Review: Calibration of the discrete element method

Modeling Mechanochemical Depolymerization of PET in Ball-Mill Reactors Using DEM Simulations

Developing efficient and sustainable chemical recycling pathways for consumer plastics is critical for mitigating the negative environmental implications associated with their end-of-life management. Mechanochemical depolymerization reactions have recently garnered great attention, as they are recognized as a promising solution for solvent-free transformation of polymers to monomers in the solid state. To this end, physics-based models that accurately describe the phenomena within ball mills are necessary to facilitate the exploration of operating conditions that would lead to optimal performance. Motivated by this, in this paper we develop a mathematical model that couples results from discrete element method (DEM) simulations and experiments to study mechanically-induced depolymerization. The DEM model was calibrated and validated via video experimental data and computer vision algorithms. A systematic study on the influence of the ball-mill operating parameters revealed a direct relationship between the operating conditions of the vibrating milling vessel and the total energy supplied to the system. Moreover, we propose a linear correlation between the high-fidelity DEM simulation results and experimental monomer yield data for poly(ethylene terephthalate) depolymerization, linking mechanical and energetic variables. Finally, we train a reduced-order model to address the high computational cost associated with DEM simulations. The predicted working variables are used as inputs to the proposed mathematical expression which allows for the fast estimation of monomer yields.

Improvement of a pharmaceutical powder mixing process in a tote blender via DEM simulations

An industrial-scale pharmaceutical powder blending process was studied via discrete element method (DEM) simulations. A DEM model of two active pharmaceutical ingredient (API) components and a combined excipient component was calibrated by matching the simulated response in a dynamic angle of repose tester to the experimentally observed response. A simulation of the 25-minute bin blending process predicted inhomogeneous API distributions along the rotation axis of the blending container. These concentration differences were confirmed experimentally in a production-scale mixing trial using high-performance liquid chromatography analysis of samples from various locations in the bin. Several strategies to improve the blend homogeneity were then studied using DEM simulations. Reversing the direction of rotation of the blender every minute was found to negligibly improve the blending performance. Introducing a baffle into the lid at a 45° angle to the rotation axis sped up the axial mixing and resulted in a better final blend uniformity. Alternatively, rotating the blending container 90° around the vertical axis five minutes prior to the process end was predicted to reduce axial segregation tendencies.

Discrete element modeling and experimental study of biomechanical properties of cotton stalks in machine-harvested film-stalk mixtures

To address the current problems of low accuracy and poor reliability of the discrete element model of cotton stalks, as well as the difficulty of guiding the design and optimization of the equipment through simulations, the discrete element modeling and physical-mechanical tests of cotton stalks in machine harvested film-stalk mixtures are carried out. The peak tensile force F j max , the peak pressure F y max , the peak bending force F w max , the peak shear force F j max , and the force-displacement (F-x) curves of cotton stalks are obtained from the physical tests. The discrete element model of double-layer cotton stalks based on the flat-joint model is established with the PFC3 D software. The F y max is taken as the response value, and the microscopic parameters of the cotton stalk model are used as the test factors, then the Plackett-Burman test, the steepest climb test, and the Box-Behnken test are sequentially designed using Design-Expert software. The second-order regression model describing the relationship between the F y max and the microscopic parameters is established. The optimal parameter combinations of the microscopic parameters are obtained, and then they are utilized to construct the compression, bending, and shear models of cotton stalks and to carry out the validation tests. The results confirm that the established discrete element model could accurately characterize the biomechanical properties of cotton stalks and that the parameter calibration method is reasonable, which could provide a reference for the discrete element modeling of cotton stalks and other stalks, and also offer a theoretical basis for the research of the crushing and separation mechanism of the film-stalk mixtures and the development of the equipment.

Measurement and calibration of gluten pellets discrete element parameters at varied moisture content

To quickly calibrate the discrete element parameters (DEP) of pellets with different moisture content (MC), the angle of repose (AoR) was taken as the target value to conduct experimental and simulation research on gluten pellets. The experimental method obtained the intrinsic parameters, contact parameters, and AoR of pellets with different moisture content. The parameters differed significantly under different moisture content (p < 0.05). The AoR-MC model (R2  = 0.987) was established. The Plackett-Burman test, steepest ascent test, and center compound test were carried out to establish the AoR-DEP model (R2  = 0.969) with a relative error less than or equal to 2.07%. The MC-DEP model was derived, and verified by the side plate lifting method with a relative error less than or equal to 2.58%. This paper provides a new method for calibrating DEP under different moisture content.

