Validation of movement over a belt conveyor drum

This paper presents the use of new modern methods for the research of movement of material on a belt conveyor. One of the innovative methods is Particle Image Velocimetry (PIV), which was used to scan and assess the two-dimensional vector field of speed of particles on the belt conveyor. Outputs from PIV were compared to simulations of the same transport process. These simulations were performed using the Discrete Element Method (DEM). Four transport speeds of material were assessed for a real and simulative belt conveyor model. Software tracking of particle movement was used to determine and compare the trajectories of paths of particles leaving the belt conveyor drum. Validation of the DEM simulation of material movement over a belt conveyor drum using PIV provided acceptable results in the area of particle speed fields. Comparison of the particle path trajectory corresponds to the preliminary hypothesis which leads to calibration of the DEM simulation. The results and assessment of this paper were created based on validation.Web of Science11212411

Analysing performance of first year engineering students

Many students in the engineering disciplines do not complete their higher education degree and drop out. This problem is serious, especially for first-year university students. In this paper, we analyse how students earn the credits required for their successful completion of the first study year. Using the example of a European technical university with traditional classroom-based education, we identify three groups of students: those who pass, those who earn only enough credits for staying in the program, and those who fail. Important patterns can be found at the end of the first semester. We present a simple algorithm that identifies students who may benefit from early additional support, which would increase their chances of progression to the second year and improve the retention improvement for the university. The results are evaluated in four consecutive academic years. The data from years 2013/14 and 2014/15 have been used to develop and verify the prediction model. In study years 2015/16 and 2016/17 the model has been applied to predict at-risk students, where the university tutors intervened and provided additional support and a significant improvement was achieved

DEM investigation of the influence of particulate properties and operating conditions on the mixing process in rotary drums: Part 2-Process validation and experimental study

The process of homogenization of particulates is an indispensable part of many industrial processes, and, therefore, it is necessary to pay a special attention to this area and develop it. This paper deals with a complex study of homogenization of particulate matters in a rotary drum in terms of shape, size, and density of particles. In addition, the influence of operating parameters, such as drum filling capacity, rotational speed, and drum filling pattern are also investigated. Studies of reproducibility of discrete element method simulations, effects of rotary drum sizes or effects of drum volumetric filling to the mixture homogeneity index were also carried out. In general, the least satisfactory values of the homogeneity index resulted from the mixing of particles with different densities. The dominating factor of homogenization was the drum filling-up degree. The course of the homogeneity index in 140, 280, and 420 mm drums was very similar and after five revolutions of the drum, identical values of the homogeneity index were achieved for all the drum diameters. The optimal drum filling-up degree is at 40-50% for the spherical particles and 30-40% for the sharp-edged particles. The repeatability of simulations showed the maximum relative standard deviation of the homogeneity index at 0.6% from ten simulation repetitions with the same parametric conditions.Web of Science82art. no. 18

Analysis and optimization of material flow inside the system of rotary coolers and intake pipeline via discrete element method modelling

There is hardly any industry that does not use transport, storage, and processing of particulate solids in its production process. In the past, all device designs were based on empirical relationships or the designer's experience. In the field of particulate solids, however, the discrete element method (DEM) has been increasingly used in recent years. This study shows how this simulation tool can be used in practice. More specifically, in dealing with operating problems with a rotary cooler which ensures the transport and cooling of the hot fly ash generated by combustion in fluidized bed boilers. For the given operating conditions, an analysis of the current cooling design was carried out, consisting of a non-standard intake pipeline, which divides and supplies the material to two rotary coolers. The study revealed shortcomings in both the pipeline design and the cooler design. The material was unevenly dispensed between the two coolers, which combined with the limited transport capacity of the coolers, led to overflowing and congestion of the whole system. Therefore, after visualization of the material flow and export of the necessary data using DEM design measures to mitigate these unwanted phenomena were carried out.Web of Science117art. no. 184

DEM investigation of the influence of particulate properties and operating conditions on the mixing process in rotary drums: Part 1-Determination of the DEM parameters and calibration process

