Properties Of Granular Materials Research Articles

Beyond jamming grippers: granular material in robotics

ABSTRACT Robot grippers based on the jamming of granular material have been studied widely in previous years. Recently, also other benefits and challenges of granular material have emerged for robotics. We discuss various functions of granular matter in robotic actuation, sensory processing, locomotion, and manipulation. We also provide a review of the design and methods of robots for moving in or on challenging granular environments. Drawing on the properties of granular material and their potential applications, we propose our unique perspectives and innovative ideas for future research and development in this field.

A novel method for predicting coarse aggregate particle size distribution based on segment anything model and machine learning

Particle size distribution (PSD) is an important index property of granular materials. The conventional mechanical sieve analysis for PSD determination is labor-intensive, time-consuming, and inefficient. With the development of computer vision, image-based gradation prediction methods gradually emerge. However, previous studies mainly focused on images where individual aggregate particles are separated from each other without overlapping (i.e., not densely packed together), thus limiting their applicability. This study proposed a novel framework to predict the PSD of densely packed coarse aggregate particles, which is based on visual foundation model and machine learning with appropriate feature engineering. First, the segment anything model, which is one of the visual foundation models, was used for the instance segmentation of the densely packed aggregate particles. Then, the feature engineering was implemented with the segmentation result. The major quantitative indicators related to particle sizes were extracted from each mask, such as the area, the diameter of minimum enclosing circle, and the major axes of the equivalent ellipse of particle contours. Subsequently, the cumulative distribution curves of these indicators were plotted, followed by the data sampling operation on these curves to generate the feature vectors. The artificial neural network (ANN) model was then trained for gradation prediction with each of the feature vectors and the data points extracted from PSD curves used as the inputs and data labels, respectively. The model-training dataset consisted of 8160 different sets of digitally generated particle samples with known PSDs. Finally, verification test results of additional five different groups of digital particle samples and real coarse aggregate samples with known PSDs show that the root mean squared error (RMSE) of predicted aggregate sizes is 1.79 mm and 1.86 mm for digital and real aggregate particle samples, respectively. Therefore, the efficacy and feasibility of the proposed method was validated in terms of predicting the PSD of densely packed coarse aggregates from two-dimensional image information. As compared to the Mask RCNN combined with empirical formula of which the RMSE values were 5.12 mm and 5.84 mm for digital and real aggregate particle samples, respectively, the proposed framework demonstrates improved particle segmentation applicability and better PSD prediction accuracy.

Acid fluoride in ceramic material production

Purpose: The aim of this work is to develop fluorine anhydrite-based ceramic materials and engineering concept for their production and identify the conditions for the ceramic body formation and strength improvement.Methodology/approach: Acid fluoride without aditional processing and ash from thermal power plants are used in the experiment. Sodium silicate solution and the aluminum powder are introduced in the melt for the mullite formation. The phase composition is investigated on a Shimadzu XRD-6000 Diffractometer. Clay is dried to prepare the mixture and then it is ground in a jaw breaker and co-milled with the specific amount of acid fluoride.Research findings: Granular and piece ceramic wall materials with the required properties are obtained. Drying and firing conditions and the main performance characteristics are determined herein.Practical implications: Construction and technical characteristics of acid fluoride are detected for the ceramic material production, the proposed methods can be used for ceramics modification, allowing to reduce expenditures per unit of output for mineral raw materials.Originality: Process conditions are determined for the ceramics production, and dependencies are suggested to control the composition and properties of granular and piece ceramic wall materials.

