Modeling of damage evolution in soft-wood perpendicular to grain by means of a discrete element approach

The anisotropy of wood within the radial–tangential (RT) growth plane has a major influence on the cracking behavior perpendicular to grain. Within the scope of this work, a two-dimensional discrete element model is developed, consisting of beam elements for the representation of the microstructure of wood. Molecular dynamics simulation is used to follow the time evolution of the model system during the damage evolution in the RT plane under various loading conditions. It is shown that the results are in good agreement with experiments on spruce wood, and that the presented discrete element approach is applicable for detailed studies of the dependence of the microstructure on mesoscopic damage mechanism and dynamics of crack propagation in microstructured and cellular materials like wood.     

Multi-continuum analysis of thermally induced matrix cracking

Matrix micro-cracking due to thermal loading is a major concern in composite cryogenic tanks because it presents permeation paths for the stored fluids and gases. Accurate prediction of composite damage due to micro-crack initiation is thus an important aspect of tank analysis and design. In the research presented, failure criteria are applied at both the composite (macro-) and constituent (micro-) scale in an effort to assess the most effective analysis techniques for predicting composite damage. Constituent scale information is developed using multi-continuum theory, a classic strain decomposition approach. Numerical predictions are correlated against experimental results.     

A modelling and verification approach for soybean seed particles using the discrete element method

To build a discrete element method (DEM) model of soybean seed particles, the shape and size of soybean seed particles were measured and analysed. The results showed that the shape of a soybean seed particle could be approximated to an ellipsoid and that the dispersity in size could be approximated by a normal distribution. Additionally, a certain functional relationship between the primary dimension and secondary dimensions was determined. On this basis, an approach for modelling soybean seed particles based on the multi-sphere (MS) method was proposed. The soybean seed particle was simplified to an ellipsoid with the averaged size of one hundred randomly selected soybean seeds. The model of a single soybean seed particle was built by filling spheres within the ellipsoid. For modelling soybean seed assembly, the primary dimension was generated according to the normal distribution, and the other secondary dimensions were calculated based on their relationships with the primary dimension. In this way, the model of soybean seed assembly with different sizes and distributions was built. In this paper, four varieties of soybean seed were used. By comparing the simulated results and experimental results both in piling tests and “self-flow screening” tests, when the number of filling spheres was five, the simulated results were close to those obtained experimentally. Therefore, the feasibility and validity of the modelling method for soybean seed particles that we proposed were verified. Finally, an application case was employed to show how to use the soybean seed particle model and the discrete element method to analyse the discharging process of a silo.     

Experimental study and discrete element method simulation of Geldart Group A particles in a small-scale fluidized bed

Geldart Group A particles are of great importance in various chemical processes because of advantages such as ease of fluidization, large surface area, and many other unique properties. It is very challenging to model the fluidization behavior of such particles as widely reported in the literature. In this study, a pseudo-2D experimental column with a width of 5 cm, a height of 45 cm, and a depth of 0.32 cm was developed for detailed measurements of fluidized bed hydrodynamics of fine particles to facilitate the validation of computational fluid dynamic (CFD) modeling. The hydrodynamics of sieved FCC particles (Sauter mean diameter of 148 µm and density of 1300 kg/m³) and NETL-32D sorbents (Sauter mean diameter of 100 µm and density of 480 kg/m³) were investigated mainly through the visualization by a high-speed camera. Numerical simulations were then conducted by using NETL’s open source code MFIX-DEM. Both qualitative and quantitative information including bed expansion, bubble characteristics, and solid movement were compared between the numerical simulations and the experimental measurement. The cohesive van der Waals force was incorporated in the MFIX-DEM simulations and its influences on the flow hydrodynamics were studied.     

Simulation of granular crystallization of cubic particles in twisting container using discrete element method

Granular compaction is a process in which the volume fraction, or density, of the granular materials increases when an excitation is applied. A recent experiment reported that twisting a large number of cubic particles in a cylindrical container leads to an ordered and dense arrangement. This structure is similar to the crystal lattice formed in solidification process. In this article, this phenomenon is repeated by using discrete element method (DEM) simulation. Two different shaped containers are used and it is found that the rectangular angles between the sidewalls and the bottom,namely wall effect, plays a key role. In addition, gravitation is also a very important parameter in this process. The higher gravitation added, the faster crystallization process is achieved. On the contrary, shear force due to friction between particles may slow down this process.     