Feasibility Analysis of Calcium Carbonate Particle Trajectory Simulation in a Dual Horizontal Shaft Mixer

This article aims to investigate the feasibility of using discrete element software EDEM 2022.0 to simulate the trajectory of artificial marble patterns in a dual horizontal shaft mixer. Research was conducted on the mixing uniformity of particles in the mixing chamber, and the optimal speed range for particle mixing was established. By simulating the trajectory of pigment particles, the trajectories of the particles at different positions of the stirring paddle were obtained, and the trajectories were compared with the measured results. In the study of uniform particle mixing, the Lacey index at different speeds was compared, and the optimal speed range was established between 40 RPM and 60 RPM. Based on this, the particle trajectory simulation found that the motion trajectories of particles at different positions of the stirring paddle varied significantly. The particles in the stirring paddle rod exhibit a gradual trend, in which they gradually decrease as they approach the head of the stirring paddle. Finally, the feasibility of this method was established by comparing the simulated and actual patterns through proportional replication of the mixing process, and it was discovered that the two were similar.

Review of calibration strategies for discrete element model in quasi-static elastic deformation

This study first reviewed theories of the mechanical response of structures under loading, and the discrete element method provides a route for studying mechanical response including elastic deformation and structure failure. However, the direct acquisition of the microscopic parameters from the governing equations of the discrete element method via experiments encounters challenges. One possible strategy to obtain these microscopic parameters is parameter calibration that are widely used by researchers. Secondly, the governing equations and failure criterion of the discrete element method are summarized, and the microscopic parameters that would be calibrated are pinpointed. Next, the principles of classical calibration methods of discrete element method are explicated in detail, alongside the validation and discussion of their properties. Lastly, this study examined the applicability of calibrated parameters and points out that the size ratio, porosity, maximum radius, and minimum radius of particles should be identical in both the geometric calibration model and that for applications.

Calibration and verification of DEM parameters of wet-sticky feed raw materials

In order to improve the accuracy of the parameters needed in the discrete element method (DEM) simulation process of wet-sticky feed raw materials, the JKR contact model in DEM was used to calibrate and verify the physical parameters of wet-sticky feed raw materials. Firstly, the parameters that have a significant effect on the angle of repose were screened using a Plackett-Burman design, and the screened parameters were: MM rolling friction coefficient, MM static friction coefficient, and JKR surface energy. Then, the three screened parameters were selected as the influencing factors and the accumulation angle of repose was selected as evaluating indicator; thus, the performance optimization experiments were carried out with the quadratic orthogonal rotation design. Taking the experimentally measured angle of repose value of 54.25°as the target value, the significance parameters were optimized, and the optimal combination was obtained : MM rolling friction factor was 0.21, MM static friction factor was 0.51, and JKR surface energy was 0.65. Finally, the angle of repose and SPP tests were compared under the calibrated parameters. The results showed that the relative error of experimental and simulated tests in angle of repose was 0.57%, and the compression displacement and compression ratio of the experimental and simulated tests in SPP were 1.01% and 0.95%, respectively, which improved the reliability of the simulated results. The research findings provide a reference basis for simulation study and optimal design of related equipment for feed raw materials.

A DEM Model to Evaluate Refill Strategies of a Twin-Screw Feeder

Residence time distribution (RTD) modeling has proven to be a valuable tool for material tracking in continuous pharmaceutical processes. Refilling is thoroughly studied in the literature, but the main focus lies on the feed rate disturbances. The impact of the feeders themselves on intermixing of different material batches is often overlooked. Since the experimental methods to measure the RTD feeder discharging processes feeder are complex and material intensive, there is only limited experimental RTD data available in the literature. A DEM (discrete element method) simulation of a discharge of a twin-screw feeder shows that a large fraction of material that is moved and intermixed by the agitator. In addition to the intermixing, there is a tendency to discharge material located above the agitator early. In order to predict the behavior during multiple refill events, three models in order of increasing complexity are presented: (1) A simple exponential RTD assuming perfect intermixing of material batches; (2) a RTD model based on DEM results; (3) particle-level material tracking by extrapolation of the DEM results. All three of these models are able to predict the survival function of old material for late refills at low fill levels, however, earlier refills at high fill levels require more complex models to accurately represent the dynamics inside the hopper of the feeder.

