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At least 73 records · Page 4

Discrete element modeling of irregular-shaped soft pine particle flow in an FT4 powder rheometer

Pine residues are a commonly used biomass feedstock that consists of different anatomical fractions, each with distinct particle characteristics. Here, in this work, an experiment-informed discrete element model is developed to investigate the flowability of pine residues in an FT4 rheometer. Multi-sphere particles with distinct particle attributes are created to model each anatomical fraction type. A systematic analysis of specimens with varying particle characteristics (e.g., anatomical fraction type, particle shape, and size) is conducted to elucidate the relationship between particle attributes and flowability. The results show that stems recorded the highest axial force and torque and, correspondingly, the highest flow energy, which is attributed to their high stiffness and interlocking effect. Increasing their percentage in the mixture increases the flow energy while increasing needles tends to decrease flow energy. Knowledge gained in this study on the flow of anatomical fractions is important for the efficient and robust processing of pine residues.

09 BIOMASS FUELS↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗

Explicit simulation of the Brownian rotation of arbitrary shaped aerosol particles using quaternions

The shape of an aerosol particle strongly influences its mass and momentum transfer cross-sections, charging properties, and other physical properties. Here, we present an explicit time-stepping procedure to simulate the rotational Brownian motion of arbitrary shaped aerosol particles by solving Euler’s equation of rotation. A Langevin formulation of the rotation equations is used, wherein Brownian motion due to thermal collisions between a particle and background gas molecules is represented using a stochastic fluctuating torque and fluid resistance is included as a drag torque. To avoid singularities associated with describing the orientation of a shape with Euler angles, we employ a quaternion formulation that leads to first-order stochastic differential equations to describe the evolution of the angular position and angular velocity of a rigid body. We perform all the rotational dynamics calculations in the body-fixed frame of reference attached to the rotating shape whose basis vectors are the normalized eigenvectors of the inertia tensor of the particle. Numerical solutions to rotation under torque-free conditions, damped rotation without Brownian motion, and stochastic rotation for arbitrary shapes are presented and discussed. The presented method enables time-resolved simulation of Brownian rotation for direct comparison with experimentally measured trajectories or statistical measures. The second order accuracy of the used time-stepping procedure places a severe restriction on the timestep that can be used for obtaining accurate results. Animations of presented simulations are included for visualizing rotational motion at various gas pressures. To aid implementation, MATLAB ® codes are also provided. Extension to include translation Brownian motion is straightforward.

Roy, Mrittika↗

Heat conduction in metal-filled polymers - The role of particle size, shape, and orientation

This paper presents a new type of analysis for predicting the thermal conductivity of disperse composites from the properties of the component phases and elementary characterizations of particle shapes and orientation. This analysis successfully predicted the sensitivity to particle shape which was confirmed by experiments also reported in this paper. These results suggest that highly elongated particles may be used to achieve dramatic modifications of thermal conductivity and the analysis presented here may be a useful tool in the design or development of disperse composites of specific thermal conductivity. The analysis may also apply to other properties such as electrical conductivity or magnetic permeability.

Hansen, D.↗

Effects of particle size, shape and loading rate on the normal compaction of an advanced granular ceramic

Compaction behavior of granular materials is influenced by strain rate, particle size, and shape. In this report, boron carbide powders with different particle sizes under uni-axial strain conditions are studied using quasi-static compression, dynamic Kolsky bar experiments and normal plate impact. A rounded powder is compacted to investigate the effect of particle shape. The normal plate impact technique is an excellent tool in characterization of powder compaction behavior up to strain rates of ~10 5 s -1 . From our experiments, granular boron carbide shows a highly compressible behavior with significant volume compaction. Constitutive responses are obtained for four powders. Particle fracture is identified as key deformation mechanism. Dynamic loading introduces more particle fragmentation than quasi-static loading. Morphological characterization of particle shapes shows that the deformation from powder compaction alters the particle shape distribution, which is also rate-dependent. Particle size, shape and strain rate effects on the normal stress are discussed accordingly.