Prediction of hopper discharge rate using combined discrete element method and artificial neural network

An Artificial Neural Network (ANN) was developed to predict the mass discharge rate from conical hoppers. By employing Discrete Element Method (DEM), numerically simulated flow rate data from different internal angles (20°–80°) hoppers were used to train the model. Multi-component particle systems (binary and ternary) were simulated and mass discharge rate was estimated by varying different parameters such as hopper internal angle, bulk density, mean diameter, coefficient of friction (particle-particle and particle-wall) and coefficient of restitution (particle-particle and particle-wall). The training of ANN was accomplished by feed forward back propagation algorithm. For validation of ANN model, the authors carried out 22 experimental tests on different mixtures (having different mean diameter) of spherical glass beads from different angle conical hoppers (60° and 80°). It was found that mass discharge rate predicted by the developed neural network model is in a good agreement with the experimental discharge rate. Percentage error predicted by ANN model was less than ±13%. Furthermore, the developed ANN model was also compared with existing correlations and showed a good agreement.     

A numerical study on the impact resistance of composite shells using an energy based failure model

This paper presents a numerical study on the impact resistance of composite shells laminates using an energy based failure model. The damage model formulation is based on a methodology that combines stress based, continuum damage mechanics (CDM) and fracture mechanics approaches within a unified procedure by using a smeared cracking formulation. The damage model has been implemented as a user-defined material model in ABAQUS FE code within shell elements. Experimental results obtained from previous works were used to validate the damage model. Finite element models were developed in order to investigate the pressure and curvature effects on the impact response of laminated composite shells.     

The importance of modelling ballast particle shape in the discrete element method

The discrete element method has been used to model railway ballast. Particles have been modelled using both spheres and clumps of spheres. A simple procedure has been developed to generate clumps which resemble real ballast particles much more so than spheres. The influence of clump shape on the heterogeneous stresses within an aggregate has been investigated, and it has been found that more angular clumps lead to a greater degree of homogeneity. A box test consisting of one cycle of sleeper load after compaction has been performed on an aggregate of spheres and also on an alternative aggregate of clumps. The interlocking provided by the clumps provides a much more realistic load- deformation response than the spheres and the clumps will be the basis for future work on ballast degradation under cyclic loading.     

A procedure for superposing linear cohesive laws to represent multiple damage mechanisms in the fracture of composites

The relationships between a resistance curve (R-curve), the corresponding fracture process zone length, the shape of the traction-displacement softening law, and the propagation of fracture are examined in the context of the through-the-thickness fracture of composite laminates. A procedure for superposing linear cohesive laws to approximate an experimentally-determined R-curve is proposed. Simple equations are developed for determining the separation of the critical energy release rates and the strengths that define the independent contributions of each linear softening law in the superposition. The proposed procedure is demonstrated for the longitudinal fracture of a fiber-reinforced polymer-matrix composite. It is shown that the R-curve measured with a Compact Tension Specimen test cannot be predicted using a linear softening law, but can be reproduced by superposing two linear softening laws.     

A discrete element method for the simulation of CFRP cutting

Orthogonal machining of unidirectional carbon fiber-reinforced polymer (UD-CFRP) composites is simulated using discrete element method (DEM). The objective of this work is to present a simple numerical model that allows the study the machining of unidirectional composites during orthogonal cutting. To control the physicochemical phenomena that occur during cutting, it is necessary to identify the parameters of contact, very difficult to measure experimentally. The DEM numerical simulation is presented then as an alternative to the problem. This tool has helped to recreate the physical mechanisms identified experimentally and to understand the origin of the abrasive wear of carbide tools. The observation of the chip formation using a high speed video camera made possible to validate qualitatively the results of numerical simulation by discrete elements. This tool can also determine the cutting forces quite close to reality.     

Microscopic investigation of the packing features of soft-rigid particle mixtures using the discrete element method

Soft-rigid mixtures (SRMs) have become popular materials in civil engineering applications for environmental protection because of their outstanding engineering properties. In soft-rigid granular systems, packing features strongly affect shear behavior and directly reflect internal stability. However, the packing features of SRMs have not been previously reported. The aim of this study is to explore the effect of material susceptibility on packing features from a microscopic perspective. First, fifty-three numerical assemblies were established to thoroughly investigate the effects of the size ratio and soft content on several microscopic quantities, e.g., the particle structure, stress network, and local void. Then, the effects of the confining stress and stiffness ratio were analyzed from another eighteen assemblies by six chosen indexes. The results provide microscopic insights into the void structures and stress transmission of SRMs in a packing state.     