Characterization of permanent deformation properties of densely-compacted unbound granular materials subjected to cyclic loading

To investigate the long-term deformation properties of unbound granular materials (UGM) that are ordinarily adopted to construct subgrade for high-speed railway, a series of medium-sized cyclic triaxial tests were performed to obtain the relationship between permanent strain and loading cycles under different cyclic stress levels. Moreover, DEM analysis was conducted for the samples to reveal the deformation mechanism and verify the strain developing tendency. It is found that the UGM samples present different long-term deformation properties under different cyclic stress levels. As cyclic stress increases, the permanent strain of UGM sample transfers from rapid stabilization to tardy stabilization, then to tardy failure and finally to rapid failure. Furthermore, the exponent in a power law function was selected as the critical indicator of deformation developing tendency. With the exponent obtained precisely in accordance with the strain rate, the deformation tendency can be analyzed quantitatively. Finally, the characteristics of interparticle force chains induced by different cyclic stress levels were obtained by DEM analysis, which provided evidences for the classification of long-term deformation properties of UGM samples. The achievements have guiding significance for the design of subgrade of both ballasted and unballasted high-speed railway.

Review on the chemical reduction modelling of hematite iron ore to magnetite in fluidized bed reactor

Steel production is considered as one of the major backbones of many economies. Though blast furnace is the primary route of steel production, the industries are willing to alternatives technologies such as the high temperature-controlled conversion of hematite to magnetite. The geological and mineralogical characteristics of the low-grade iron ores possess difficulties in their conventional enrichment. The literature concludes the advantages of high-temperature conversion in terms of easiness in downstream operations caused by decreased hardness and increased magnetic susceptibility of magnetite. The modelling work has been primarily focused on the direct reduction of iron ore to metallic iron. The present compilation discusses the scientific and engineering developments on the reduction-roasting of iron-ore followed by the CFD–DEM modelling and simulation work performed to reduce iron ore to magnetite. It provides a comprehensive review of the experimental and industrial progress done in the area.

Efficient DEM simulations of railway ballast using simple particle shapes

For complex shaped materials, computational efficiency and accuracy of DEM models are usually opposing requirements. In the literature, DEM models of railway ballast often use very complex and computationally demanding particle shapes in combination with very simple contact laws. In contrast, this study suggests efficient DEM models for railway ballast using simple particle shapes together with a contact law including more physical effects. In previous works of the authors, shape descriptors, calculated in a shape analysis of two types of ballast, were used to construct simple particle shapes (clumps of three spheres). Using such a shape in DEM simulations of compression and direct shear tests, accurate results were achieved only when the contact law included additional physical effects e.g. edge breakage. A parametrisation strategy was developed for this contact law comparing DEM simulations with the measurements. Now, all the constructed simple particle shapes are parametrised allowing to study their suitability and relating their shape descriptors to those of railway ballast. The most suitable particle shapes consist of non-overlapping spheres, thus have a high interlocking potential, and have lowest sphericity and highest convexity values. In a micromechanical analysis of the four best performing shapes, three shapes show similar behaviour on the bulk and the micro-scale, while one shape differs clearly on the micro-scale. This analysis shows, which shapes can be expected to produce similar results in DEM simulations of other tests/load cases. The presented approach is a step towards both efficient and accurate DEM modelling of railway ballast.

A DEM-Based Modeling Method and Simulation Parameter Selection for Cyperus esculentus Seeds

To build a DEM model of Cyperus esculentus seed particles, the shape and size of the Cyperus esculentus seed particles were measured and analyzed. The results showed that the dispersity in size had a normal distribution. Additionally, a certain functional relationship between the primary dimension and secondary dimensions was determined. The width of the seed was the primary dimension, and the other secondary dimensions (length and thickness) were calculated based on their relationships with the primary dimension. On this basis, an approach for modeling Cyperus esculentus seed particles based on the multi-sphere (MS) method was proposed. The discrete element analysis models of three varieties of Cyperus esculentus seeds were established with different numbers of filing spheres. Moreover, to obtain more accurate simulation parameters, first, a range of values of the simulation parameters was obtained by the experimental method. Second, the Plackett–Burman (PB) test and the path of steepest ascent method were both adopted to correct and calibrate the simulation parameters, which were difficult to obtain through experiments, and simulation of the direct shear test was used for calibration. All of the methods guaranteed that the selected parameters were reasonable. The test results showed that the static friction coefficient of seed–seed had a significant effect on the simulation results. Finally, piling tests and the bulk density test were used for modeling verification. By comparing the simulated results and experimental results in the piling tests and bulk density test, when the number of filing spheres increased, the simulated results were close to those obtained experimentally. Therefore, the feasibility and validity of the modeling method for Cyperus esculentus seed particles that we proposed and the simulation parameters that were obtained were verified.

