The aim of this work is to look into the applicability of Discrete Element Modelling (DEM) coupled to Computational Fluid Dynamics (CFD) to simulate micro-scale colloidal particles immersed in fluid. Numerical methods were implemented through the commercial framework of EDEM2.3. As opposed to dissolved matter, which behaves as a continuum within the fluid medium, particulate matter is made of discrete entities that interact amongst themselves, and with the fluid and any physical boundaries. Particulate matter is ubiquitous in many purification processes that would beneficiate from having an easy way to model particle dynamics immersed in water. In an effort to understand better the dynamics of particle deposition under surface forces and hydraulic forces, a micro-scale numerical model was built adopting both a mechanistic and a statistical approach to represent the forces involved in colloidal suspension. The primary aim of the model was to simulate particle aggregation, deposition and cluster re-suspension in real world micro-systems. Case studies include colloidal flocculation in a constricted tube, and colloidal fouling around membrane filtration feed spacers. This work used a DEM-CFD coupling method that combined the DEM particle flow simulation with hydrodynamics forces from a velocity field computed through CFD. It also implemented boundary-particle and particle-particle interactions by enabling the modelling of surface and interfacial forces. Two kinds of coupling method were considered: two-way and one-way coupling. Two-way coupling is suitable for high particle concentration flow where particle loading affects the hydrodynamics. One-way coupling is suitable for dispersed particle configuration where the flow field is assumed to be undisturbed by the particles. The advantages and drawbacks of both techniques for micron-size particles were investigated. EDEM 2.3 was customised with plug-ins to implement Van der Waals forces and Brownian forces and its post-processing features offered the ability to investigate easily the microparticles behaviour under the influence of fluid forces. In this context, DEM-CFD modelling using EDEM 2.3 represents an improvement on previously published works as it enables higher visibility and reproducibility along with increasing the number of potential users of such modelling. Emphasis was given in presenting original findings and validation results that illustrate DEMCFD applicability, with respect to modelling of hydraulically mediated colloidal surface interaction; while highlighting factors that limit the ability of the technique. For instance, the effect of particle disturbance on the surrounding medium currently proves difficult to model.

In this PhD some key computational and algorithmic aspects of the Combined Finite Discrete Element Method (FDEM) are critically evaluated and either alternative novel or improved solutions have been proposed, developed and tested. In particular, two novel algorithms for contact detection have been developed. Also a comparative study of different contact detection algorithms has been made. The scope of this work also included large and grand scale FDEM problems that require intensive use of CPU; thus, novel parallelization solutions for grand scale FDEM problems have been developed and implemented using the MPI (Message Passing Interface) based domain decomposition. In this context a special attention is paid to the rapidly developing multi-core desktop architectures. The proposed novel solutions have been intensively validated and verified and demonstrated using various problems from literature.

This work examines the fundamental flow behaviour of granular materials under conditions relevant to blast furnace. Such a study may have some impact on the development of new technology to improve performance of blast furnace operation. The blast furnace operation involves rich granular dynamics phenomena which currently attract a strong interest from wide scientific and engineering community. In this work, percolation phenomenon is analyzed extensively. Percolation phenomenon is one of the most significant factors which cause particle segregation and mixing. In blast furnace when sinter and coke of different size and density are charged, percolation phenomenon occurs. In this work percolation properties like percolation velocity, residence time distribution and radial dispersion are checked for different material properties of percolating particles. It was found that percolation behaviour is related to many factors. Percolation properties of a single particle and also for batches of percolating particle were examined. The effect of external forces on percolation properties is also checked. DEM simulation method was found to be suitable for analysis of percolation flow behaviour of different types of particles. It was also found that the change of packed bed conditions has a great impact on particle percolation and segregation behaviour. In a packed bed, vibration and liquid of different properties were introduced. Particle dynamics in descending packed bed condition was checked. The effect of vibration and descending velocity was measured for percolation behaviour. Both vibration frequency and amplitude are important factors for particle flow in such a packed bed. Descending velocity of packed particles combined with vibration was found to have a pronounced impact on percolation behaviour. Liquid properties like viscosity and density affect particle dynamics significantly. Particle segregation in a pile was investigated as an extension of the percolation study. The effects of diameter ratio of binary feed, initial mixing ratio, feed rate in case of central feeding on conical pile were investigated. It was found that all of those parameters affect particle flow and segregation. Flowing layer over static pile was simulated and velocity profile and mixing ratio in different layers were observed. 3-D Screening Layer model was validated by DEM and experiment. In case of multipoint feed system, a conical pile which is similar to the deadman of a blast furnace was generated and the flowing layer characteristics over this static pile was also analysed.