Particle screening phenomena in an oblique multi-level tumbling reservoir: a numerical study using discrete element simulation

Due to their wide usage in industrial and technological processes, granular materials have captured great interest in recent research. The related studies are often based on numerical simulations and it is challenging to investigate computational phenomena of granular systems. Particle screening is an essential technology of particle separation in many industrial fields. This paper presents a numerical model for studying the particle screening process using the discrete element method that considers the motion of each particle individually. Dynamical quantities like particle positions, velocities and orientations are tracked at each time step of the simulation. The particular problem of interest is the separation of round shape particles of different sizes using a rotating tumbling vertical cylinder while the particulate material is continuously fed into its interior. This rotating cylinder can be designed as a uniform or stepped multi level obliqued vertical vessel and is considered as a big reservoir for the mixture of particulate material. The finer particles usually fall through the sieve openings while the oversized particles are rebounded and ejected through outlets located around the machine body. Particle–particle and particle–boundary collisions will appear under the tumbling motion of the rotating structure. A penalty method, which employs spring-damper models, will be applied to calculate the normal and frictional forces. As a result of collisions, the particles will dissipate kinetic energy due to the normal and frictional contact losses. The particle distribution, sifting rate of the separated particles and the efficiency of the segregation process have been studied. It is recognized that the screening phenomenon is very sensitive to the machines geometrical parameters, i.e. plate inclinations, shaft eccentricities and aperture sizes in the sieving plates at different levels of the structure. The rotational speed of the machine and the feeding rate of the particles flow have also a great influence on the transportation and segregation rates of the particles. In an attempt to better understand the mechanism of the particle transport between the different layers of the sifting system, different computational studies for achieving optimal operation have been performed.     

Granular temperature with discrete element method simulation in a bubbling fluidized bed

The Discrete Element Method (DEM) plays an important role in understanding and modeling the kinetic characteristics in granular systems. A soft-sphere method with a linear spring–dashpot model was used in the simulation of a bubbling fluidized bed. The time-averaged granular temperature and vertical particle velocity at different heights were numerically studied and compared to experimental measurements of Müller. The influence of a velocity-dependent coefficient of restitution and three drag models were also investigated in this work. Good agreement was found between the DEM simulation and Müller’s experiment, especially using the DiFelice drag model. The variable coefficient of restitution, with a sufficiently high yielding relative velocity, gives a granular temperature that is a little lower compared to that of a constant coefficient of restitution, while it predicts a more intense velocity fluctuation, with a lower yielding relative velocity. By comparing the granular temperature in the vertical direction and in the transverse direction, a strong anisotropy is found in the bed.     

A calibration framework for discrete element model parameters using genetic algorithms

In this research, a universal framework for automated calibration of microscopic properties of modeled granular materials is proposed. The proposed framework aims at industrial scale applications, where optimization of the computational time step is important. It can be generally applied to all types of DEM simulation setups. It consists of three phases: data base generation, parameter optimization, and verification. In the first phase, DEM simulations are carried out on a multi-dimensional grid of sampled input parameter values to generate a database of macroscopic material responses. The database and experimental data are then used to interpolate the objective functions with respect to an arbitrary set of parameters. In the second phase, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the calibration multi-objective optimization problem. In the third phase, the DEM simulations using the results of the calibrated input parameters are carried out to calculate the macroscopic responses that are then compared with experimental measurements for verification and validation.The proposed calibration framework has been successfully demonstrated by a case study with two-objective optimization for the model accuracy and the simulation time. Based on the concept of Pareto dominance, the trade-off between these two conflicting objectives becomes apparent. Through verification and validation steps, the approach has proven to be successful for accurate calibration of material parameters with the optimal simulation time.     

Fracture modeling using a microstructural mechanics approach--II. Finite element analysis

In the accompanying paper [C.S. Chang, T.K. Wang, L.J. Sluys, J.G.M. van Mier, J. Eng. Fract. Mech. (this volume)], the theoretical aspects of a stress-strain model are described based on a microstructural approach. A finite element formulation was presented that incorporates the developed stress-strain relationship. In this paper the results of finite element analyses are described. The paper is focused on two main issues: the difference between the micropolar and the non-polar microstructural model, and the performance of the model respect to mesh size dependence. Specimens in uniaxial tension test and in biaxial tension-shear tests have been analyzed. To evaluate the applicability of this method, the finite element results are also compared with measured experimental results.     

Micromechanical modeling of damage and fracture of unidirectional fiber reinforced composites: A review

An overview of methods of the mathematical modeling of deformation, damage and fracture in fiber reinforced composites is presented. The models are classified into five main groups: shear lag-based, analytical models, fiber bundle model and its generalizations, fracture mechanics based and continuum damage mechanics based models and numerical continuum mechanical models. Advantages, limitations and perspectives of different approaches to the simulation of deformation, damage and fracture of fiber reinforced composites are analyzed.     