Efficient Discrete Element Modeling of Particle Dampers

Particle dampers’ dissipative characteristics can be difficult to predict because of their highly non-linear behavior. The application of such devices in deformable vibrating systems can require extensive experimental and numerical analyses; therefore, improving the efficiency when simulating particle dampers would help in this regard. Two techniques often proposed to speed up the simulation, namely the adoption of a simplified frictional moment and the reduction of the contact stiffness, are considered; their effect on the simulation run-time, on the ability of the particle bed to sustain shear deformation, and on the prediction of the dissipation performance is investigated for different numerical case studies. The reduction in contact stiffness is studied in relation to the maximum overlap between particles, as well as the contacts’ duration. These numerical simulations are carried out over a wide range of motion regimes, frequencies, and amplitude levels. Experimental results are considered as well. All the simulations are performed using a GPU-based discrete element simulation tool coupled with the multi-body code MBDyn; the results and execution time are compared with those of other solvers.

Determination of mechanical properties of Zanthoxylum armatum using the discrete element method

Using the discrete element method (DEM) to investigate the behavior of particles is a crucial strategy in the research and development of novel equipment. Green pepper (Zanthoxylum armatum) is a globally renewable plant-derived medicinal and food homologous commodity with a wide range of uses and great demand, but the mechanical properties needed to develop its processing equipment are scare. Thus, this case of study aimed to systematically explore the necessary input parameters to model green pepper, and to provide new insights for the guidance of future industrial applications worldwide. On the basis of the experimental measured physical properties, the contact properties of green pepper on zinc-coated steel were fist calibrated, and then used to determine the contact properties between particles. The differences between the experimental and simulation results were analyzed for selection and verification of the contact properties accurately. Difference analysis confirmed that the coefficient of restitution, coefficient of static friction and coefficient of rolling friction for contact between the particle and zinc-coated steel have values of 0.392, 0.650, and 0.168, and those coefficients for particle-to-particle contact have values of 0.199, 0.710, and 0.184, respectively. Discoveries in this work may contribute to the research and development of production equipment for green pepper.

Modelling Method and Application of Anti-Corrosion Pill Particles in Oil and Gas Field Wellbore Casing Annulus Based on the Discrete Element Method

This study uses a self-developed anti-corrosion pill particle as the research object and develops the pill particle population modelling method in order to optimize the anti-corrosion process of oil and gas wellbore casing annuli. The shape of the pill particle is similar to a cylinder, according to the test and analysis of geometrical characteristics, and can be simplified into three types based on height, namely pill particles A (5.4 mm), B (5.8 mm), and C (6.2 mm). The multi-sphere approach is then used to create models of three different types of pill particles with varying degrees of precision. The feasibility and effectiveness of the modelling method for pill particle populations are proven by comparing the simulation results of the bulk density test and the angle of repose test. The results show that the 12-sphere models of pill particles A, B, and C are accurate representations of genuine pill particle morphologies and are adequate for simulating particle mechanics and flow processes. The applicability and practical use of the modelling method are then demonstrated using an example of a self-designed pill particle discharging mechanism. The results show that the modelling method can accurately simulate the pill discharging process and provide an accurate simulation model and theoretical basis for the optimization of the structural parameters, dimension parameters, and operating parameters of the discharging device.

Numerical Investigation of Effect of Drum Barrel on Coal-Loading Performance of Thin-Coal-Seam Shearer Machines