University of Macau / Faculty of Science and Technology / Department of Civil and Environmental Engineering

Master of Science / Department of Grain Science and Industry / Kingsly Ambrose / It is a well-known phenomenon that the break-release, particle size and size distribution of wheat milling are functions of machine operational parameters and grain properties. Due to the non-uniformity in characteristics and properties of wheat kernel, the kernel physical and mechanical properties may affect the size reduction process. The discrete element method (DEM) is a numerical modeling technique that can be used to study and understand the effect of physical and mechanical properties of a material on processing. The overall objective of this study is to develop a DEM model of the 1st break wheat milling process. In this study, different physical and mechanical properties of wheat mill streams were determined for using as the input parameters in DEM model development. The particle size and size distribution (PSD), true, bulk and tapped density, young’s modulus, coefficient of static and rolling friction, and coefficient of restitution were measured for wheat kernel, 1st break and flour from hard red winter (HRW), hard red spring (HRS), and soft red winter (SRW) wheat. Overall moisture content was found to have a greater significant effect on the physical properties i.e. density and PSD of the mill streams than material properties i.e. Young’s modulus, coefficients of friction and coefficient of restitution. The DEM model of 1st break wheat milling was developed using both single and multi-sphere approaches. The single sphere approach simulated the size reduction of a spherical cluster of bonded particles with mono-sized particles. The model was simulated for hard red winter (HRW) wheat milling at 16% moisture levels and validated using lab scale milling trials giving a PSD of 437.73 m with a percent deviation of prediction of 235.37. The deviation of prediction was reduced to 192.29 with a mean PSD of 371.52 m by conducting sensitivity analysis by modifying the shear modulus and coefficient of restitution values. In the multi-sphere approach, a bonded cluster resembling a wheat kernel in shape and size was used to simulate the milling process. The model predicted a 1st break PSD of 412.65 µm which had a deviation of 185.89 from lab scale and 156.78 from plant scale milling. The model could however satisfactorily predict the variation in PSD from 1st break milling with moisture content with reasonable accuracy. Future capabilities using the model include performing additional sensitivity analysis to understand the effect of other mechanical properties of wheat on the 1st break PSD. It can also be used to improve the 1st break release during wheat milling.

Many powders and particulate solids are stored and handled in large quantities across various industries. These solids often encounter handling and storage difficulties that are caused by the material cohesion. The cohesive strength of a bulk material is a function of its past consolidation stress. For example, high material cohesive strength as a result from high storage stresses in a silo can cause ratholing problems during discharge. Therefore, it is essential to consider the stress-history dependence when evaluating such handling behaviour. In recent years the Discrete Element Method (DEM) has been used extensively to study the complex behaviour of granular materials. Whilst extensive DEM studies have been performed on cohesionless solids, much less work exists on modelling of cohesive solids. The commonly used DEM models to model adhesion such as the JKR, DMT and linear cohesion models have been shown to have difficulty in predicting the stress-history dependent behaviour for cohesive solids. DEM modelling of cohesive solid at individual particle level is very challenging. To apply the model at single particle level accurately would require one to determine the model parameters at particle level and consider the enormous complexity of interfacial interaction. Additionally it is computationally prohibitive to model each and every individual particle and cohesion arising from several different phenomena. In this study an adhesive elasto-plastic contact model for the mesoscopic discrete element method (DEM) with three dimensional non-spherical particles is proposed with the aim of achieving quantitative predictions of cohesive powder flowability. Simulations have been performed for uniaxial consolidation followed by unconfined compression to failure using this model. Additionally, the scaling laws necessary to produce scale independent predictions for cohesionless and cohesive solids was also investigated. The influence of DEM input parameters and model implementation have been explored to study the effect of particle (meso-scale) properties on the bulk behaviour in uniaxial test simulation. The DEM model calibration was achieved using the Edinburgh Powder Tester (EPT) – an extended uniaxial tester to measure flowability of bulk solids. The EPT produced highly repeatable flowability measurements and was shown to be a good candidate for DEM model calibration. The implemented contact model has been shown to be capable of predicting the experimental flow function (unconfined compressive strength versus the prior consolidation stress) for a limestone powder which has been selected as a reference solid in the Europe wide PARDEM research network. Contact plasticity in the model is shown to affect the flowability significantly and is thus essential for producing satisfactory computations of the behaviour of a cohesive granular material. The model predicted a linear relationship between a normalized unconfined compressive strength and the product of coordination number and solid fraction. Significantly, it has been found that contribution of adhesive force to the limiting friction has a significant effect on bulk unconfined strength. Failure to include the adhesive contribution in the calculation of the frictional resistance may lead to under-prediction of unconfined strength and incorrect failure mode. The results provide new insights and propose a micromechanical based measure for characterising the strength and flowability of cohesive granular materials. Scaling of DEM input parameters in a 3D simulation of the loading regimes in a uniaxial test indicated that whilst both normal and tangential contact stiffness (loading, unloading, and load dependent) scales linearly with radius of the particle, the adhesive forces scales with the square of the radius of the particles. This is a first step towards a mesoscopic representation of a cohesive powder that is phenomenological based to produce the key bulk characteristics of a granular solid and the results indicate that it has potential to gain considerable computational advantage for large scale DEM simulations. The contact model parameters explored include particle contact normal loading stiffness, tangential stiffness, and contact friction coefficient. The DEM model implementation parameters included numerical time step, strain rate, and boundary condition. Many useful observations have been made with significant implications for the relative importance of the DEM input parameters. Finally the calibration procedure was applied to a spray dried detergent powder and the simulation results are compared to whole spectrum of loading regime in a uniaxial experiment. The experimental and simulation results were found to be in reasonable agreement for the flow function and compression behaviour.

