Determination of lifter design, speed and filling effects in AG mills by 3D DEM

The power required to operate large gyratory mills often exceeds 10 MW. Hence, optimisation of the power consumption will have a significant impact on the overall economic performance and environmental impact of the mineral processing plant. In most of the published models of tumbling mills (e.g. [Morrell, S., 1996. Power draw of wet tumbling mills and its relationship to charge dynamics, Part 2: An empirical approach to modelling of mill power draw. Trans. Inst. Mining Metall. (Section C: Mineral Processing Ext. Metall.) 105, C54-C62. Austin, L.G., 1990. A mill power equation for SAG mills. Miner. Metall. Process. 57-62]), the effect of lifter design and its interaction with mill speed and filling are not incorporated. Recent experience suggests that there is an opportunity for improving grinding efficiency by choosing the appropriate combination of these variables. However, it is difficult to experimentally determine the interactions of these variables in a full scale mill. Although some work has recently been published using DEM simulations, it was basically. limited to 2D. The discrete element code, Particle Flow Code 3D (PFC3D), has been used in this work to model the effects of lifter height (525 cm) and mill speed (50-90% of critical) on the power draw and frequency distribution of specific energy (J/kg) of normal impacts in a 5 m diameter autogenous (AG) mill. It was found that the distribution of the impact energy is affected by the number of lifters, lifter height, mill speed and mill filling. Interactions of lifter design, mill speed and mill filling are demonstrated through three dimensional distinct element methods (3D DEM) modelling. The intensity of the induced stresses (shear and normal) on lifters, and hence the lifter wear, is also simulated. (C) 2004 Elsevier Ltd. All rights reserved.

Geometric distortion in clinical MRI systems - Part II: correction using a 3D phantom

In this paper, we present the correction of the geometric distortion measured in the clinical magnetic resonance imaging (MRI) systems reported in the preceding paper (Part 1) using a 3D method based on the phantom-mapped geometric distortion data. This method allows the correction to be made on phantom images acquired without or with the vendor correction applied. With the vendor's 2D correction applied, the method corrects for both the residual geometric distortion still present in the plane in which the correction method was applied (the axial plane) and the uncorrected geometric distortion along the axis non-nal to the plane. The evaluation of the effectiveness of the correction using this new method was carried out through analyzing the residual geometric distortion in the corrected phantom images. The results show that the new method can restore the distorted images in 3D nearly to perfection. For all the MRI systems investigated, the mean absolute deviations in the positions of the control points (along x-, y- and z-axes) measured on the corrected phantom images were all less than 0.2 mm. The maximum absolute deviations were all below similar to0.8 mm. As expected, the correction of the phantom images acquired with the vendor's correction applied in the axial plane performed equally well. Both the geometric distortion still present in the axial plane after applying the vendor's correction and the uncorrected distortion along the z-axis have all been restored. (C) 2004 Elsevier Inc. All rights reserved.

Geometric distortion in clinical MRI systems - Part I: evaluation using a 3D phantom

Recently, a 3D phantom that can provide a comprehensive and accurate measurement of the geometric distortion in MRI has been developed. Using this phantom, a full assessment of the geometric distortion in a number of clinical MRI systems (GE and Siemens) has been carried out and detailed results are presented in this paper. As expected, the main source of geometric distortion in modern superconducting MRI systems arises from the gradient field nonlinearity. Significantly large distortions with maximum absolute geometric errors ranged between 10 and 25 mm within a volume of 240 x 240 x 240 mm(3) were observed when imaging with the new generation of gradient systems that employs shorter coils. By comparison, the geometric distortion was much less in the older-generation gradient systems. With the vendor's correction method, the geometric distortion measured was significantly reduced but only within the plane in which these 2D correction methods were applied. Distortion along the axis normal to the plane was, as expected, virtually unchanged. Two-dimensional correction methods are a convenient approach and in principle they are the only methods that can be applied to correct geometric distortion in a single slice or in multiple noncontiguous slices. However, these methods only provide an incomplete solution to the problem and their value can be significantly reduced if the distortion along the normal of the correction plane is not small. (C) 2004 Elsevier Inc. All rights reserved.

Analysis of lipoproteins using 2D diffusion-edited NMR spectroscopy and multi-way chemometrics

This study represents the first application of multi-way calibration by N-PLS and multi-way curve resolution by PARAFAC to 2D diffusion-edited H-1 NMR spectra. The aim of the analysis was to evaluate the potential for quantification of lipoprotein main- and subtractions in human plasma samples. Multi-way N-PLS calibrations relating the methyl and methylene peaks of lipoprotein lipids to concentrations of the four main lipoprotein fractions as well as 11 subfractions were developed with high correlations (R = 0.75-0.98). Furthermore, a PARAFAC model with four chemically meaningful components was calculated from the 2D diffusion-edited spectra of the methylene peak of lipids. Although the four extracted PARAFAC components represent molecules of sizes that correspond to the four main fractions of lipoproteins, the corresponding concentrations of the four PARAFAC components proved not to be correlated to the reference concentrations of these four fractions in the plasma samples as determined by ultracentrifugation. These results indicate that NMR provides complementary information on the classification of lipoprotein fractions compared to ultracentrifugation. (C) 2004 Elsevier B.V. All rights reserved.

A First Order Predicate Logic Formulation of the 3D Reconstruction Problem and its Solution Space

This paper defines the 3D reconstruction problem as the process of reconstructing a 3D scene from numerous 2D visual images of that scene. It is well known that this problem is ill-posed, and numerous constraints and assumptions are used in 3D reconstruction algorithms in order to reduce the solution space. Unfortunately, most constraints only work in a certain range of situations and often constraints are built into the most fundamental methods (e.g. Area Based Matching assumes that all the pixels in the window belong to the same object). This paper presents a novel formulation of the 3D reconstruction problem, using a voxel framework and first order logic equations, which does not contain any additional constraints or assumptions. Solving this formulation for a set of input images gives all the possible solutions for that set, rather than picking a solution that is deemed most likely. Using this formulation, this paper studies the problem of uniqueness in 3D reconstruction and how the solution space changes for different configurations of input images. It is found that it is not possible to guarantee a unique solution, no matter how many images are taken of the scene, their orientation or even how much color variation is in the scene itself. Results of using the formulation to reconstruct a few small voxel spaces are also presented. They show that the number of solutions is extremely large for even very small voxel spaces (5 x 5 voxel space gives 10 to 10(7) solutions). This shows the need for constraints to reduce the solution space to a reasonable size. Finally, it is noted that because of the discrete nature of the formulation, the solution space size can be easily calculated, making the formulation a useful tool to numerically evaluate the usefulness of any constraints that are added.

Automatic initialisation of 3D deformable models for cartilage segmentation

Deformable models are a highly accurate and flexible approach to segmenting structures in medical images. The primary drawback of deformable models is that they are sensitive to initialisation, with accurate and robust results often requiring initialisation close to the true object in the image. Automatically obtaining a good initialisation is problematic for many structures in the body. The cartilages of the knee are a thin elastic material that cover the ends of the bone, absorbing shock and allowing smooth movement. The degeneration of these cartilages characterize the progression of osteoarthritis. The state of the art in the segmentation of the cartilage are 2D semi-automated algorithms. These algorithms require significant time and supervison by a clinical expert, so the development of an automatic segmentation algorithm for the cartilages is an important clinical goal. In this paper we present an approach towards this goal that allows us to automatically providing a good initialisation for deformable models of the patella cartilage, by utilising the strong spatial relationship of the cartilage to the underlying bone.