Thin-coal-seam shearer mining efficiency is seriously restricted by the poor loading performance of the drum. The loading of the drum to the cracked coal lumps is based on a screw-conveying mechanism, and its loading performance is influenced by many structural parameters, including drum width, helical angle, axial tilt angle, number of blades and form and diameter of the barrel. The barrel diameter directly influences the drum envelope zone’s capacity, and its influence on loading performance is not yet clear. Therefore, this work first compared the drum-loading results between experiments and numerical modeling, and the results proved that the application of the discrete element method (DEM) to the modeling drum loading process is feasible and the results are reliable. Secondly, the influence of barrel diameter on particles’ axial velocity, loading rate and web depth was studied using the ejection and pushing modes. The results showed that the particles’ axial velocity has a noticeable impact on loading rate under ejection loading conditions, and the loading rate first increases and then decreases with the increase in barrel diameter. When the diameter is less than 700 mm in drum-pushing modes, the particles’ axial velocity plays an important role on drum loading; the filling level has an obvious impact on loading performance when the barrel diameter is larger than 700 mm. The drum loading ejection rate is 25% higher than that of pushing mode, which is due to the loading rate of particles located in a web depth from 300 to 600 mm. The influence of barrel diameter on loading performance using drum ejection is more obvious than that in pushing mode. The results provide a reference for drum structural design to some extent.

A comprehensive review of the application of DEM in the investigation of batch solid mixers

Powder mixing is a vital operation in a wide range of industries, such as food, pharmaceutical, and cosmetics. Despite the common use of mixing systems in various industries, often due to the complex nature of mixing systems, the effects of operating and design parameters on the mixers’ performance and final blend are not fully known, and therefore optimal parameters are selected through experience or trial and error. Experimental and numerical techniques have been widely used to analyze mixing systems and to gain a detailed understanding of mixing processes. The limitations associated with experimental techniques, however, have made discrete element method (DEM) a valuable complementary tool to obtain comprehensive particle level information about mixing systems. In the present study, the fundamentals of solid-solid mixing, segregation, and characteristics of different types of batch solid mixers are briefly reviewed. Previously published papers related to the application of DEM in studying mixing quality and assessing the influence of operating and design parameters on the mixing performance of various batch mixing systems are summarized in detail. The challenges with regards to the DEM simulation of mixing systems, the available solutions to address those challenges and our recommendations for future simulations of solid mixing are also presented and discussed.

An Efficient Parallel Framework for the Discrete Element Method Using GPU

The discrete element method (DEM), a discontinuum-based method to simulate the interaction between neighbouring particles of granular materials, suffers from intensive computational workload caused by massive particle numbers, irregular particle shapes, and complicated interaction modes from the meso-scale representation of the macro information. To promote the efficiency of the DEM and enlarge the modelling scales with a higher realism of the particle shapes, parallel computing on the graphics processing unit (GPU) is developed in this paper. The potential data race between the computing cores in the parallelisation is tackled by establishing the contact pair list with a hybrid technique. All the computations in the DEM are made on the GPU cores. Three benchmark cases, a triaxial test of a sand specimen, cone penetration test and granular flow due to a dam break, are used to evaluate the performance of the GPU parallel strategy. Acceleration of the GPU parallel simulations over the conventional CPU sequential counterparts is quantified in terms of speedup. The average speedups with the GPU parallelisation are 84, 73, and 60 for the benchmark cases.

A Multi-Objective Identification of DEM Microparameters for Brittle Materials

The discrete element method (DEM) [...]

A “Sequential Design of Simulations” approach for exploiting and calibrating discrete element simulations of cohesive powders

The flow behaviours of cohesive particles in the ring shear test were simulated and examined using discrete element method guided by a design of experiments methodology. A full factorial design was used as a screening design to reveal the effects of material properties of partcles. An augmented design extending the screening design to a response surface design was constructed to establish the relations between macroscopic shear stresses and particle properties. It is found that the powder flow in the shear cell can be classified into four regimes. Shear stress is found to be sensitive to particle friction coefficient, surface energy and Young’s modulus. A considerable fluctuation of shear stress is observed in high friction and low cohesion regime. In high cohesion regime, Young’s modulus appears to have a more significant effect on the shear stress at the point of incipient flow than the shear stress during the pre-shear process. The predictions from response surface designs were validated and compared with shear stresses measured from the Schulze ring shear test. It is found that simulations and experiments showed excellent agreement under a variety of consolidation conditions, which verifies the advantages and feasibility of using the proposed “Sequential Design of Simulations” approach.