Across industry the majority of raw materials handled are particulate in nature, ranging in size and properties from aggregates to powders. The stress regimes experienced by the granular solids vary and the exhibited bulk behaviours can be complex and unexpected. The prevalence of granular solids makes them an area of interest for industry and researchers alike as many challenges still remain, such as dealing with complex cohesive behaviour in materials, which often gives rise to handling difficulties. Storage and transportation are an important part of the process chain for industries where particulate solids are commonplace. Failure to properly account for the cohesive nature of a particulate solid can be costly as it can easily lead to blockages in a silo such as ratholing or arching near the outlet during discharge. The cohesive strength of a bulk material depends on the consolidation stress it has experienced. As a result, the stress history in the material leading up to a handling scenario needs to be considered when evaluating its handling behaviour. The Discrete Element Method (DEM) has been extensively used to simulate the behaviour of granular materials, however the majority of the focus has been on noncohesive systems. For cohesive solids, it is crucial that the stress history dependent behaviour is adequately captured. Many of the contact models commonly used in DEM simulations to simulate cohesive granular materials such as the JKR model or liquid bridge models are elastic in nature and may not capture the stress history dependent behaviour observed in cohesive particulate solids. A comprehensive study on the effect of cohesion arising from the addition of moisture on the behaviour of two types of LKAB iron ore fines (KPBO and KPRS) has been carried out. The addition of moisture to the sample has been found to have a significant effect on both kinds of fines. KPRS fines were found to have a much higher unconfined strength and flow function at higher moisture contents, and also show a greater increase in cohesion with the addition of moisture, while at moisture contents of less than 2% the KPBO fines demonstrate higher unconfined yield strength. The KPBO fines were also found to achieve a significantly looser initial packing at much lower moisture content when compared to the KPRS fines. The lateral pressure ratio has also been evaluated. In this study a mesoscopic adhesive contact model that accounts for contact plasticity and stress history dependency in the bulk solid, the Edinburgh Elasto-Plastic Adhesion (EEPA) mode, has been presented and mathematically verified. A parametric study of the DEM contact model parameters was conducted to gain a deeper understating of the effect of input parameters on the simulated cohesive bulk behaviour. The EEPA contact model has been used to predict an experimental flow function of KPRS iron ore fines. The contact model has demonstrated the ability to capture the stress history dependent behaviour that exists in cohesive granular solids. The DEM simulations provide a very close match to the experimental flow functions, with the predicted unconfined strengths found to be within the standard deviations of the experimental results. Investigations into the failure mode predicted by the DEM simulations show that the samples are failing from the development of shear planes similar to those observed experimentally. The effect of increasing levels of adhesion has been explored for a flat bottomed silo where the level of adhesion has been varied. The DEM simulations were found to capture the major phenomena occurring in silo discharge including the various flow zones associated with a flat bottomed silo. Funnel flow, the effective transition and mass flow which are associated with a mixed flow pattern were observed in the model silo. The location of the effective transition height was identified: above this was mass flow. The velocity determined from the discharge rate was found to be in excellent agreement with the velocity profiles found in the zones of mass flow. A high velocity core flow zone was observed above the outlet where velocities were greater than 1.25 times the mass flow velocity, VMF. The level of adhesion in the silo was found to affect the discharge rate - a reduced flow rate was found until the eventual blockage of the silo at a high level of adhesion was found. As the level of adhesion increased the probability of arching also increased, and the formation of intermittent arching behaviour was noted in the cases with higher levels of adhesion in the system. The development of both temporary and permanent cohesive arches over the silo outlet were also observed with stopped flow from the silo.

