Milling is a common unit operation in industry for the purpose of intentional size reduction. Considerable amount of energy is consumed during a grinding process and much of the energy is dissipated as heat and sound, which often makes grinding into an energy-intensive and highly inefficient operation. Despite many attempts to interpret particle breakage during a milling process, the grindability of a material in a milling operation remains aloof and the mechanisms of particle breakage are still poorly understood. Hence the optimisation and refinement in the design and operation of milling are in great need of an improved scientific understanding of the complex failure mechanisms. This thesis aims to provide an in-depth understanding of particle breakage associated with stressing events that occur during milling. A hybrid of experimental, theoretical and numerical methods has been adopted to elucidate the particle breakage mechanics. This study covers from single particle damage at micro-scale to bulk comminution during the whole milling process. The mechanical properties of two selected materials, i.e. alumina and zeolite were measured by indentation techniques. The breakage test of zeolite granules subjected to impact loading was carried out and it was found that tangential component velocity plays an increasingly important role in particle breakage with increasing impact velocity. Besides, single particle breakage via in-situ loading was conducted under X-ray microcomputed tomography (μCT) to study the microstructure of selected particles, visualize the progressive failure process and evaluate the progressive failure using the technique of digital image correlation (DIC). A new particle breakage model was proposed deploying a mechanical approach assuming that the subsurface lateral crack accounts for chipping mechanism. Considering the limitation of existing models in predicting breakage under oblique impact and the significance of tangential component velocity identified from experiment, the effect of impact angle is considered in the developed breakage model, which enables the contribution of the normal and tangential velocity component to be rationalized. The assessment of breakage models including chipping and fragmentation under oblique impact suggests that the equivalent normal velocity proposed in the new model is able to give close prediction with experimental results sourced from the public literature. Milling experiments were performed using the UPZ100 impact pin mill (courtesy by Hosokawa Micron Ltd. UK) to measure the comminution characteristics of the test solids. Several parameters were used to evaluate the milling performance including product size distribution, relative size span, grinding energy and size reduction ratio etc. The collective data from impact pin mill provides the basis for the validation of numerical simulation results. The Discrete Element Method (DEM) is first used to model single particle breakage subject to normal impact loading using a bonded contact model. A validation of the bonded contact model was conducted where the disparity with the experimental results is discussed. A parametric study of the most significant parameters e.g. bond Young’s modulus, the mean tensile bond strength, the coefficient of variation of the strength and particle & particle restitution coefficient in the DEM contact model was carried out to gain a further understanding of the effect of input parameters on the single particle breakage behavior. The upscaling from laboratory scale (single particle impact test) to industrial process scale (impact pin mill) is achieved using Population Balance Modelling (PBM). Two important functions in PBM, the selection function and breakage function are discussed based on the single particle impact from both experimental and numerical methods. An example of predicting product size reduction via PBM was given and compared to the milling results from impact pin mill. Finally, the DEM simulation of particle dynamics with emphasis on the impact energy distribution was presented and discussed, which sheds further insights into the coupling of PBM and DEM.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:738946 |
| Date | January 2017 |
| Creators | Wang, Li Ge |
| Contributors | Ooi, Jin ; Sun, Jin ; Butler, Ian |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/28950 |
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