Pin-on-Disc Modelling with Mesh Deformation Using Discrete Element Method

The pin-on-disc test is a standard sliding wear test used to analyse sliding properties, including wear contour and wear volume. In this study, long-term laboratory test performance is compared with a short-term numerical model. A discrete element method (DEM) approach combined with an Archard wear model and a deformable geometry technique is used. The effect of mesh size on wear results is evaluated, and a scaling factor is defined to relate the number of revolutions between the experiment and the numerical model. The simulation results indicate that the mesh size of the disc has a significant effect on the wear contour. The wear depth and wear width follow a normal distribution after experiencing a run-in phase, while the wear volume has a quadratic relation with the number of revolutions. For the studied material combination, the calibration of the wear coefficient shows that the wear volume of the pin-on-disc test accurately matches the simulation results for a minimum of eight revolutions with a wear coefficient lower than 2 × 10^-11 Pa^-1.

Direct Compaction Drug Product Process Modeling

Most challenges during the development of solid dosage forms are related to the impact of any variations in raw material properties, batch size, or equipment scales on the product quality and the control of the manufacturing process. With the ever pertinent restrictions on time and resource availability versus heightened expectations to develop, optimize, and troubleshoot manufacturing processes, targeted and robust science-based process modeling platforms are essential. This review focuses on the modeling of unit operations and practices involved in batch manufacturing of solid dosage forms by direct compaction. An effort is made to highlight the key advances in the past five years, and to propose potentially beneficial future study directions.

DEM modelling of railway ballast using the Conical Damage Model: a comprehensive parametrisation strategy

Despite ongoing research, the parametrisation of a DEM model is a challenging task, as it depends strongly on the particle shape representation used, particle-particle contact law and the simulated applications: for railway ballast e.g. lab tests or track conditions. The authors previously modelled railway ballast with a DEM model using a simple particle shape. The DEM model was parametrised, by trial-and-error, to compression and direct shear test results. A good agreement between DEM model and experimental results was achieved only when the Conical Damage Model (CDM) was used as the contact law. Compared to the well-known linear-spring Cundall-Strack law or the Hertz-Mindlin law, this contact law takes into account additional physical effects (e.g. edge breakage) occurring in the experiment. Little is known on the influence of the CDM model parameters on the simulation results or on possible parameter ambiguities. This lack of knowledge hinders a reliable and efficient parametrisation of DEM models using different particle shapes. Both points are addressed in this work in detail by investigating a DEM model for railway ballast using one simple particle shape. Suggestions for a parametrisation strategy of reduced computational effort are formulated and tested using a second particle shape. In future works, the newly presented parametrisation strategy can help to calibrate different DEM models and to study the influence of particle shape.

Shaping the Design Features of a Dynamometer for Measuring Resistance Biaxial Components of Symmetrical Coulters

The article lays out the methodology for shaping the design features of a strain gauge transducer, which would make it possible to study forces and torques generated during the operation of symmetrical seeder coulters. The transducers that have been known up until now cannot be used to determine forces and torques for the coulter configuration adopted by the authors. For this purpose, the design of the transducer in the form of strain gauge beams was used to ensure the accumulated stress concentration. A detailed design was presented in the form of a 3D model, along with a transducer body manufactured on its basis, including the method for arranging the strain gauges thereon. Moreover, the article discusses the methodology of processing voltage signals obtained from component loads. Particular attention was paid to the methodology of determining the load capacity of the transducer structure, based on finite element method (FEM). This made it possible to choose a transducer geometry providing the expected measurement sensitivity and, at the same time, maintaining the best linearity of indications, insignificant coupling error, and a broad measurement range. The article also presents the characteristics of the transducer calibration process and a description of a special test stand designed for this purpose. The transducer developed within the scope of this work provides very high precision of load spectrum reads, thus enabling the performance of a detailed fatigue analysis of the tested designs. Additionally, the versatility it offers makes it easy to adapt to many existing test stands, which is a significant advantage because it eliminates the need to build new test stands.

Modeling of High-Density Compaction of Pharmaceutical Tablets Using Multi-Contact Discrete Element Method

The purpose of this work is to simulate the powder compaction of pharmaceutical materials at the microscopic scale in order to better understand the interplay of mechanical forces between particles, and to predict their compression profiles by controlling the microstructure. For this task, the new framework of multi-contact discrete element method (MC-DEM) was applied. In contrast to the conventional discrete element method (DEM), MC-DEM interactions between multiple contacts on the same particle are now explicitly taken into account. A new adhesive elastic-plastic multi-contact model invoking neighboring contact interaction was introduced and implemented. The uniaxial compaction of two microcrystalline cellulose grades (Avicel^® PH 200 (FMC BioPolymer, Philadelphia, PA, USA) and Pharmacel^® 102 (DFE Pharma, Nörten-Hardenberg, Germany) subjected to high confining conditions was studied. The objectives of these simulations were: (1) to investigate the micromechanical behavior; (2) to predict the macroscopic behavior; and (3) to develop a methodology for the calibration of the model parameters needed for the MC-DEM simulations. A two-stage calibration strategy was followed: first, the model parameters were directly measured at the micro-scale (particle level) and second, a meso-scale calibration was established between MC-DEM parameters and compression profiles of the pharmaceutical powders. The new MC-DEM framework could capture the main compressibility characteristics of pharmaceutical materials and could successfully provide predictions on compression profiles at high relative densities.

