rodriguez et al. [“Formation of particle jetting in a cylindrical shock tube,” Shock Waves 23(6), 619–634 (2013)] and the simulations of Osnes et al. [“Numerical simulation of particle jet formation induced by shock wave acceleration in a Hele-Shaw cell,” Shock Waves 28(3), 451–461 (2018)], the simulations are performed in a quasi-two-dimensional cylindrical geometry (Hele-Shaw cell). Parametric studies are carried out to assess the impact of the coefficient of restitution and the strength of the incident shock on the particle jetting behavior. The deposition of vorticity through a multiphase (gas–particle) analog of Richtmyer–Meshkov instability is observed to play a crucial role in channeling the particles into well-defined jets at the outer edge of the particle bed. This is confirmed by the presence of vortex pairs around the outer jets. Furthermore, the effect of the relaxation of the relative velocity between the two phases on the vorticity generation is explored by analyzing the correlation between the radial velocity of particles and the radial velocity of the gas at the particle location.

42 ENGINEERING↗

DOE OSTI2013

Reducing uncertainty in personnel dosimetry calculations in the VHTR plant using MAVRIC

This work analyzes the efficacy of the MAVRIC sequence of the Scale 6.1 code package with respect to the accuracy of results and the ability to utilize large-memory, parallel machines. MAVRIC implements the hybrid FW-CADIS methodology to solve neutron and photon transport for shielding applications. Using the discrete ordinates method to solve the Boltzmann transport equation, an importance map is generated which MAVRIC then uses to bias a stochastic Monte Carlo simulation. The MAVRIC sequence is applied to generate neutron and photon dose rate distributions of improved accuracy in a model of a proposed VHTR power plant. Problems like this one, with a size on the order of magnitude of a nuclear power plant, require a prohibitive amount of memory to store complete importance maps. The issue is addressed by refining the mesh in areas around the source through the detector regions, while leaving a coarse mesh elsewhere. Additionally through the use of parallel computing, the angular flux can be expanded in higher quadrature sets, which leads to a better importance map while requiring no extra memory requirements during the Monte Carlo portion of the sequence. The final Monte Carlo simulations can be run concurrently on several machines with results combined after the fact, emulating parallelism that is not yet available in MAVRIC sequence. Using a combination of strategies, the MAVRIC sequence is shown to be able to scale across available computational resources, allowing the user to more quickly obtain Monte Carlo results with lower relative uncertainties in large, deep-penetration shielding problems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Discrete element simulation of Pebble Bed Reactors on graphics processing units

Prediction of pebble positions in a Pebble Bed Reactor (PBR) is necessary for both reactor physics and thermal hydraulics simulations as the arrangement of pebbles has a significant impact on the resulting core power, coolant flow, and fuel temperature. Knowledge of pebble movement as the fuel is cycled through the core is also critical for predicting the fuel residence time and subsequently, the fuel burnup. Simulation with the Discrete Element Method (DEM) can provide knowledge of both the fuel packing and the fuel movement during cycling. Previous works that have performed 3D full-core DEM simulation of PBRs have used simplified models that neglect reflector wall features. This work employs a graphics processing unit (GPU)-enabled DEM code, Project Chrono, to analyze the differences in pebble packing and pebble velocities between a simplified smooth PBR reflector and a more realistic reflector that includes circular wall features. Additionally, a sensitivity study is performed on the depth of the wall features to ensure that crystallization is prevented. Project Chrono is also validated for PBR cycling applications using experimental data. It is found that wall features with a depth of at least 0.5 pebble diameters significantly reduce crystallization in the near-wall region, leading to discrepancies in both packing fraction and pebble velocity in this region compared to the simplified reflector models. These discrepancies are found to lead to roughly a 5–10% difference in the prediction of the near-wall porosity and a 10% difference in the prediction of the velocity of pebbles near the wall. As a result of these discrepancies, it is suggested that future DEM simulations of PBRs include wall features to reduce modeling errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Near-field radiative heat transfer between irregularly shaped dielectric particles modeled with the discrete system Green's function method

Near-field radiative heat transfer (NFRHT) between irregularly shaped dielectric particles made of SiO 2 and morphology characterized by Gaussian random spheres is studied. Particles are modeled using the discrete system Green's function (DSGF) approach, which is a volume integral numerical method based on fluctuational electrodynamics. This method is applicable to finite, three-dimensional objects, and all system interactions are defined independent of thermal excitation by a generalized system Green's function. The DSGF method is deemed suitable to model NFRHT between irregularly shaped particles after verification against the analytical solution for chains of two and three SiO 2 spheres. The NFRHT results reveal that geometric irregularity in particles leads to a reduction of the total conductance from that of comparable perfect spheres at vacuum separation distances smaller than the particle size, a regime in which NFRHT is a surface phenomenon. At vacuum separation distances larger than the particle size, NFRHT becomes a volumetric process, and the total conductance between irregularly shaped particles converges to that of comparable perfect spheres. Spectral analysis reveals, however, that particle irregularity leads to damping and broadening of resonances at all separation distances, thereby highlighting the importance of the DSGF method for spectral engineering in the near field. The reduced spectral coherence when particle size is larger than the vacuum separation distance is attributed to coupling of surface phonon-polaritons within the randomly generated, distorted particle features. For particle size smaller than the vacuum separation distance, resonance broadening and damping are linked with the multiple localized surface phonon modes supported by the composite spherical harmonic morphologies of the Gaussian random spheres. In conclusion, this paper has direct implications for thermal management of packed particle systems, with applications in radiative property control, electronics, energy conversion, and nanomanufacturing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Deformation of Granular Material under Continuous Rotation of Stress Principal Axes