Granular materials are in abundance in nature and are estimated to constitute over 75% of all raw materials passing through the industry. Granular or particulate solids are thus of considerable interest to many industrial sectors and research communities, where many unsolved challenges still remain. This thesis investigates the micro- and macro-phenomena in densely packed particulate systems by means of the Discrete Element Method (DEM), which is a numerical tool for analysing the internal complexities of granular material as the mechanical interactions are considered at the grain scale. It presents an alternative approach to phenomenological continuum approaches when studying localisation problems and finite deformation problems in granular materials. In order to develop a comprehensive theoretical understanding of particulate matter and to form a sound base to improve industrial processes, it is desirable to study the mechanical behaviour of granular solids subject to a variety of loading conditions. In this thesis, three loading actions were explored in detail, which are biaxial compression, rigid object penetration and progressive formation of granular piles. The roles of particle shape and contact friction in each of these loading scenarios were investigated. The resulting packing structures were compared and studied to provide a micromechanical insight into the development of contact force network which governs the collective response. The interparticle contact forces and displacements were then used to evaluate the equivalent continuum stress and strain components thus providing the link between micro- and macroscopic descriptions. The information collected from the evolution of strong contact network illustrates the underlying mechanism of force transmission and propagation. DEM simulations presented in this thesis demonstrate strong capability in predicting the bulk behaviour as well as capturing local phenomenon occurring in the system. The research first simulates a testing environment of biaxial compression in DEM, in which the phenomenon of strain localisation was investigated, with special attention given to the interpretation of underlying failure mechanism. Several key micromechanical quantities of interest were extracted to understand the bifurcation instability, such as force chains, contact orientation, particle rotation and void ratio. In the simulation of progressive formation of granular piles, a counterintuitive pressure profile with a significant pressure dip under the apex was predicted for three models under certain conditions. Both particle shape and preparation history were shown to be important in the resulting pressure distribution. During the rigid body penetration into a granular sample, the contact forces were used to evaluate the equivalent continuum stress components. Significant stress concentration was developed around the punch base which further led to successive collapse and reformation of force chains. Taking the advantage of micromechanical analysis at particle scale, two distinct bearing failure mechanisms were identified as the penetration proceeded. To further quantify the nature of strain mobilisation leading to failure, Particle Image Velocimetry (PIV) was employed to measure the deformation over small strain interval in association with shear band propagation in the biaxial test and deformation pattern in the footing test. The captured images from DEM simulation and laboratory experiments were evaluated through PIV correlation. This optical measuring technique is able to yield a significant improvement in the accuracy and spatial resolution of the displacement field over highly strained and localised regions. Finally, a series of equivalent DEM simulations were also conducted and compared with the physical footing experiments, with the objective of evaluating the capability of DEM in producing satisfactory predictions.

