13 research outputs found
Segregation and mixing of granular material in industrial processes
Within the EU-funded PARDEM network mixing and segregation are studied in silos and heaps, agitated mixers and fluidized beds. A method is presented with which mixing and segregation can be characterized, adapted for quasi-static to dynamic systems and applied at the global system level as well as at the local level. This paper attempts to give an overview of the applicability of this analysis by providing three instances, being chute flow representing flow down a heap, agitated mixing and fluidization, in which the method is applied
On the modelling of complex systems: methodologies and applications
This paper provides an overview of some of the techniques and methodologies utilized in the modelling of complex systems that involve many interacting components with different physical properties over different spatial and temporal scales. Such systems are difficult to resolve, since they exhibit high levels of uncertainty. We discuss modelling strategies and present some applications from the field of complex system modelling
A Hybrid Approach for the Modelling of Complex Systems: Methodologies and Applications
In this paper the hybrid approach is presented for the modelling of complex systems that involve many interacting components with different physical properties over different spatial and temporal scales. Such systems are difficult to resolve, since they exhibit high levels of uncertainty. We briefly discuss other modelling strategies and their advantages and disadvantages and then a complete description of the mathematical-computational hybrid framework is given. Then, an application from the field of particulate-based engineering processes is presented and the ability of the framework is demonstrated to accurately represent key granular material processes with the aid of information extracted from different scales
Constructing an engineering model for moisture migration in bulk solids as a prelude to predicting moisture migration caking
The aim of this study was to examine one of the mechanisms behind moisture migration caking, where liquid solution bridges form between particles in a bulk solid system because of an increase in local relative humidity, and then solidify as the local relative humidity drops - the effect being increased as more cycles occur. The goal was to develop a one-dimensional model for the heat and mass transfer processes involved, based on established physics and the characteristic moisture sorption curve of the solid (in this case sugar). The model was verified using scaled-down equipment (a caking box) to simulate the caking in a big bag. The results of this study will assist in the prediction of caking produced in this way
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Micro-mechanical parameterisations for continuum modelling of granular material using the discrete element method
The present work uses the discrete element method (DEM) to describe assemblies of particulate bulk materials. Working numerical descriptions of entire processes using this scheme are infeasible because of the very large number of elements (1012 or more in a moderately sized industrial silo). However it is possible to capture much of the essential bulk mechanics through selective DEM on important regions of an assembly, thereafter using the information in continuum numerical descriptions of particulate processes. The continuum numerical model uses population balances of the various components in bulk solid mixtures. It depends on constitutive relationships for the internal transfer, creation and/or destruction of components within the mixture. In this paper we show the means of generating such relationships for two important flow phenomena – segregation whereby particles differing in some important property (often size) separate into discrete phases, and degradation, whereby particles break into sub-elements, through impact on each other or shearing. We perform DEM simulations under a range of representative conditions, extracting the important parameters for the relevant transfer, creation and/or destruction of particles in certain classes within the assembly over time. Continuum predictions of segregation and degradation using this scheme are currently being successfully validated against bulk experimental data and are beginning to be used in schemes to improve the design and operation of bulk solids process plant
Sampling Issues in Assessing Particle Degradation in Pneumatic Conveying Systems
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Mathematical modelling of the behaviour of granular material in a computational fluid dynamics framework using micro-mechanical models
In this paper, a Computational Fluid Dynamics framework is presented for the modelling of key processes which involve granular material (i.e. segregation, degradation, caking). Appropriate physical models and sophisticated algorithms have been developed for the correct representation of the different material components in a granular mixture. The various processes, which arise from the micromechanical properties of the different mixture species can be obtained and parametrised in a DEM / experimental framework, thus enabling the continuum theory to correctly account for the micromechanical properties of a granular system. The present study establishes the link between the micromechanics and continuum theory and demonstrates the model capabilities in simulations of processes which are of great importance to the process engineering industry and involve granular materials in complex geometries
A hybrid numerical model for predicting segregation during core flow discharge
A continuum numerical model is presented that parameterizes the interactions between particles at the microscopic level and predicts the development of moving stagnant zone boundaries during core flow discharge of granular material. The model is then employed for the prediction of segregation of multi-component granular mixtures during discharge from core flow hoppers and its capability to accurately simulate the behavior of the granular mixture is demonstrated through comparisons with experimental data