Analysis of a triangulation based approach for specimen generation for discrete element simulations

Discrete element methods are emerging as useful numerical analysis tools for engineers concerned with granular materials such as soil, food grains, or pharmaceutical powders. Obviously, the first step in a discrete element simulation is the generation of the geometry of the system of interest. The system geometry is defined by the boundary conditions as well as the shape characteristics (including size) and initial coordinates of the particles in the system. While a variety of specimen generation methods for particulate materials have been developed, there is no uniform agreement on the optimum specimen generation approach. This paper proposes a new triangulation based approach that can easily be implemented in two or three dimensions. The concept of this approach (in two dimensions) is to triangulate a system of points within the domain of interest, creating a mesh of triangles. Then the particles are inserted as the incircles of these triangles. Extension to three dimensions using a mesh of tetrahedra and inserting the inspheres is relatively trivial. The major advantages of this approach include the relative simplicity of the algorithm and the small computational cost associated with the preparation of an initial particle assembly. The sensitivity of the characteristics of the particulate material that is generated to the topology of the triangular mesh used is explored. The approach is compared with other currently used methods in both two and three dimensions. These comparisons indicate that while this approach can successfully generate relatively dense two-dimensional particle assemblies, the three- dimensional implementation is less effective at generating dense systems than other available approaches. The research presented in this paper made use of software developed by other researchers. For the two-dimensional study the program Triangle developed by Jonathan Shewchuk was used. The three-dimensional analysis used the Geompack++ program developed by Barry Joe as well as an implementation of the Jodrey and Tory (1985) algorithm by Monika Bargiel and Jacek Moscinski called NSCP3D.     

Recent progress on the discrete element method simulations for powder transport systems: A review

Powder transport systems are ubiquitous in various industries, where they can encounter single powder flow, two-phase flow with solids carried by gas or liquid, and gas–solid–liquid three-phase flow. System geometry, operating conditions, and particle properties have significant impacts on the flow behavior, making it difficult to achieve good transportation of granular materials. Compared to experimental trials and theoretical studies, the numerical approach provides unparalleled advantages over the investigation and prediction of detailed flow behavior, of which the discrete element method (DEM) can precisely capture complex particle-scale information and attract a plethora of research interests. This is the first study to review recent progress in the DEM and coupled DEM with computational fluid dynamics for extensive powder transport systems, including single-particle, gas–solid/solid–liquid, and gas–solid–liquid flows. Some important aspects (i.e., powder electrification during pneumatic conveying, pipe bend erosion, non-spherical particle transport) that have not been well summarized previously are given special attention, as is the application in some new-rising fields (ocean mining, hydraulic fracturing, and gas/oil production). Studies involving important large-scale computation methods, such as the coarse grained DEM, graphical processing unit-based technique, and periodic boundary condition, are also introduced to provide insight for industrial application. This review study conducts a comprehensive survey of the DEM studies in powder transport systems.     

Numerical study of the interfaces of 3D‐printed concrete using discrete element method

3D concrete printing is an additive manufacturing method which reduces the time and improves the efficiency of the construction process. Structural behavior of printed elements is strongly influenced by the properties of the material and the interface surfaces. The printing process creates interface surfaces between layers in the horizontal and vertical directions. The bond strength between layers is the most critical property of printed elements. In this paper, the structural behavior of printed elements is studied using the discrete element method. The material is modelled using discrete particles with bonding between them. A new discrete model of a multilayer geometry is presented to study the behavior of the interfaces of printed concrete. The layers are made up of randomly placed particles to simulate the heterogeneous nature of concrete. The numerical model is developed to simulate the flexural behavior of multilayer specimens. A four‐point flexural test is simulated considering the interface surfaces between layers. This numerical model provides relevant results to improve the behavior of this kind of structural elements. The aim of this work is to provide a discrete element model to predict the mechanical behavior of 3D concrete printed components.     

Convergence and stability analysis of the deformable discrete element method

This work investigates numerical properties of the algorithm of the discrete element method (DEM) employing deformable circular disks presented in the authors' earlier publication. The new formulation called the deformable DEM (DDEM) enhances the standard DEM (SDEM) by introducing an additional (global) deformation mode caused by the stresses in the particles induced by the contact forces. An accurate computation of the contact forces would require an iterative solution of the implicit relationship between the contact forces and particle displacements. In order to preserve efficiency of the DEM, the new formulation has been adapted to the explicit time integration. It has been shown that the explicit DDEM algorithm is conditionally stable and there are two restrictions on its stability. Except for the limitation of the time step as in the SDEM, the stability in the DDEM is governed by the convergence criterion of the iterative solution of the contact forces. The convergence and stability limits have been determined analytically and numerically for selected regular and irregular configurations. It has also been found out that the critical time step in DDEM remains unchanged with respect to the SDEM.