Numerical simulation of magnetite segregation in a dense medium cyclone

Numerical simulations of turbulent driven flow in a dense medium cyclone with magnetite medium have been conducted using Fluent. The predicted air core shape and diameter were found to be close to the experimental results measured by gamma ray tomography. It is possible that the Large eddy simulation (LES) turbulence model with Mixture multi-phase model can be used to predict the air/slurry interface accurately although the LES may need a finer grid. Multi-phase simulations (air/water/medium) are showing appropriate medium segregation effects but are over-predicting the level of segregation compared to that measured by gamma-ray tomography in particular with over prediction of medium concentrations near the wall. Further, investigated the accurate prediction of axial segregation of magnetite using the LES turbulence model together with the multi-phase mixture model and viscosity corrections according to the feed particle loading factor. Addition of lift forces and viscosity correction improved the predictions especially near the wall. Predicted density profiles are very close to gamma ray tomography data showing a clear density drop near the wall. The effect of size distribution of the magnetite has been fully studied. It is interesting to note that the ultra-fine magnetite sizes (i.e. 2 and 7 mu m) are distributed uniformly throughout the cyclone. As the size of magnetite increases, more segregation of magnetite occurs close to the wall. The cut-density (d(50)) of the magnetite segregation is 32 gm, which is expected with superfine magnetite feed size distribution. At higher feed densities the agreement between the [Dungilson, 1999; Wood, J.C., 1990. A performance model for coal-washing dense medium cyclones, Ph.D. Thesis, JKMRC, University of Queensland] correlations and the CFD are reasonably good, but the overflow density is lower than the model predictions. It is believed that the excessive underflow volumetric flow rates are responsible for under prediction of the overflow density. (c) 2006 Elsevier Ltd. All rights reserved.

Study of flow behaviour in a three-product cyclone using computational fluid dynamics

Simplicity in design and minimal floor space requirements render the hydrocyclone the preferred classifier in mineral processing plants. Empirical models have been developed for design and process optimisation but due to the complexity of the flow behaviour in the hydrocyclone these do not provide information on the internal separation mechanisms. To study the interaction of design variables, the flow behaviour needs to be considered, especially when modelling the new three-product cyclone. Computational fluid dynamics (CFD) was used to model the three-product cyclone, in particular the influence of the dual vortex finder arrangement on flow behaviour. From experimental work performed on the UG2 platinum ore, significant differences in the classification performance of the three-product cyclone were noticed with variations in the inner vortex finder length. Because of this simulations were performed for a range of inner vortex finder lengths. Simulations were also conducted on a conventional hydrocyclone of the same size to enable a direct comparison of the flow behaviour between the two cyclone designs. Significantly, high velocities were observed for the three-product cyclone with an inner vortex finder extended deep into the conical section of the cyclone. CFD studies revealed that in the three-product cyclone, a cylindrical shaped air-core is observed similar to conventional hydrocyclones. A constant diameter air-core was observed throughout the inner vortex finder length, while no air-core was present in the annulus. (c) 2006 Elsevier Ltd. All rights reserved.

Review of recent results on excursion set models

Many images consist of two or more 'phases', where a phase is a collection of homogeneous zones. For example, the phases may represent the presence of different sulphides in an ore sample. Frequently, these phases exhibit very little structure, though all connected components of a given phase may be similar in some sense. As a consequence, random set models are commonly used to model such images. The Boolean model and models derived from the Boolean model are often chosen. An alternative approach to modelling such images is to use the excursion sets of random fields to model each phase. In this paper, the properties of excursion sets will be firstly discussed in terms of modelling binary images. Ways of extending these models to multi-phase images will then be explored. A desirable feature of any model is to be able to fit it to data reasonably well. Different methods for fitting random set models based on excursion sets will be presented and some of the difficulties with these methods will be discussed.

Energy and averages in the mechanics of granular materials

We derive a general thermo-mechanical theory for particulate materials consisting of granules of arbitrary whose material points possess three translational and three independent rotational degrees of freedom. Additional field variables are the translational and rotational granular temperatures, the kinetic energies shape and size. The kinematics of granulate is described within the framework of a polar continuum theory of the velocity and spin fluctuations respectively and the usual thermodynamic temperature. We distinguish between averages over particle categories (averages in mass/velocity and moment of inertia/spin space, respectively) and particle phases where the average extends over distinct subsets of particle categories (multi phase flows). The relationship between the thermal energy in the granular system and phonon energy in a molecular system is briefly discussed in the main body of the paper and discussed in detail in the Appendix A. (C) 2001 Elsevier Science B.V. All rights reserved.

