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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Flow and arrest in stressed granular materials

Flowing granular materials often abruptly arrest if not driven by sufficient applied stresses. Such abrupt cessation of motion can be economically expensive in industrial materials handling and processing, and is significantly consequential in intermittent geophysical phenomena such as landslides and earthquakes. Using discrete element simulations, we calculate states of steady flow and arrest for granular materials under the conditions of constant applied pressure and shear stress, which are also most relevant in practice. Here the material can dilate or compact, and flow or arrest, in response to the applied stress. Our simulations highlight that under external stress, the intrinsic response of granular materials is characterized by uniquely-defined steady states of flow or arrest, which are highly sensitive to interparticle friction. While the flowing states can be equivalently characterized by volume fraction, coordination number or internal stress ratio, to characterize the states of shear arrest, one needs to also consider the structural anisotropy in the contact network. Here, we highlight the role of dilation in the flow-arrest transition, and discuss our findings in the context of rheological transitions in granular materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Modified kinetic theory applied to the shear flows of granular materials

Here, granular materials are characterized by large collections of discrete particles, where the particle-particle interactions are significantly more important than the particle-fluid interactions. The current kinetic theory captures fairly accurately the granular flow behavior in the dilute case, when only binary interactions are significant, but is not accurate at all in the dense flow regime, where multi-particle interactions and contacts must be modeled. To improve the kinetic theory results for granular flows in the dense flow regime, we propose a Modified Kinetic Theory (MKT) model that utilizes the contact duration or cut-off time to account for the complex particle-particle interactions in the dense regime. The contact duration model, also called TC model, is originally proposed by Luding and McNamara to solve the inelastic collapse issue existing in the Inelastic Hard Sphere (IHS) model. This model defines a cut-off time t c such that dissipation is not counted if the time between two consecutive contacts is less than t c . As shown in their study, the use of a cut-off time t c can also reduce the dissipation during multi-particle contacts. In this paper we relate the TC model with the Discrete Element Method (DEM) by choosing the cut-off time t c to be the duration of contact calculated from the linear-spring-dashpot soft-sphere model of the DEM. We examine two types of granular flows: simple shear flow and the plane shear flow, and compare the results of the classical Kinetic Theory (KT) model, the present MKT model, and the DEM model. Here, we show that the MKT model entails a significant improvement over the KT model for simple shear flows at inertial regimes. With the MKT model the calculations are close to the DEM results at solid fractions as high as 0.57. Even for the plane shear flows, where shear rate and solid fraction are inhomogeneous, the results of the MKT model agree very well with the DEM results.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Applicability of discrete element method with spherical and clumped particles for constitutive study of granular materials

Discrete element method (DEM) has been intensively used to study the constitutive behaviour of granular materials. However, to what extent a real granular material can be reproduced by virtual DEM simulations remains unclear. This study attempts to answer this question by comparing DEM simulations with typical features of experimental granular materials. Three groups of models with spherical and clumped particles are investigated from four perspectives: (i) deviatoric stress and volumetric behaviour; (ii) critical state behaviour; (iii) stress-dilatancy relationship; and (iv) the evolution of principal stress ratio against axial strain. The results demonstrate that DEM with spherical or clumped particles is capable of qualitatively describing macroscopic deviatoric stress responses, volumetric behaviour, and critical state behaviour observed in experiments for granular materials. On the other hand, some qualitative deviations between experiments and the investigated DEM simulations are also observed, in terms of the stress-dilatancy behaviour and principal stress ratio against axial strain, which are proven to be critical for constitutive modelling. The results demonstrate that DEM with spherical or clumped particles may not necessarily fully capture experimental features of granular materials even from a qualitative perspective. It is thus encouraged to thoroughly validate DEM with experiments when developing constitutive models based on DEM observations.

58 GEOSCIENCES↗
DOE OSTI2016

Meso-scale framework for modeling granular material using computed tomography

Numerical modeling of unconsolidated granular materials is comprised of multiple nonlinear phenomena. Accurately capturing these phenomena, including grain deformation and intergranular forces depends on resolving contact regions several orders of magnitude smaller than the grain size. Here, we investigate a method for capturing the morphology of the individual particles using computed X-ray and neutron tomography, which allows for accurate characterization of the interaction between grains. The ability of these numerical approaches to determine stress concentrations at grain contacts is important in order to capture catastrophic splitting of individual grains, which has been shown to play a key role in the plastic behavior of the granular material on the continuum level. Discretization approaches, including mesh refinement and finite element type selection are presented to capture high stress concentrations at contact points between grains. The effect of a grain’s coordination number on the stress concentrations is also investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Calibrating a finite-strain phase-field model of fracture for bonded granular materials with uncertainty quantification

To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, graphics processing unit-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.