The mechanical response of granular material to the rotation of stress principal axes is an issue of both practical and theoretical importance in soil mechanics. This study used a two-dimensional (2D) discrete-element method (DEM) simulation to investigate the deformation of granular material under the continuous rotation of stress principal axes while maintaining fixed principal stress values. The results show that under such rotation, the deformation can exceed that caused by fixed principal stress axes cyclic biaxial compression with a maximum deviatoric stress ratio that equals the fixed stress ratio during rotation. The volumetric strain was found to be contractive overall while oscillating within each load cycle for specimens with significant fabric anisotropy. Here, the initial fabric-anisotropy orientation was found to have little influence on the overall evolution of volumetric strain, although it was found to affect the development of shear strain. During the cycles of rotation of initial stress principal axes, the dilatancy of granular material, in the contractive direction, was found to be dominated by the evolving orientation of the major principal stress axis in reference to the initial major principal stress axis during anisotropic consolidation, and the influence of the initial fabric-anisotropy orientation was found to be trivial. As stress rotation continued, the influence of the relative orientation between stress and fabric became prominent, causing the material to dilate when the major principal stress axis rotated from the normal of the bedding plane to being perpendicular to it and causing contraction during the other half of the cycle.

58 GEOSCIENCES↗

DOE OSTI2022

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗

DOE OSTI2026

DEM Modeling and Validation of Pebble Bed Packing Using Chrono::GPU

Accurate prediction of pebble packing structure is important for pebble bed reactors because the spatial distribution of void fraction directly affects coolant flow, pressure drop, heat transfer, and neutronic behavior. However, experimentally validated DEM studies that directly evaluate local void-fraction structure in reactor-relevant pebble beds remain limited. In this work, the pebble bed experiment conducted at Missouri University of Science and Technology is simulated using the graphics processing unit (GPU)-based discrete element method (DEM) code Chrono::GPU. The study focuses on evaluating the ability of Chrono::GPU to reproduce the packing arrangement and void-fraction distribution of a randomly packed spherical pebble bed. The DEM results are first verified against established radial void-fraction correlations, including the Mueller and Vortmeyer-Schuster models, to assess the predicted bulk porosity, near-wall behavior, and oscillatory packing structure. The simulation is then verified against reference DEM data and validated against gamma-ray computed tomography (CT) experimental data at three axial locations. The Chrono::GPU results reproduce the main features of the experimental packing, including the high void fraction near the wall, the first near-wall trough, and the damped oscillatory radial profile caused by wall-induced ordering. Quantitative comparison with DEM data and the CT-based radial profiles shows good agreement, with mean absolute errors on the order of 0.07 and root-mean-square errors below 0.09 for the averaged profiles. These results demonstrate that Chrono::GPU can accurately capture the void-fraction structure of spherical pebble beds and provides a reliable DEM framework for future pebble bed reactor packing, recycling, and thermal-hydraulic studies.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Parameter Determination of the Non-Local Granular Fluidity Model for Wood Chips by Comparison to Well-Defined Experimental Flow Systems

Unlike simple liquids and gases, the bulk flow and transport of granular materials remain poorly understood by physicists and pose many problems for engineers in designing and operating bulk-solids handling equipment. Discrete element methods (DEM) are currently considered the state-of-the-art for simulating the flow of granular materials, but DEM is limited in system size to about a few million particles due to high computational costs, even when run on current high-performance computing architectures. Continuum models are needed to simulate the flows of bulk solids in industrial-scale vessels and equipment, e.g., grain silos and coal-ash disposal piles. The focus of this work is the so-called nonlocal granular fluidity (NLGF) model that has been previously shown to reproduce observed nonlocal behaviors that arise when granular phenomena occur on length scales that are near the scale of the system geometry, e.g., the jamming of hopper outlets and the stop-height of piles on inclines [PNAS, 110(17), 6730-6735]. We have implemented the NLGF constitutive model in OpenFOAM CFD software, performed simulations of well-defined flow systems, and compared the results to experimental data. Experimental systems include a ring-shear tester, pile formation, flow on an incline, and discharge of a hopper. The tested material was loblolly pine wood chips that were milled and sieved to a size range of roughly 0.05-0.25 inches in diameter. The NLGF model parameters were tuned to achieve reasonable agreement between simulation and experimental results. Further, we evaluate the mapping between measurable material properties (bulk friction angle, particle-particle friction, compressibility, grain diameter, etc.) with NLGF model parameters, some of which have direct analogs (friction parameters and grain diameter) while others are constructs of the model (nonlocal amplitude and timescale of fluidity evolution).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