A Novel Computational Approach Coupled with Machine Learning to Predict the Extent of Agglomeration in Particulate Processes

Solid particle agglomeration is a prevalent phenomenon in various processes across the chemical, food, and pharmaceutical industries. In pharmaceutical manufacturing, agglomeration is both desired in unit operations like wet granulation and undesired in unit operations such as agitated filter drying of highly potent active pharmaceutical ingredients (API). Agglomeration needs to be controlled for optimal physical properties of the API powder. Even after decades of work in the field, there is still very limited understanding of how to quantify, predict, and control the extent of agglomeration, owing to the complex interaction between the solvent and the solid particles and stochasticity imparted by mixing. Furthermore, a large size of industrial scale particulate process systems makes it computationally intractable. To overcome these challenges, we present a novel theory and computational methodology to predict the agglomeration extent by coupling the experimental measurements of agglomeration risk zone or "sticky zone" with discrete element method. The proposed model shows good agreement with experiments. Further, a machine learning model was built to predict agglomeration extent as a function of input variables, such as material properties and processing conditions, in order to build a digital twin of the unit operation. While the focus of the present study is the agglomeration of particles during industrial drying processes, the proposed methodology can be readily applied to numerous other particulate processes where agglomeration is either desired or undesired.

Calibration of the Discrete Element Method Parameters in Living Juvenile Manila Clam (Ruditapes philippinarum) and Seeding Verification

The Manila Clam is an important economic shellfish in China’s seafood industry. In order to improve the design of juvenile Manila Clam seeding equipment, a juvenile clam discrete element method (DEM) particle shape was established, which is based on 3D scanning and EDEM software. The DEM contact parameters of clam-stainless steel, and clam-acrylic were calibrated by combining direct measurements and test simulations (slope sliding and dropping). Then, clam DEM simulation and realistic seeding tests were carried out on a seeding wheel at different rotational speeds. The accuracy of the calibrated clam DEM model was evaluated in a clam seeding verification test by comparing the average error of the variation coefficient between the realistic and simulated seeding tests. The results showed that: (a) the static friction coefficients of clam-acrylic and clam-stainless steel were 0.31 and 0.23, respectively; (b) the restitution coefficients of clam-clam, clam-acrylic, and clam-stainless steel were 0.32, 0.48, and 0.32, respectively. Furthermore, the results of the static repose angle from response surface tests showed that when the contact wall was acrylic, the coefficient rolling friction and static friction of clam-clam were 0.17 and 1.12, respectively, and the coefficient rolling friction of clam-acrylic was 0.20. When the contact wall was formed of stainless steel, the coefficient rolling friction and static friction of clam-clam were 0.33 and 1.25, respectively, and the coefficient rolling friction of clam-stainless steel was 0.20. The results of the verification test showed that the average error between the realistic and simulated value was <5.00%. Following up from these results, the clam DEM model was applied in a clam seeding simulation.

Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture

The numerical model of the granular flow within an aggregate mixture, conducted in the vertical static and/or the conveyor blender, was explored using the discrete element method (DEM) approach. The blending quality of limestone fine aggregate fractions binary mixture for application in self-compacting concrete was studied. The potential of augmenting the conveyor mixer working efficiency by joining its operation to a Komax-type vertical static mixer, to increase the blending conduct was investigated. In addition the impact of the feed height on the flow field in the cone-shaped conveyor mixer was examined using the DEM simulation. Applying the numerical approach enabled a deeper insight into the quality of blending actions, while the relative standard deviation criteria ranked the uniformity of the mixture. The primary objective of this investigation was to examine the behavior of mixture for two types of blenders and to estimate the combined blending action of these two mixers, to explore the potential to augment the homogeneity of the aggregate fractions binary mixture, i.e., mixing quality, reduce the blending time and to abbreviate the energy-consuming.