36 MATERIALS SCIENCE↗
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 OSTI2017

Dynamic induced softening in frictional granular materials investigated by discrete-element-method simulation

A granular system composed of frictional glass beads is simulated here using the discrete element method. The intergrain forces are based on the Hertz contact law in the normal direction with frictional tangential force. The damping due to collision is also accounted for. Systems are loaded at various stresses and their quasistatic elastic moduli are characterized. Each system is subjected to an extensive dynamic testing protocol by measuring the resonant response to a broad range of ac drive amplitudes and frequencies via a set of diagnostic strains. The system, linear at small ac drive amplitudes, has resonance frequencies that shift downward (i.e., modulus softening) with increased ac drive amplitude. Detailed testing shows that the slipping contact ratio does not contribute significantly to this dynamic modulus softening, but the coordination number is strongly correlated to this reduction. This suggests that the softening arises from the extended structural change via break and remake of contacts during the rearrangement of bead positions driven by the ac amplitude.

58 GEOSCIENCES↗
DOE OSTI2024

Machine Learning Aided Modeling of Granular Materials: A Review

Artificial intelligence (AI) has become a buzzy word since Google’s AlphaGo beat a world champion in 2017. In the past five years, machine learning as a subset of the broader category of AI has obtained considerable attention in the research community of granular materials. This work offers a detailed review of the recent advances in machine learning-aided studies of granular materials from the particle-particle interaction at the grain level to the macroscopic simulations of granular flow. This work will start with the application of machine learning in the microscopic particle-particle interaction and associated contact models. Then, different neural networks for learning the constitutive behaviour of granular materials will be reviewed and compared. Finally, the macroscopic simulations of practical engineering or boundary value problems based on the combination of neural networks and numerical methods are discussed. We hope readers will have a clear idea of the development of machine learning-aided modelling of granular materials via this comprehensive review work.

42 ENGINEERING↗
DOE OSTI2024

Mesoscale simulation of granular materials under weak shock compaction–pore size distribution effects

This research established a systematic method to generate various pore-size distributions (PSDs) and studied the effect of PSDs on the shock compaction response of granular materials using two-dimensional mesoscale simulations under identical porosity. Simulations utilized various PSDs for three particle shapes (circle, ellipse, and square). Contacting particle configurations using three PSDs, characterized by spatially uniform distributed pores to heterogeneous distributed pores, and non-contacting particle configurations under a single case of PSD were tested. The PSD of generated particle sets was characterized using coordination number, mean diameter, and bimodality coefficient as statistical metrics. Mesoscale simulations showed that regardless of the conditions of pore distributions, shock compaction of granular materials consistently demonstrates a precursor, shock compaction front, and end. However, the shock compaction velocity of contacting particles was dependent on the PSDs despite the constant initial porosity. The compaction velocity was faster in particle configurations with relatively uniform pore distributions than in heterogeneous pore distributions, which our study demonstrated can be attributed to particle rearrangement during compaction. Circular-shaped particles had high sensitivity in shock compaction response to the various PSDs. Furthermore, a contacting particle configuration tended to propagate the shock compaction wave relatively faster than particles that were in a non-contact configuration. This study established the relative importance of considering PSD as a metric over the coordination number in studies of the shock compaction response of granular materials. Further, insights are provided on the evolving shock substructure to characterize the shock compaction response of granular materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions

Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Strain localization in dry sheared granular materials: A compactivity-based approach

