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The purpose of this study is to explore how particle shape influences the screening, including screening efficiency per unit time, and the relationship between vibration parameters and screening efficiency per unit time in discrete element method (DEM) numerical simulations.

In this paper, a three-dimensional discrete element model of vibrating screen with composite vibration form of swing and translation was proposed to simulate the screening process. In total, 11 kinds of non-spherical particles whose shapes changed in a continuous regularity gradual process were established using a multi-sphere method. In the DEM simulations, vibration parameters, including vibration frequency, vibration amplitude and stroke angle, and swing parameters, including swing frequency and swing angle, were changed to perform parametric studies.

It shows that the effect of particle shape on screening efficiency is quantitative actually. However, the trends of different shape particles’ screening efficiency per unit time are mainly consistent.

Some simple particle shapes can be expected to be explored to do screening simulation studies reasonably with modification of the simulation data in DEM numerical simulations. That may improve the computational efficiency of numerical simulations and provide guidance to the study of the screening process.

The purpose of this paper is to fundamentally develop a mathematical model for predicting the particle size distribution (PSD) in fluidized beds because their hydrodynamics depend on the PSD and its evolution during operation. To predict the gradual PSD change in a fluidized bed by using the population balance method (PBM), the kinetic parameter for agglomerate formation should be known and this parameter, in this work, is determined by the results of computational fluid dynamic–discrete element method (CFD-DEM) simulation.

Momentum and energy conservation equations and soft-sphere DEM are used to simulate the agglomeration phenomenon at high temperature in a two-dimensional air-polyethylene fluidized bed in bubbling regime. The Navier–Stokes equations for motion of gas are solved by the SIMPLE algorithm. Newton’s second law of motion is applied to describe the motion of individual particles. Collision between particles is detected by the no-binary search algorithm.

A correlation is proposed for estimating the kinetic parameter for agglomerate formation based on collision frequency, collision efficiency and inlet gas temperature. Based on the corrected kinetic parameter, the PBM is able to predict the PSD evolution in the fluidized bed in a fairly good agreement with the results of the CFD-DEM.

The results of the agglomeration process cannot be compared quantitatively with experimental results. Because three-dimensional fluidized bed mostly contains millions of particles and simulating them takes a long computing time in DEM. As far as temperature is a dominant parameter in the agglomeration process, effects of inlet gas temperature are examined on the kinetic parameter. On the other hand, wider and deeper insights in which the effect of other parameters, such as velocity and so on will be studied, is one of the goals in the authors’ next works to compensate for the shortcomings in this work.

This study helps to understand the effect of the inlet gas temperature during the agglomeration process on the kinetic parameter and provides fundamental information in dealing with kinetic parameter to attain PSD in fluidized bed by the PBM.

Application of the discrete element method (DEM) to real scale engineering problems involving three‐dimensional modelling of large, non‐spherical particles must consider the inertia tensor and temporal change in the orientation of the particles when calculating the rotational motion. This factor has commonly been neglected in discrete element modelling although it will significantly influence the dynamic behaviour of non‐spherical particles. In this paper two methods, vector transformation and tensor transformation, for calculation of the rotational motion of particles in response to applied moments are presented. The methods consider the inertia tensor and the local object frame of arbitrary shaped particles and suggest solutions for the non‐linear Euler equations for calculation of their rotational motion. They are discussed with respect to implementation into a discrete element code and assessed in terms of their accuracy and computational efficiency.

The purpose of this paper is to examine several calibration techniques that have been developed to determine the discrete element method (DEM) parameters for slow and rapid unconfined flow of granular conical pile formation. This paper also aims to discuss some of the methods currently employed to scale particle properties to reduce computational resources and time to solve large DEM models.

DEM models have been calibrated against simple bench‐scale experimental results to examine the validity of selected parameters for the contact, material and mechanical models to simulate the dynamic and static behaviour of cohesionless polyethylene pellets. Methods to determine quantifiable single particle parameters such as static friction and the coefficient of restitution have been highlighted. Numerical and experimental granular pile formation has been investigated using different slumping and pouring techniques to examine the dependency of the type of flow mechanism on the DEM parameters.