Effect of hardness on three very different forms of wear

Different abrasive wear tests have been applied to materials with hardnesses ranging from 80 HV (aluminium) to 1700 HV (tungsten carbide). The tests were: dry sand rubber wheel (DSRbrW); a similar test using a steel wheel (DSStlW); a new combined impact-abrasion test (FIA). The DSRbrW results were as expected, giving generally decreasing wear with increasing hardness. White cast irons and tool steels containing coarse, hard carbide particles performed better than more homogeneous materials of comparable hardness. When normalized to load and distance, the DSStlW results for the homogeneous materials were similar to the DSRbrW results. The multi-phase materials performed poorly in the DSStlW test, with volume loss for high-speed steel (880 HV) higher than that of aluminium. Within this group, wear increased with increasing hardness. These unexpected results are explained in terms of (a) differential friction coefficients of wheel and specimen, (b) increased fracture of sand, and (c) introduction of microfracture wear mechanisms. The FIA combined impact-abrasion results lacked clear correlations with hardness. The span of relative wear rates was similar to that reported for materials in ball mills. White cast irons at maximum hardness performed fairly poorly and showed evidence of microfracture. (C) 1997 Elsevier Science S.A.

Refining individualized consideration: Distinguishing developmental leadership and supportive leadership

This study explores the theoretical and empirical distinction between developmental leadership and supportive leadership, which are currently encompassed in a single sub dimension of transformational leadership, individualized consideration. Items were selected to assess these constructs, and hypotheses regarding the differential effects of developmental and supportive leadership were proposed. Confirmatory factor analyses provided support for the proposed distinction between developmental and supportive leadership, although these leadership factors were very strongly associated. Structural equation modelling and multi-level modelling results indicated that both developmental leadership and supportive leadership displayed unique relationships with theoretically selected outcome measures. Developmental leadership displayed significantly stronger relationships with job satisfaction, career certainty, affective commitment to the organization and role breadth self-efficacy than did supportive leadership. Results provide initial evidence in support of the discriminant validity of these two types of leadership. Discussion focuses on the need to further examine the construct of developmental leadership.

Experiments and modelling of phenanthrene biodegradation in the aqueous phase by a mixed culture

Pollution by polycyclic aromatic hydrocarbons(PAHs) is widespread due to unsuitable disposal of industrial waste. They are mostly defined as priority pollutants by environmental protection authorities worldwide. Phenanthrene, a typical PAH, was selected as the target in this paper. The PAH-degrading mixed culture, named ZM, was collected from a petroleum contaminated river bed. This culture was injected into phenanthrene solutions at different concentrations to quantify the biodegradation process. Results show near-complete removal of phenanthrene in three days of biodegradation if the initial phenanthrene concentration is low. When the initial concentration is high, the removal rate is increased but 20%-40% of the phenanthrene remains at the end of the experiment. The biomass shows a peak on the third day due to the combined effects of microbial growth and decay. Another peak is evident for cases with a high initial concentration, possibly due to production of an intermediate metabolite. The pH generally decreased during biodegradation because of the production of organic acid. Two phenomenological models were designed to simulate the phenanthrene biodegradation and biomass growth. A relatively simple model that does not consider the intermediate metabolite and its inhibition of phenanthrene biodegradation cannot fit the observed data. A modified Monod model that considered an intermediate metabolite (organic acid) and its inhibiting reversal effect reasonably depicts the experimental results.

Multi-centre Phase II trial of the polyamine synthesis inhibitor SAM486A (CGP48664) in patients with metastatic melanoma

Purpose: To determine the activity and tolerability of SAM496A, an inhibitor of S-adenosylmethionine decarboxylase (SAMDC), in patients with metastatic melanoma who had not received prior chemotherapy. Selected patients were offered participation in two sub-studies examining early changes in tumor metabolism with FDG-PET and changes in tumor polyamine content. Patients and methods: Fifteen patients with measurable metastatic melanoma, normal cardiac function, and no known CNS metastases were eligible and received SAM486A by 1-hour IV infusion daily for 5 days every 3 weeks. Response was assessed by SWOG criteria. Results: No patient had a confirmed partial response. Fatigue/lethargy, myalgia and neutropenia were the main toxicities but no febrile neutropenia or grade 4 non-hematological toxicity occurred. Five patients had PET scans pre-treatment and on days 8-12 of cycle 1. No patient had reduction of tumor metabolism. Serial biopsy in one patient showed alterations in polyamines consistent with SAMDC inhibition. Conclusions: Using the present dose and schedule of administration, SAM486A does not have significant therapeutic potential in patients with metastatic melanoma.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.