Shear banding is widely observed in natural fault zones as well as in laboratory experiments on granular materials. Understanding the dynamics of strain localization under different loading conditions is essential for quantifying strength evolution of fault gouge, energy partitioning during earthquakes and characterizing rheological transitions and fault zone structure changes. To that end, we develop a physics-based continuum model for strain localization in sheared granular materials. The grain-scale dynamics is described by the Shear Transformation Zone (STZ) theory, a non-equilibrium statistical thermodynamic framework for viscoplastic deformation in amorphous materials. Using a finite strain computational framework, we investigate the initiation and growth of complex shear bands under a variety of loading conditions and identify implication for strength evolution and ductile to brittle transition. Our numerical results show similar localization patterns to field and lab observations and suggest that shear zones show more ductile response at higher confining pressures, lower dilatancy and loose initial conditions. Lower pressures, higher dilatancy and dense initial conditions favor a brittle response and larger strength drops. These findings shed light on a range of mechanisms for strength evolution in dry sheared granular materials and provide a critical input to physicsbased multiscale models of fault zone instabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Strength anisotropy of granular material consisting of perfectly round particles

Abstract The strength anisotropy of granular materials deposited under gravity has mostly been attributed to elongated particles' tendency to align long axes along the bedding plane direction. However, recent experiments on near‐spherical glass beads, for which preferred particle alignment is inapplicable, have exhibited surprisingly strong strength anisotropy. This study tests the hypothesis that certain amount of fabric anisotropy caused by the anisotropic stress during deposition under gravity can be locked in a circular‐particle deposit. Such locked‐in fabric anisotropy can withstand isotropic consolidation and leads to significant strength anisotropy. 2D discrete element method simulations of direct shear tests on circular‐particle deposits are conducted in this study, allowing for the monitoring of both stress and fabric. Simulations on both monodispersed and polydispersed circular‐particle samples generated under downward gravitational acceleration exhibit clear anisotropy in shear strength, thereby proving the hypothesis. When using contact normal‐based and void‐based fabric tensors to quantify fabric anisotropy in the material, we find that the intensity of anisotropy is discernible but low prior to shearing and is dependent on the consolidation process and the dispersity of the sample. The fact that samples with very low anisotropy intensity measurements still exhibit fairly strong strength anisotropy suggests that current typical contact normal‐based and void‐based second‐order fabric tensor formulations may not be very effective in reflecting the anisotropic peak shear strength of granular materials. Copyright © 2017 John Wiley & Sons, Ltd.

Wang, Rui↗
DOE OSTI2021

Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning

The analytical description of path-dependent elastic-plastic responses of a granular system is highly complicated because of continuously evolving microstructures and strain localisation within the system undergoing deformation. This study offers an alternative to the current analytical paradigm by developing micromechanics-informed machine-learning based constitutive modelling approaches for granular materials. A set of critical variables associated with the constitutive behaviour of granular materials are identified through an incremental stress-strain relationship analysis. Depending on the strategy to exploit the priori micromechanical knowledge, three different training strategies are explored. The first model uses only the measurable external variables to make stress predictions; the second model utilises a directed graph to link all the external strain sequences and internal microstructural evolution variables into a single prediction model comprised of a series of sub-mappings, and the third model explicitly integrates the physically important non-temporal properties with external strain paths into training through an enhanced Gated Recurrent Unit (GRU). These three models show satisfactory agreement with unseen test specimens based on multi-directional loading cases. The basic features and potential applications of each model are explained. Lastly, the key factors for constitutive training and limitations of the current work are also discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A laboratory-scale compression feed screw for characterizing continuous feeding of dense granular materials

Compression feed screws are commonly used in biorefineries for the continuous feeding of biomass feedstock into reactors. Developing methods to assess the feasibility of feeding granular materials in a compression feed screw is critical for reducing solids handling issues during operation. A laboratory-scale compression feed screw has been built to measure critical process parameters of the feeding operation, namely the driving torque and the mass flow rate. The process parameters of two granular materials, microcrystalline cellulose Avicel PH-200 and milled corn stover are measured using the laboratory-scale feeder. The results show that a larger torque is required to feed corn stover than Avicel PH-200, even though the former consists of more compressible particles. Further, the device can capture real-time fluctuations in the process parameters during operation. Here, the laboratory-scale feeder can be used to compare the feeding of different granular materials and the measured parameters can be used to validate predictive models for a compression screw feeding process.