Smoothed particle hydrodynamics approach for modelling submerged granular flows and the induced water wave generation

In this study, we develop a Smoothed Particle Hydrodynamics (SPH) 2D-model for simulating fully submerged granular flows and their arising water waves. The granular particles are characterised by a non-Newtonian flow pattern, following a Casson constitutive law, generalised by applying the infinitesimal strain theory to avoid numerical singularities inherited from the original law. The implementation of this rheological model on the weakly compressible viscous Navier-Stokes equations enables the simultaneous modelling of the motion of granular flows and their resulting water waves, establishing a monolithic representation of fluid-structure coupling. The novelty of this model lies in the numerical continuity of the generalised rheological model based mainly on the yield stress criterion, which is computed purely from the mechanical properties of granular materials, including internal friction, cohesion, and viscosity coefficients. The proposed SPH model is validated through two benchmarks available in the literature, representing a submarine landslide along an inclined plane and an immersed granular column collapse. The outcomes of our study illustrate the effectiveness of the proposed model in accurately predicting the motions of submerged granular masses and their resulting water waves, which is crucial for accurately predicting the behaviour of underwater landslides and other natural hazards.

A continuous-discontinuous deformation analysis method for research on the mechanical properties of coarse granular materials

The mechanical properties of coarse granular materials play a crucial role in the safety of rockfill dams. From a mesoscopic viewpoint, the macroscopic mechanical properties of these materials are a result of the interactions between particles and the progression of particle breakage. Traditional continuum-based numerical methods struggle to accurately analyze the mechanical properties of coarse granular materials. Discontinuous deformation analysis (DDA) is a more suitable algorithm for studying these properties due to its significant benefits in block displacement mode and open-close iteration for contact handling. In this paper, a continuous-discontinuous deformation analysis method (CDDA) based on the conventional DDA is developed for the numerical investigation of coarse granular materials' mechanical properties. This method incorporates critical kinetic damping, multi-stageloading, stricter displacement convergence criteria and particle breakage simulation. It can provide a comprehensive representation of deformation, particle breakage, force chain, shear zone, and stress–strain curve evolutions. The CDDA results are found to be consistent with indoor test results and can more effectively disclose the deformation and failure mechanism of coarse granular materials. Furthermore, CDDA is employed to examine the impacts of particle size and end friction, leading to valuable insights regarding these effects.

Effect of atmospheric dielectric barrier discharge treatment on the triboelectric charging properties of brominated Polyethylene granules

This paper aims to investigate the effect of dielectric barrier discharge (DBD) plasma treatment on the triboelectric charging properties of granular materials containing brominated flame retardants (BFRs). This work focuses on the impact of treatment time and the applied voltage frequency. Experiments were carried out on Polyethylene (PE) particles containing 40000 ppm of bromine (PE 4.6 % of Hexabromobenzene) and BFR-free PE. The DBD treated particles were then charged by triboelectric effect in a multi-cylinder device. The triboelectric charge acquired by each sample was quantified using a Faraday cage connected to an electrometer. The humidity of the ambient air ranged between 51 % and 60 % and the temperature varied from 16.5 °C to 19 °C during the experiments. Results show the significant influence of DBD treatment time on the triboelectric charging of brominated and non-brominated PE granules. In case of brominated PE, the particles acquire less charge than the non-brominated ones. Furthermore, it was found that the charge of DBD-treated particles is influenced by the applied voltage frequency. The observed variation in triboelectric behavior may be attributed to the changes in the roughness and wettability of the polymer surface caused by DBD.

Contact networks and force transmission in aggregates of hexapod-shaped particles.

Hexapods, consisting of three mutually orthogonal arms, have been utilized as a representative nonconvex shape to demonstrate the impact of interlocking on the strength properties of granular materials. Nevertheless, the microstructural characteristics of hexapod packings, which underlie their strength, have remained insufficiently characterized. We use particle dynamics simulations to build isotropically-packed aggregates of hexapods and we analyze the effects of aspect ratio and interparticle friction on the microstructure and force transmission. We find that the packing fraction is an unmonotonic function of aspect ratio due to competition between steric exclusions and interlocking. Interestingly, the contact coordination number declines considerably with friction coefficient, showing the stronger effect of friction on the stability of hexapod packings as compared with sphere packings. The pair distribution functions show that local ordering due to steric exclusions disappears beyond the aspect ratio 3 and the hexapods touch their second neighbors. Remarkably, hexapods of aspect ratio 3 tend to align with their neighbors and form locally ordered structures, implying a contact coordination number which is highly sensitive to the confining pressure. We also show that the probability density function of forces between hexapods is similar to that of sphere packings but with broadening exponential fall-off of strong forces as aspect ratio increases. Finally, the elastic bulk modulus of the aggregates is found to increase considerably with aspect ratio as a consequence of the rapid increase of contact density and the number of contacts with second neighbors.