The proposed methods can provide cost effective and simple techniques to determine suitable input parameters for DEM models. Rolling friction and particle shape representation has shown to have a significant influence on the bulk flow characteristics via a sensitivity analysis and needs to be accessed based on the environmental conditions.

This paper describes several effective known and novel methodologies to characterise granular materials that are needed to accurately model granular flow using the DEM to provide valuable quantitative data. For the DEM to be a viable predictive tool in industrial applications which often contain huge quantities of particles with random particle shapes and irregular properties, quick and validated techniques to “tune” DEM models are necessary.

The purpose of this paper is to present an image based method for estimating the 3D motion of rigid particles from high‐speed video footage (HSV). The computed motion can be used as either a means to generate quantitative feedback for a process or to validate the accuracy of discrete element method (DEM) simulation models.

Experiments consist of a diamond impacting an angled plate and video is captured at 4,000 frames per second. Simple image analysis is used to track the particle in each frame and to extract its 2D silhouette boundary. Using an approximate 3D model of the particle generated from a multi‐camera setup, a pose estimation scheme based on silhouette consistency is used in conjunction with a rigid body model to compute the 3D motion.

Under reasonable conditions, the method can reliably estimate the linear and angular motion of the particle to within 1 per cent of their true values.

As an example application, we demonstrate how the method can be used to validate DEM simulations of simple impact experiments captured with HSV, providing valuable insight towards further development. In particular, we investigate the effects of shape representation through sphere‐clumping and the applicability of different contact models.

The novelty of our method is its ability to accurately compute the motion associated with a real world interaction, such as an impact, which provides numerical ground truth at an individual particle level. While similar schemes have been attempted with ideal particles (e.g. spheres), the resulting models do not naturally extend to realistic particle shapes. Since our method can track real particles, real‐world processes can be better quantified.

The purpose of this paper is to obtain the combination of working parameters suitable for pulsating negative pressure shale shaker through simulation, which is conducive to efficient recovery of clean drilling fluid and relatively dry cuttings.

Shale shaker is still one of the main equipment in solid–solid and solid–liquid separation processes in drilling industry. This research is based on a new drilling fluids circulation treatment device, namely pulsating negative pressure shale shaker. In this work, a numerical study of particle flow and separation in the pulsating negative pressure shale shaker is carried out by coupling computational fluid dynamics/discrete element method (CFD-DEM). The effect of vibration parameters and negative pressure parameters are studied in terms of conveyance velocity and percent through screen.

The results show that, conveyance velocity of particle is mainly affected by vibration parameters, negative pressure in pulsating form can effectively prevent cuttings from sticking to the screen. Vibration parameters and pulsating airflow velocity peak have great influence on percent through screen, while vibration frequency and screen slope have influence on the time when the percent through screen reaches stability.

In this paper, the authors put forward a new kind of drilling waste fluid treatment equipment, and focused on the study of particle movement law. The results have important guiding significance for the selection of structural design parameters and rational use of equipment. In addition, the new device provides a new idea for solid–liquid separation method, which is one of the hot topics in current research.

Since surface runoff clogs stormwater grates, leading to deterioration of drainage capacity, and also it is difficult to complete the study with actual dimensions in experiments, a numerical simulation work was established in this study to investigate the surface runoff clogging stormwater grate patterns. The purpose of this study is to describe the mechanisms of storm grate clogging and storm well deposition for different flow rate floods and granular materials.

In the work of this study, the volume of fluid (VOF) method and the discrete element method (DEM) are used to solve the gas–liquid and particle flows. In order to solve the evolution of the gas–liquid interface during surface runoff, the VOF was used. To simulate the rain grate and set up different material particles to represent the surface floating materials, the DEM was utilized.