09 BIOMASS FUELS↗
DOE OSTI2017

Breakage mechanics for granular materials in surface-reactive environments

It is known that the crushing behaviour of granular materials is sensitive to the state of the fluids occupying the pore space. Here, in this work, a thermomechanical theory is developed to link such macroscopic observations with the physico-chemical processes operating at the microcracks of individual grains. The theory relies on the hypothesis that subcritical fracture propagation at intra-particle scale is the controlling mechanism for the rate-dependent, water-sensitive compression of granular specimens. First, the fracture of uniaxially compressed particles in surface-reactive environments is studied in light of irreversible thermodynamics. Such analysis recovers the Gibbs adsorption isotherm as a central component linking the reduction of the fracture toughness of a solid to the increase of vapour concentration. The same methodology is then extended to assemblies immersed in wet air, for which solid-fluid interfaces have been treated as a separate phase. It is shown that this choice brings the solid surface energy into the dissipation equations of the granular matrix, thus providing a pathway to (i) integrate the Gibbs isotherm with the continuum description of particle assemblies and (ii) reproduce the reduction of their yield strength in presence of high relative humidity. The rate-effects involved in the propagation of cracks and the evolution of breakage have been recovered by considering non-homogenous dissipation potentials associated with the creation of surface area at both scales. It is shown that the proposed model captures satisfactorily the compression response of different types of granular materials subjected to varying relative humidity. This result was achieved simply by using parameters based on the actual adsorption characteristics of the constituting minerals. The theory therefore provides a physically sound and thermodynamically consistent framework to study the behaviour of granular solids in surface-reactive environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine-Learning-Based Multiscale Methods for 3D Modelling of Granular Materials by Incorporating History-Dependent State Variables

Over the past decades, the prevalence of machine learning (ML) methods has made the development of ML-based constitutive models for granular materials undoubtedly a popular subject. Numerous studies have been made to feature the loading path or history-dependent stress-strain response of granular media using neural networks. In this work, a novel finite element method (FEM)–ML multiscale approach was developed by incorporating internal variables to improve the simulation accuracy of 3D history-dependent granular materials for the first time. To this end, a surrogate constitutive model based on the single-step-based multi-layer perceptron (MLP) neural network was used to replace representative volume element (RVE) simulations conducted by the discrete element method (DEM) in the multiscale FEM–DEM approach. Although the prediction principle of the MLP aligns with the FEM algorithm, artificially added internal variables are required to differentiate the loading history. To address this issue, history variables associated with the Frobenius norm are proposed to be fed into the MLP coupled with the strain tensor to extract the history-dependent behaviour of granular assemblies. The developed FEM–ML approach was demonstrated in 3D conventional triaxial compression (CTC) simulations. Compared to the multiscale FEM–DEM approach, the proposed FEM–ML method exhibits a significantly improved computational efficiency.

granular materials↗
DOE OSTI2022

From force chains to nonclassical nonlinear dynamics in cemented granular materials

In this letter, we present evidence for a mechanism responsible for the nonclassical nonlinear dynamics observed in many cemented granular materials that are generally classified as mesoscopic nonlinear elastic materials. We demonstrate numerically that force chains are created within the complex grain-pore network of these materials when subjected to dynamic loading. The interface properties between grains along with the sharp and localized increase of the stress occurring at the grain-grain contacts leads to a reversible decrease of the elastic properties at macroscopic scale and peculiar effects on the propagation of elastic waves when grain boundary properties are appropriately considered. These effects are observed for relatively small amplitudes of the elastic waves, i.e., within tens of microstrain, and relatively large wavelengths, i.e., orders of magnitude larger than the material constituents. The mechanics are investigated numerically using the hybrid finite-discrete-element method and match those observed experimentally using nonlinear resonant ultrasound spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Learning Predicts Stress–Strain Relations of Granular Materials Based on Triaxial Testing Data

This study presents an AI-based constitutive modelling framework wherein the prediction model directly learns from triaxial testing data by combining discrete element modelling (DEM) and deep learning. A constitutive learning strategy is proposed based on the generally accepted frame-indifference assumption in constructing material constitutive models. The low-dimensional principal stress-strain sequence pairs, measured from discrete element modelling of triaxial testing, are used to train recurrent neural networks, and then the predicted principal stress sequence is augmented to other high-dimensional or general stress tensor via coordinate transformation. Through detailed hyperparameter investigations, it is found that long short-term memory (LSTM) and gated recurrent unit (GRU) networks have similar prediction performance in constitutive modelling problems, and both satisfactorily predict the stress responses of granular materials subjected to a given unseen strain path. Furthermore, the unique merits and ongoing challenges of data-driven constitutive models for granular materials are discussed.

42 ENGINEERING↗