36 MATERIALS SCIENCE↗

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗

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↗

Elastomeric nematic colloids, colloidal crystals and microstructures with complex topology

Control of physical behaviors of nematic colloids and colloidal crystals has been demonstrated by tuning particle shape, topology, chirality and surface charging. However, the capability of altering physical behaviors of such soft matter systems by changing particle shape and the ensuing responses to external stimuli has remained elusive. We fabricated genus-one nematic elastomeric colloidal ring-shaped particles and various microstructures using two-photon photopolymerization. Nematic ordering within both the nano-printed particle and the surrounding medium leads to anisotropic responses and actuation when heated. With the thermal control, elastomeric microstructures are capable of changing from genus-one to genus-zero surface topology. Using these particles as building blocks, we investigated elastomeric colloidal crystals immersed within a liquid crystal fluid, which exhibit crystallographic symmetry transformations. Furthermore, our findings may lead to colloidal crystals responsive to a large variety of external stimuli, including electric fields and light. Pre-designed response of elastomeric nematic colloids, including changes of colloidal surface topology and lattice symmetry, are of interest for both fundamental research and applications.

36 MATERIALS SCIENCE↗

Shape Dependence of Pressure-Induced Phase Transition in CdS Semiconductor Nanocrystals

Understanding structural stability and phase transformation of nanoparticles under high pressure is of great scientific interest, as it is one of the crucial factors for design, synthesis, and application of materials. Even though high-pressure research on nanomaterials has been widely conducted, their shape-dependent phase transition behavior still remains unclear. Examples of phase transitions of CdS nanoparticles are very limited, despite the fact that it is one of the most studied wide band gap semiconductors. Here we have employed in-situ synchrotron wide-angle X-ray scattering (WAXS) and transmission electron microscopy (TEM) to investigate the high-pressure behaviors of CdS nanoparticles as a function of particle shapes. We observed that CdS nanoparticles transform from wurtzite to rocksalt phase at elevated pressure in comparison to their bulk counterpart. Phase transitions also vary with particle shape—rod-shaped particles show a partially reversible phase transition and the onset of the structural phase transition pressure decreases with decreasing surface-to-volume ratios, while spherical particles undergo irreversible phase transition with relatively low phase transition pressure. Additionally, TEM images of spherical particles exhibited sintering-induced morphology change after high-pressure compression. Calculations of the bulk modulus reveals that spheres are more compressible than rods in the wurtzite phase. These results indicate that the shape of the particle plays an important role in determining their high-pressure properties. Our study provides important insights into understanding of the phase-structure-property relationship, guiding future design and synthesis of nanoparticles for promising applications.

36 MATERIALS SCIENCE↗

A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows

In this study, interaction force of non-spherical particles in low Reynolds number gas-solid flow is investigated by neural network approaches. An artificial neural network (ANN) model is developed to correlate the non-spherical particle shape and the flow conditions with the interaction force. To define the particle shape, spherical harmonic expansion is applied. Furthermore, variational autoencoder model is then used to extract latent geometric features. The latent vector is utilized as an input with the Reynolds number for the ANN. The interaction force data, which is used as output data of the ANN, is obtained by particle resolved direct numerical simulation for 5200 non-spherical particles. The proposed model enables unsupervised extraction for non-spherical particle shapes and accurate predictions on the interaction force without heavy computation. This study provides the model that can explain complicated shapes of particles and be applied to a large scale, computational fluid dynamics simulation.

01 COAL, LIGNITE, AND PEAT↗

Ceramic powder for sintering materials

Surface activity of ceramic powders such as MgO and Al2O3, for use in sintering with sp. emphasis on their particle size, shape, particle size distribution, packing, and coexisting additives and impurities are reviewed.