Effects of cementing matrix characteristics and particle size on the adhesion rule and mechanical properties of cemented granular materials

The process of filling self-compacting cement grout (SCCG) into granular packing without disturbing the granular skeleton culminates in the formation of a well-defined cemented granular materials (CGMs). The inherent attributes of both the cementing matrix and granular packing critically dictate the adhesion behavior and mechanical performance of CGMs. A succession of cement grout flow tests was conducted to elucidate the influence of particle size and the SCCG flowability on SCCG adhesion mechanism within granular packing. Furthermore, the influence of particle size and the cementing matrix volume on the mechanical characteristics of CGMs was scrutinized via uniaxial compressive testing. The results illuminate that the adhesion behavior of SCCG within granular packing is predominantly dependent on the yield stress of SCCG and the average particle size. Additionally, it is established that the peak strength of CGMs is intimately intertwined with the cementing matrix volume and the average particle size, as corroborated by a substantial aggregate of 135 uniaxial compression tests.

Modeling the single particle crushing behavior by random discrete element method

Microscopic properties of granular materials typically exhibit significant heterogeneity. Realistic particle crushing simulation in granular materials requires the use of model that incorporate the spatial heterogeneity of its microscopic properties. This study introduces a novel approach, the Random Field Theory-Discrete Element Method (RFT-DEM) model, to simulate the single-particle crushing behavior of granular materials, considering the spatial heterogeneity of microscopic properties within particles. The material heterogeneity was characterized through Random Field Theory, demonstrating reasonable consistency between simulated and experimental results. The size-dependent characteristics of crushing strength and Weibull modulus were confirmed through a series of single-particle crushing simulations, emphasizing the model's capability to capture such features. Systematic analyses explored the impact of coefficient of variation (COV) and scale of fluctuation (SOF) on single-particle crushing behavior. Increasing COV resulted in reduced characteristic crushing strength and Weibull modulus, with larger particles exhibiting greater sensitivity. Furthermore, increasing SOF initially increased these parameters until a threshold SOF value of 0.0005 m, beyond which they stabilized. Reduced COV or increased SOF diminished the size effect in characteristic crushing strength, and once COV exceeded a threshold of 0.03, the size effect became independent of its variations. These findings contribute to a comprehensive understanding of the intricate interplay between microscopic properties and crushing behavior in granular materials.

Non-convex shape effects on the biaxial compression of granular materials composed of monophasic packing and binary mixture

Driven by external compressions or shears, the granular material composed of non-convex shapes often undergoes self-assembly and becomes entangled, resulting in denser packings. In this work, the biaxial compression of monophasic and binary mixture composed of 2D intersecting crosses have been simulated via the discrete element method. As the aspect ratio increases, both the yield strength and elastic modulus initially increase before reaching a peak at w = 0.5. In binary mixtures, an antagonistic effect has been observed in mechanical properties of granular material. The decrease in strength and stiffness in binary mixtures can be attributed to the constraints imposed by multi-point contacts, along with the local order degree, which is particularly unique for non-convex particle packings. Building upon this understanding, we have extended the empirical formula into predicting the mechanical behavior of non-convex binary mixtures. This extension incorporates an additional non-linear term determined by both the shape factor and component fraction.

Observe, inspect, modify: Three conditions for generative AI governance

In a world increasingly shaped by generative AI systems like ChatGPT, the absence of benchmarks to examine the efficacy of oversight mechanisms is a problem for research and policy. What are the structural conditions for governing generative AI systems? To answer this question, it is crucial to situate generative AI systems as regulatory objects: material items that can be governed. On this conceptual basis, we introduce three high-level conditions to structure research and policy agendas on generative AI governance: industrial observability, public inspectability, and technical modifiability. Empirically, we explicate those conditions with a focus on the EU’s AI Act, grounding the analysis of oversight mechanisms for generative AI systems in their granular material properties as observable, inspectable, and modifiable objects. Those three conditions represent an action plan to help us perceive generative AI systems as negotiable objects, rather than seeing them as mysterious forces that pose existential risks for humanity.