This paper's goal was to select methods and a calibration procedure which would lead to the determination of relevant parameters of a discrete element method (DEM) and virtual material creation. Seven particulates were selected with respect to their shape (spherical and non-spherical), size and density. The first calibration experiment involved "packing test" to determine the shape accuracy and bulk density of virtual packed particulates. The series of simulations were compared with real experiments, and the size, shape and density of virtual particles were optimized. Using three apparatuses, the input parameter values were experimentally determined for a contact model that defines the behavior of particulates in DEM simulations. The research part of the paper examines the influence of factors such as particle number; pile formation method; and the method of evaluation of the angle of repose on the process of the calibration of virtual material. The most reproducible results were achieved by the "pilling" method and by the rotating drum-both evaluated by the geometric method. However, it is always advisable to make an overall visual comparison of the slope shape between the calibration simulation and the experimental curves. The bowl's diameter to particle size ratio should be greater than 25, and the calibration experiment should contain approximately 4000 particles to ensure representative results during angle of repose calibration experiment.Web of Science82art. no. 22

Simulation of material flow through a sample divider

The prerequisite for a modem approach to innovative procedures of the development of current or even newly created equipment for the transport of particulate materials is the utilization of simulation methods, such as the Discrete Element Method (DEM). This article focuses on the basic, or initial, validation of movement of material through the sample divider. The mechanical-physical properties of brown coal were measured. Based on these parameters the preliminary input values for EDEM Academic were selected, and a simulation of the dividing process was run. The key monitored parameters included density and friction coefficient. Experiments on a realistic model of the equipment were performed and assessed. The total weights of brown coal at the exit from the divider were determined for a specific speed of the divider. The aim of this task was to simulate the realistically determined weight division of the brown coal sample. The result from the DEM was compared with the results of measurement on a realistic model.Web of Science12119919

Investigating Influence of Demographic Factors on Study Recommenders

Recommender systems in e-learning platforms, can utilise various data about learners in order to provide them with the next best material to study. We build on our previous work, which defines the recommendations in terms of two measures (i.e. relevance and effort) calculated from data of successful students in the previous runs of the courses. In this paper we investigate the impact of students’ socio-demographic factors and analyse how these factors improved the recommendation. It has been shown that education and age were found to have a significant impact on engagement with materials

Evaluating Weekly Predictions of At-Risk Students at The Open University: Results and Issues

Improving student retention rates is a critical task not only for traditional universities but particularly in distance learning courses, which are in recent years rapidly gaining in popularity. Early indications of potential student failure enable the tutor to provide the student with appropriate assistance, which might improve the student’s chances of passing the course. Collated results for a course cohort can also assist course teams to identify problem areas in the educational materials and make improvements for future course presentations. Recent work at the Open University (OU) has focused on improving student retention by predicting which students are at risk of failing. In this paper we present the models implemented at the OU, evaluate these models on a selected course and discuss the issues of creating the predictive models based on historical data, particularly mapping the content of the current presentation to the previous one. These models were initially tested on two courses and later extended to ten courses

Developing predictive models for early detection of at-risk students on distance learning modules

Not all students who fail or drop out would have done so if they had been offered help at the right time. This is particularly true on distance learning modules where there is no direct tutor/student contact, but where it has been shown that making contact at the right time can improve a student’s chances. This paper explores the latest work conducted at the Open University, one of Europe’s largest distance learning institutions, to identify when is the optimum time to make student interventions and to develop models to identify the at-risk students in this time frame. This work in progress is taking real time data and feeding it back to module teams as the module is running. Module teams will be indicating which of the predicted at-risk students have received an intervention, and the nature of the intervention

Study of the relationships between multi-hole, multi-disc mill performance parameters and comminution indicators

The knowledge of a grinder structure, its performance parameters and characteristics of biomaterials breakage are crucial for this research whose aim is to determine the dependencies between performance parameters and comminution indicators. The aim of this study is to investigate the relationships between multi-disc mill performance parameters such as discs angular speed, batch dosing speed and comminution characteristics: power consumption, specific energy consumption, throughput and size reduction ratio. To achieve these goals, an experiment was conducted on a five-disc mill with a special monitoring system. The research program was established, with disc angular speed at different configurations and different batch dosing speeds. The results show that power consumption, specific energy consumption and size reduction ratio depend on the total increase in angular speed of discs S Delta omega in such a way that an increase in S Delta omega causes an increase in the abovementioned comminution indicators. In turn, an increase in batch dosing speed W causes an increase in throughput. The fitting curves of comminution indicators in dependence of selected performance parameters are also presented in this study.Web of Science1315art. no. 826