From pharmaceutical powders to agricultural grains, a great proportion of the materials handled in industrial situations are granular or particulate in nature. The variety of stesses that the matierals may experience and the resulting bulk behaviours may be complex. In agricultural engineering, a better understanding into agricultural processes such as seeding, harvesting, transporting and storing will help to improve the handling of agricultural grains with optimised solutions. A detailed understanding of a granular system is crucial when attempting to model a system, whether it is on a micro (particle) or macro (bulk) scale. As numerical capabilities are ever increasing, the Discrete Element Method (DEM) is becoming an increasingly popular numerical technique for computing the behaviour of discrete particels for both industrial and scientific applications. A look into the literature shows a lack of validation of what DEM can predict, specifically with respect to bulk behaviour. In addition, when validation studies are conducted, discrepancies between bulk responses in physical tests and numerical predictions using measured particles properties may arise. The aire of this research is to develop a methodology to calibrate DEM models for agricultural grains using data meaured in bulk physical tests. The methodology will have a wider application to granular solids in general and will advance understanding in the area of DEM model calibration. A contrasting set of granular materials were used to develop the methodology including 3 inorganic solids (single and paired glass beads, and polyethylene terephthalate pellets) and two organic materials (black eyes beans and black kidney beans). The developed methodology consists of three steps: 1. The development of bulk physical tests to measure the bulk responses that will be used to calibrate the DEM models, 2. The creation of the numerical dataset that will describe how the DEM input parameters influence the bulk responses , and 3. The optimisation of the DEM parameters using a searching algorithm and the results from Step 1 and 2. Two laboratory devices were developed to provide calibration data for the proposed methodology: a rotating drum and an confined compression test. These devices were chosen as they can produce bulk responses that are repeatable and easy to quantify, as well as generate discriminating results in numerical simulations when DEM parameters are varied. The bulk response determined from the rotating drum device was the dynamic angle of repose Ør formed when the granular material in a 40% filled drum is rotating at a speed of 7 rpm. the confined compression apparatus was used to determine the bulk stiffness of a system by monitoring the change in void ratio from the stress applied during a loading and unloading cycle. The gradient of the loading and unloadng curves termed λ and κ respectively were chosen as the bulk responses to calibrate the DEM models. The experimental results revealed that the dynamic Ør was significantly influences by the particle aspect ration and boundary conditions. The stiffness parameters were found to be predominantly influences by the initial packing arrangement. The numerical dataset describing how the DEM input parameters influence the numerical bulk responses was created by simulating the bulk physical tests, varying selected DEM parameters and monitoring the effects on bulk parameters. To limit the number of simulations required, design of experiment (DOE) methods were used to determine a reduced factorial matrix of simulations. In additions, an extensive parametric investigation on the non-optimised parameters as well as a scaling sensitivity study was carried out. The final step in determining the optimised parameters is to use a searching algorithm to infer the DEM parameters based on the numerical dataset and used the experimental results as calibration data. To perform a comparative study, tow searching algorithms were explored: the first was a simple method based on Microsoft Excel's Solver algorithm coupled with a weighted inverse distance method. The second made used of the statistical analysis program Statistica. It was shown that the Excel Solver algorithm is simpler and quicker to use but for the present first implementation, could only perform an optimisation based on two bulk responses. Statistica required the creation of a staistical model based on the numerical dataset before using the profiling and desirability searching technique, but was able to optimise the parameter using all three bulk responses. A verification and validation of the optimisation methodology was conducted using the optimised parameters for the black eyed beans. A verification was cnducted by simulating the two calibration experiments using the optimsed parameters and comparing these with the experiments. In addition, a validation was peformed by predicting the response of ta shallow footing penetration on a bed of black eyed beans. It was found that DEM simulations using optimised parameters predicted vertical stress on the footing during penetration to an acceptable degree of accuracy for industrial applications (<10%) at penetration depths up to 30mm.

This thesis presents a new bonded particle model that accurately predicts the wideranging behaviour of cementitious materials. There is an increasing use of the Discrete Element Method (DEM) to study the behaviour of cementitious materials such as concrete and rock; the chief advantage of the DEM over continuum-based techniques is that it does not predetermine where cracking and fragmentation initiate and propagate, since the system is naturally discontinuous. The DEM’s ability to produce realistic representations of cementitious materials depends largely on the implementation of an inter-particle bonded-contact model. A new bonded-contact model is proposed, based on the Timoshenko beam theory which considers axial, shear and bending behaviour of inter-particle bonds. The developed model was implemented in the commercial EDEM code, in which a thorough verification procedure was conducted. A full parametric study then considered the uni-axial loading of a concrete cylinder; the influence of the input parameters on the bulk response was used to produce a calibrated model that has been shown to be capable of producing realistic predictions of a wide range of behaviour seen in cementitious materials. The model provides useful insights into the microscopic phenomena that result in the bulk loading responses observed for cementitious materials such as concrete. The new model was used to simulate the loading of a number of deformable structural elements including beams, frames, plates and rings; the numerical results produced by the model provided a close match to theoretical solutions.