Research on breakage mechanical properties of fragile granular material considering the effect of gradations

Research on breakage mechanical properties of fragile granular material considering the effect of gradations

Discrete Element Simple Shear Test Considering Particle Shape

The particle shape has significant effects on the slip and rotation of particles in the shear of geomaterials, which is an important factor in the deformation and strength of geomaterials. This paper employed particle flow code (PFC3D) to simulate the simple shear test, and ellipsoidal particles with different aspect ratios were prepared to study the effects of particle shape on the mechanical behavior and fabric evolution of granular materials under complex stress paths. The numerical results show that the particle shape has a significant effect on the peak strength, dilatancy, non-coaxiality, and other mechanical properties of granular materials. The contact fabric evolves from orthotropy to transverse isotropy under the principal stress axes rotation. This paper will provide a reference for natural granular materials with different shapes in the study of mechanical behavior and the micro-constitutive model.

Fracture process zone in crystalline rock: effect of specimen size and shape

Ability to predict fracture properties of granular materials based on their size and loading conditions needs rigorous experimental evidence. Charcoal granite specimens of various sizes and geometries are tested under three- and four-point bending to investigate the effect on the fracture toughness of rock and size of the fracture process zone calculated using Digital Image Correlation (DIC), with validation provided by Acoustic Emission (AE). Two different methods to evaluate the length of the fracture process zone using DIC are adopted: the first one assumes that a traction free crack does not propagate in the pre-peak regime, while the second one hypothesizes that a cohesionless crack may exist at peak load before unstable crack growth. The effects of specimen size, geometry, and loading conditions are found to be more prominent for the specimen sizes used in the laboratory but are predicted to become less significant and eventually negligible as the specimen size increases. DIC results are in general agreement with localization of AE events, but the former technique is suggested due to greater resolution and ability of continuous measurements of the fracture process zone dimensions.

Influence of the interparticle friction coefficient on the mechanical behaviour of breakable granular materials with realistic shape

Interparticle friction coefficient μ is an important factor affecting the mechanical properties of granular materials. In this study, the influence of μ on the mechanical behavior of granular materials is investigated by DEM. Through 3D scanning and Voronoi tessellations, the breakable particle model with realistic shape is constructed. A series of drained triaxial tests were performed at different μ values. Then, the particle breakage characteristics, including the degree of particle breakage and the breakage mode, were evaluated. In addition, microscopic characteristics, including coordination numbers and contact forces, were examined. Finally, the underlying mechanisms of φc evolution are explained from two perspectives of particle movement and fabric anisotropy. First, the rolling behavior of the particles increases with μ values, leading to a larger average displacement of particles. The influence of particle movement and friction coefficient balance each other, resulting in φc remaining constant when μ⩾0.4. Second, the initial increase of φc is due to the increase of the contact normal anisotropy ac, the normal contact force anisotropy an and the tangential contact force anisotropy at. Subsequently, the constant φc is the result of the decrease of ac and an being compensated by the increase of at.

The Effect of a Moving Boundary on the Shear Strength of Granular Materials in a Direct Shear Test

The boundary state significantly influences the soil shear strength. Therefore, it is necessary to overcome the limitations of existing indoor test instruments and determine the differences in the shear properties of granular materials to ensure the economic feasibility and mechanical integrity of engineering structures. In this study, the core formula for the direct shear test was derived from the static balancing analysis of the shear box, the external force on the specimen, and the internal force on the shear surface. Three loading methods were then developed by the staggered state of the upper and lower boxes: the upper box moving shear loading method (UM), the lower box moving shear loading method (LM), and the bidirectional moving shear loading method (BM). Finally, by manipulating the motion boundary, the discrete element method (DEM) was employed to simulate the shear test of granular materials. Among the three loading methods, the order of the peak shear stresses was as follows: UM > BM > LM. Moreover, the order of the sample post-peak stress uniformities was as follows: LM > BM > UM. A shear strength conversion formula was then proposed. The findings of this study promote the advancement of the shear mechanics theory of granular materials in direct shear testing and can serve as a scientific basis for the design and manufacture of shear equipment.

