17 resultados para Particle number distribution


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Modelling and optimization of the power draw of large SAG/AG mills is important due to the large power draw which modern mills require (5-10 MW). The cost of grinding is the single biggest cost within the entire process of mineral extraction. Traditionally, modelling of the mill power draw has been done using empirical models. Although these models are reliable, they cannot model mills and operating conditions which are not within the model database boundaries. Also, due to its static nature, the impact of the changing conditions within the mill on the power draw cannot be determined using such models. Despite advances in computing power, discrete element method (DEM) modelling of large mills with many thousands of particles could be a time consuming task. The speed of computation is determined principally by two parameters: number of particles involved and material properties. The computational time step is determined by the size of the smallest particle present in the model and material properties (stiffness). In the case of small particles, the computational time step will be short, whilst in the case of large particles; the computation time step will be larger. Hence, from the point of view of time required for modelling (which usually corresponds to time required for 3-4 mill revolutions), it will be advantageous that the smallest particles in the model are not unnecessarily too small. The objective of this work is to compare the net power draw of the mill whose charge is characterised by different size distributions, while preserving the constant mass of the charge and mill speed. (C) 2004 Elsevier Ltd. All rights reserved.

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Australian lungfish Neoceratodus forsteri may be the closest living relative to the first tetrapods and yet little is known about their retinal ganglion cells. This study reveals that lungfish possess a heterogeneous population of ganglion cells distributed in a horizontal streak across the retinal meridian, which is formed early in development and maintained through to adult stages. The number and complement of both ganglion cells and a population of putative amacrine cells within the ganglion cell layer are examined using retrograde labelling from the optic nerve and transmission electron-microscopic analysis of axons within the optic nerve. At least four types of retinal ganglion cells are present and lie predominantly within a thin ganglion cell layer, although two subpopulations are identified, one within the inner plexiform and the other within the inner nuclear layer. A subpopulation of retinal ganglion cells comprising up to 7% or the total population are significantly larger (> 400 mu m(2)) and are characterized as giant or alpha-like cells. Up to 44% of cells within the retinal ganglion cell layer represent a population of presumed amacrine cells. The optic nerve is heavily fasciculated and the proportion of myelinated axons increases with body length from 17% in subadults to 74% in adults. Spatial resolving power, based on ganglion cell spacing, is low (1.6-1.9 cycles deg(-1), n = 2) and does not significantly increase with growth. This represents the first detailed study of retinal ganglion cells in sarcopterygian fish, and reveals that, despite variation amongst animal groups, trends in ganglion cell density distribution and characteristics of cell types were defined early in vertebrate evolution.