Akiya, H.↗

NASA LSII Lunar Simulant Project

Introduction: America has entered a new era of exploration. NASA’s Artemis program will lead humanity forward to the Moon and prepare us for the next giant leap, the exploration of Mars [1]. To champion technologies needed to live on and explore the Moon, NASA’s Space Technology Mission Directorate (STMD) established the Lunar Surface Innovation Initiative (LSII)[2].LSII's technology development portfolio includes: Utilizing the Moon’s resources; Establishing sustainable surface power; Building machinery and electronics that work in extreme environments, like super-chilly permanently shadowed craters; Mitigating lunar dust; Carrying out surface excavation, manufacturing and construction duties; and Extreme access which includes navigating and exploring the surface/subsurface. To support the development and testing of these technologies, LSII created the lunar simulant project, to create and/or acquire low-, medium-and high-fidelity lunar simulants to match the needs of STMD projects at all levels of technology readiness levels (TRL), as well as other NASA programs. There is not one bulk lunar simulant that will satisfy the needs of all projects. NASA's Approach to Simulants: Just as LSII's activities are being implemented through a combination of unique NASA work and public-private partnerships, NASA will work with commercial simulant providers to acquire simulants that meet NASA's needs. If warranted, NASA will develop simulants using government agencies, as was done with the NASA/USGS Lunar Highlands Type (NU-LHT)series of lunar simulants [3].NASA is also collaborating with the Johns Hopkins University Applied Physics Laboratory(JHUAPL) Lunar Surface Innovation Consortium (LSIC) in the development and characterization of lunar simulants [4]. Within NASA, a small team (< 10 people) is coordinating simulant activities across the agency, with team members located at several NASA centers. The overall objective of the project is to procure lunar simulants in sufficient amounts for earth-based testing of subsystems and systems in a variety of environments (i.e., laboratory, high-bay, thermal-vacuum chambers), required for Artemis missions to the Moon, as well as other missions carrying NASA lunar payloads, such as the Commercial Lunar Payload Services (CLPS)program [5]. Lunar Highlands Simulant: NASA's Artemis Program is targeting the lunar south pole region for initial human missions and the Artemis Base Camp. Hence, the LSII lunar simulant project is currently focusing on the mineralogy and properties of lunar highlands regolith [6 and 7]. Plagioclase-rich rocks (e.g., anorthosite, norite) are the dominant constituent in highlands simulants, with Shawmere, Stillwater, and White Mountain anorthosites being used in commercially available simulants. However, because these feedstocks are terrestrial in nature, they include hydrated minerals, carbon-bearing minerals, and other chemical signatures that are not present on the Moon, and these minor mineral assemblages need to be taken into account when trying to understand test procedures and results. Glass Component: While much attention has been placed on the rock/mineral component of lunar simulants, glass is just as important when creating simulants. The glass component in lunar regoliths is often greater than 50% by volume [8]. This component includes impact melt glass, dark matrix breccias, and agglutinates. However, this component is difficult, time-consuming and expensive to make. Most lunar simulants, past and current, have relied on basaltic cinder as a feedstock for glass. Getting better glass components at a lower cost, particularly agglutinates and glass with an anorthositic composition is a near-term objective that the NASA simulant project is trying to address . Characterization: It is extremely important for lunar simulants to be characterized by several analytical methods. Gruener et al. [9] and JHUAPL LSIC [10] conducted initial assessments of some of the commercially available simulants in 2019 and early 2020, before the global pandemic. Further analyses are needed to better quantify important parameters such as, modal mineralogy and glass content, particle shape, and particle size distribution. These quantified results can then be used in determining figures of merit (FOM) that show how well simulants compare to lunar regolith [11 and 12].

J E Gruener↗

Near net shape bulk laminated silicon iron electric steel for improved electrical resistance and low high frequency loss

The invention involves producing discontinuous, flake-shaped particles of a soft magnetic material, coating the flake-shaped particles with an electrically insulating coating, and consolidating the coated flaked-shaped particles to form a soft magnetic bulk shape. The consolidated bulk shape can comprise a layer or a simple or complex 3D magnet part shape, which has a consolidated layered microstructure that includes laminated soft magnetic regions that are substantially encapsulated by an electrical insulating layer to increase the resistivity of soft magnetic material, especially when used in silicon iron magnet parts.