Multi-GPUs DEM algorithm and its application in the simulation of granular materials

The Discrete Element Method (DEM) is one of the most common numerical approach for modeling the physical and mechanical properties of granular materials. However, its computational efficiency can be a major bottleneck, which significantly hinders its application in engineering fields. To overcome this challenge, a multi-GPU framework with OpenMP has been developed. In this framework, the DEM particles in 3D space and their corresponding contact information are sorted in a given direction in the simulation, and each GPU device handles a subdomain of particles and relative contacts. Additionally, the contact information is densely arranged to minimize memory usage. To further enhance efficiency, sorting and packing algorithms for the contact information have been introduced. During calculating loop, the number of contacts on each device is monitored, and the spatial division of devices is adjusted to balance memory distribution. The efficacy of the multi-GPU algorithm is verified through a chute flow test. Using numerical results, the segregation process and mechanics of granular materials during sliding have been studied in detail. Furthermore, the simulations demonstrate that the developed multi-GPU algorithm greatly enhances computational efficiency and reduces memory usage per device.

DEM study on mixing behaviors of concave-shaped particles in rotating drum based on level-set method

Granular mixing is a complex phenomenon that is commonly encountered in various engineering disciplines. A large number of past studies have mainly focused on the mixing properties of convex-shaped granular materials, while the mixing behaviors of concave-shaped granular materials have not been well studied. In this study, spherical harmonic functions are used to describe the spherical and concave shapes of individual particles. The level set function is an implicit function consisting of a set of points that can be used to determine the contact points between particles. Then, the influences of the particle shape and rotational speed on the mixing behaviors of the granular material within a horizontal drum are analyzed by the discrete element method (DEM). Results indicate that concave particles have higher coordination numbers and closer contact patterns than spherical particles, which results in greater normal collision forces, larger dynamic angle of repose and lower mixability.

Thermodynamic constitutive model for granular soils considering particle shape distribution

Particle shape has a significant effect on the shear strength and shear dilatancy properties of granular materials. This study presents a granular thermodynamic theory investigate the effects of particle shape and distribution on the mechanical properties and behavior of granular materials. The theory model outcomes closely resemble experimental results, effectively capturing the impact of particle shape on the mechanical properties and shear dilation of granular materials. The paper analyzes the relationship between a granular system's plastic behavior and granular temperature and explores the influence of irregularly shaped granular on the system's strength and kinetic energy activity. The granular temperature behavior during external loading is studied, showing that granular temperatures increase to a maximum value before gradually decreasing to a more stable state. Simulation results based on the proposed model also indicate obvious effects of nonuniform particle-shape distribution on the mechanical properties of granular materials, providing a comprehensive insight into the underlying mechanisms of the particle-shape effects from the perspective of thermodynamics.

A physically consistent Discrete Element Method for arbitrary shapes using Volume-interacting Level Sets

The properties of granular materials depend strongly on the shapes of their individual constituent particles or granules. Nonetheless, incorporating the effects of non-spherical or complex particle shapes into existing modelling frameworks, such as the discrete element method (DEM), has remained challenging. In this work, we propose the volume-interaction level set DEM (VLS-DEM) approach for carrying out physically accurate simulations of particles with arbitrary geometries. VLS-DEM builds upon level set DEM (LS-DEM), both of which implicitly define the geometry of a particle through a discrete signed distance function. However, instead of using surface nodes to compute the interparticle forces, VLS-DEM uses the overlap volume as computed by an Octree integration algorithm. This addresses some of the shortcomings of LS-DEM in terms of the accuracy and precision of the shape description and opens up the possibility for bottom-up parametrisation methods. A number of tests were performed to compare VLS-DEM with regular DEM, LS-DEM, and analytical models. VLS-DEM is shown to give physically accurate results, comparable to analytical theory, even for highly complex systems such as those with concave interlocked particles.