The research results show that the clogging distribution and clogging rate of the rainwater grate are closely related to the fluid flow velocity and the physical characteristics of the particles, and the higher the clogging rate of the rainwater grate and the higher the number of particles deposited in the rainwater well at the same surface runoff velocity, the higher the density of the clogged particles. The surface runoff velocity (0.5 m/s, 1 m/s) shows that the rapid change of particle movement state at high runoff velocity makes the particle clogging more obvious.

A multi-scale CFD-DEM approach was used to simulate the particulate motion of the road surface with different incoming runoff velocities. The innovative use of DEM to model the storm grate simulation ensures the accuracy of the traction model.

Orientation determination is an essential planning task in additive manufacturing (AM) because it directly affects the part quality, build time, geometric tolerance, fabrication cost, etc. This paper aims to propose a negative feedback decision-making (NFDM) model to realize the personalized design of part orientation in AM process.

NFDM model is constructed by integrating two sub-models: proportional–integral–derivative (PID) negative feedback control model and technique for order preference by similarity to an ideal solution (TOPSIS) decision-making model. With NFDM model, a desired target is first specified by the user. Then, the TOPSIS decision model calculates the “score” for the current part orientation. TOPSIS decision model is modified for ease of control. Finally, the PID controller automatically rotates the part based on the error between the user-specified target and the calculated “score”. Part orientation adjustment is completed when the error is eliminated. Five factors are considered in NFDM model, namely, surface roughness, support structure volume, geometric tolerance, build time and fabrication cost.

The case studies of turbine fan and dragon head indicate that the TOPSIS model can be perfectly integrated with the PID controller. This work extends the proposed model to different AM processes and investigates the feasibility of combining different decision-making models with PID controller and the effects of including various evaluation criteria in the integrated model.

The proposed model innovatively takes the TOPSIS decision-making model and the PID control model as a whole. In this way, the uncontrollable TOPSIS model becomes controllable, so the proposed model can control the TOPSIS model to achieve the user-specified targets.

The granular structure of a grinding wheel determines its performance remarkably when grinding. Nowadays, grinding wheels are man-made porous conglomerates of hard abrasive grains bonded with a binder. As an engineered material, it would be interesting to foresee the behaviour of the wheel, but it is hindered under its complex heterogeneous nature. Recently, some models based on the discrete element method (DEM) have been presented to model the grinding wheel. This paper aims to identify and propose a framework that must comply with such models and to identify new applications for DEM models in grinding.

First, the characteristics of the grinding wheel are described. In this way, the framework of DEM models of a grinding wheel material is developed, reproducing both the granular morphology and stiffness.

The paper asserts a promising future that provides the DEM in the modelling of grinding.

The potential of DEM in grinding is analysed, proposing new applications. It can be used as topography model, which can also model the stiffness. In addition, DEM opens a new interesting research line: the modelling of the grit breakout. It draws up the development of essential dressing and wear models.

The purpose of this paper is to explore US students’ experience in for-credit, unpaid internships overseas with particular reference to their personal development, how they mobilised their knowledge across contexts, their learning as acquisition and as participation, and what they contributed. Students were thought likely to encounter three forms of cultural differences: national, workplace and academic.

In total, 17 students in communication, marketing or related fields from the USA were placed in four-week internships in Wellington, New Zealand. Outcomes for them were assessed first, via weekly discussions in which they described what they had encountered that week, second, via the presentations they gave at the end of the course to internship hosts and university staff on the subject of what they had found challenging and what they had learned and contributed, and third, through assessment of students’ formal written assignments to discover what they said they had learned and what they had contributed.

Students were surprised at how proactive their internship hosts expected them to be and at how little overt direction they received. While they valued their opportunity to make a contribution to their workplace, they found this challenging. Students gave instances of their learning both as individuals and in groups. No mention was made of academic cultural differences being an issue, but they often described the demanding nature of the national and workplace cultural differences that they encountered.

The study reports on only one cohort of students in one year, so a longitudinal study of further cohorts might provide different findings.

Insights are provided into how students saw themselves as changing from their involvement. Students described the challenges they faced, how they reacted to those challenges and their most important forms of learning.