Cui, Jun↗

Shape-induced Gravitational Sorting of Saharan Dust During Transatlantic Voyage: Evidence from CALIOP Lidar Depolarization Measurements

Motivated by the physical picture of shape-dependent air resistance and, consequently, shape-induced differential sedimentation of dust particles, we searched for and found evidence of dust particle asphericity affecting the evolution and distribution of dust-scattered light depolarization ratio (delta). Specifically, we examined a large data set of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of Saharan dust from June to August 2007. Observing along a typical transatlantic dust track, we find that (1) median delta is uniformly distributed between 2 and 5 km altitudes as the elevated dust leaves the west coast of Africa, thereby indicating uniformly random mixing of particle shapes with height; (2) vertical homogeneity of median delta breaks down during the westward transport: between 2 and 5 km delta increases with altitude and this increase becomes more pronounced with westward progress; (3) delta tends to increase at higher altitude (greater than 4 km) and decrease at lower altitude (less than 4 km) during the westward transport. All these features are captured qualitatively by a minimal model (two shapes only), suggesting that shape-induced differential settling and consequent sorting indeed contribute significantly to the observed temporal evolution and vertical stratification of dust properties. By implicating particle shape as a likely cause of gravitational sorting, these results will affect the estimates of radiative transfer through Saharan dust layers.

CALIPSO↗

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Discrete element modeling of switchgrass particles under compression and rotational shear

Switchgrass is a perennial herbaceous plant regarded as a biomass energy crop in the United States for its highadaptability and yield potential. Processing and handling of switchgrass particles are challenging due to the erratic mechanical and flow behavior originating from their intrinsic particulate properties. Here, we present a bonded-sphere discrete element model designed specifically for switchgrass particles. The model simultaneously captures three key particulate features, i.e., fibrous particle shapes, a wide range of particle sizes, and particle deformability. Realistic yet computationally efficient particle shape templates are created based on the image analysis data of switchgrass specimens. A fitting procedure is proposed to ensure both the particle width and length distributions are captured, a unique requirement for fibrous particles. Two full-scale numerical models, i.e., a uniaxial compression model and a Schulze ring shear model, are developed using information fromphysical experiments. The model is calibrated using experimental data of chopped-small switchgrass specimens, and then, is validated using data of chopped-large specimens in both compression and ring-shear tests. Numerical results show that the numerical models capture bulk densities accurately (with an error of 3%) while slightly underestimate the bulk friction angle. Furthermore, an extensive sensitivity analysis reveals that (1) switchgrass particles with rougher edges (due to different processing techniques) exhibit a higher shear strength and a lower flowability; (2) stiffer particles yield a lower bulk density (up to 21% lower) compared to more deformable particles, indicating particle deformability should be incorporated when modeling biomass flow in a preprocessing system.

09 BIOMASS FUELS↗

The mechanics of brittle granular materials with coevolving grain size and shape

The influence of particle shape on the mechanics of sand is widely recognized, especially in mineral processing and geomechanics. However, most existing continuum theories for engineering applications do not encompass the morphology of the grains and its evolution during comminution. Similarly, the relatively few engineering models accounting for grain-scale processes tend to idealize particles as spheres, with their diameters considered as the primary and sole geometric descriptor. This paper inspires a new generation of constitutive laws for crushable granular continua with arbitrary, yet evolving, particle morphology. We explore the idea of introducing multiple grain shape descriptors into Continuum Breakage Mechanics (CBM), a theory originally designed to track changes in particle size distributions during confined comminution. We incorporate the influence of these descriptors on the elastic strain energy potential and treat them as dissipative state variables. In analogy with the original CBM, and in light of evidence from extreme fragmentation in nature, the evolution of the additional shape descriptors is postulated to converge towards an attractor. Comparisons with laboratory experiments, discrete element analyses and particle-scale fracture models illustrate the encouraging performance of the theory. The theory provides insights into the feedback among particle shape, compressive yielding and inelastic deformation in crushable granular continua. These results inspire new questions that should guide future research into crushable granular systems using particle-scale imaging and computations.

36 MATERIALS SCIENCE↗