Thesis (M. Eng.(Geotechnical Engineering))--University of Pretoria, 2003. / Includes bibliographical references.

Thesis (M.S.)--Ohio University, August, 2004. / Title from PDF t.p. Includes bibliographical references (p. 71-73)

A vast amount and variety of mine tailings are produced around the world each day. In the gold¬mining industry in South Africa the residue of crushed are is disposed of in large tailings or hydraulic fill dams. The outer walls of these dams are built up of layers of material, each of which is allowed to dry before the next layer is placed. In order to study the stability of these walls, the appropriate engineering properties of the tailings must be ascertained. Due to the construction technique used in tailings dam construction, the outer walls are in an unsaturated state, which also means that suctions are generated within the tailings. Various techniques exist to measure suction, most of which are indirect methods. The recent development of the mid-¬plane suction probe at the University of Pretoria created the opportunity of measuring suctions directly on desiccating samples of gold mine tailings. A test method has been developed from which soil mechanics parameters can be derived from suction measurements. The experimental programme consisted of a series of these newly developed tests on fine and coarse samples of gold mine tailings, as well as on different particle size ranges. The experimental results were used in the development of a new method of predicting the air-entry value, with only the grading of the tailings known. A new method of predicting the soil-water characteristic curve up to the air-entry value was also proposed. The results of the research showed that the tailings remain saturated up to the air-entry value. The clay, fine silt and medium silt sized tailings was found to be the controlling particle size ranges in the development of suctions. The vast amount of parameters and information gained through the use of the proposed test method clearly indicates its effectiveness in studying the performance and characteristics of a material drying from saturation. The results also indicated the effectiveness of the mid-plane suction probe for the direct measurement of suction. / Dissertation (M Eng (Geotechnical Engineering))--University of Pretoria, 2006. / Civil Engineering / unrestricted

Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Earth and Planetary Sciences. / Microfiche copy available in Archives and Science. / Vita. / Includes bibliographies. / by Wilford D. Gardner. / Ph.D.

The purpose of this work is to find a method of determining the average particle size in samples of clays and ceramical materials, and to attempt to classify their physical properties according to the size of the particles. Such data should be useful to compare the properties of clays, to match different samples for uniformity, and to better control processes where clays are used, as for instance in manufacture of paper, rubber, and burned wear. / M.S.

The present research is concerned with developing analysis methods for analyzing and exploring finite-amplitude elastic wave propagation through periodic media. Periodic arrangements of materials with high acoustic impedance contrasts can be employed to control wave propagation. These systems are often termed phononic crystals or metamaterials, depending on the specific design and purpose. Design of these systems usually relies on computation and analysis of dispersion band structures which contain information about wave propagation speed and direction. The location and influence of complete (and partial) band gaps is a particularly interesting characteristic. Wave propagation is prohibited for frequencies that correspond to band gaps; thus, periodic systems behave as filters, wave guides, and lenses at certain frequencies. Controlling these behaviors has typically been limited to the manufacturing stage or the application of external stimuli to distort material configurations. The inclusion of nonlinear elements in periodic unit cells offers an option for passive tuning of the dispersion band structure through amplitude-dependence. Hence, dispersion analysis methods which may be utilized in the design of nonlinear phononic crystals and metamaterials are required. The approach taken herein utilizes Bloch wave-based perturbation analysis methods for obtaining closed-form expressions for dispersion amplitude-dependence. The influence of material and geometric nonlinearities on the dispersion relationship is investigated. It is shown that dispersion shifts result from both self-action (monochromatic excitation) and wave-interaction (multi-frequency excitation), the latter enabling dynamic anisotropy in periodic media. A particularly novel aspect of this work is the ease with which band structures of discretized systems may be analyzed. This connection enables topology optimization of unit cells with nonlinear elements. Several important periodic systems are considered including monoatomic lattices, multilayer materials, and plane stress matrix-inclusion configurations. The analysis methods are further developed into a procedure which can be implemented numerically with existing finite-element analysis software for analyzing geometrically-complex materials.

This study employed Monte Carlo simulation to investigate the ability of the growth mixture model (GMM) to correctly identify models based on a "true" two-class pseudo-population from alternative models consisting of "false" one- and three-latent trajectory classes. This ability was assessed in terms of statistical power, defined as the proportion of replications that correctly identified the two-class model as having optimal fit to the data compared to the one-class model, and accuracy, which was defined as the proportion of replications that correctly identified the two-class model over both one- and three-class models. Estimates of power and accuracy were adjusted by empirically derived critical values to reflect nominal Type I error rates of a = .05. Six experimental conditions were examined: (a) standardized between-class differences in growth parameters, (b) percentage of total variance explained by growth parameters, (c) correlation between intercepts and slopes, (d) sample size, (e) number of repeated measures, and (f) planned missingness. Estimates of statistical power and accuracy were related to a measure of the degree of separation and distinction between latent trajectory classes (λ2 ), which approximated a chi-square based noncentrality parameter. Model selection relied on four criteria: (a) the Bayesian information criterion (BIC), (b) the sample-size adjusted BIC (ABIC), (c) the Akaike information criterion (AIC), and (d) the likelihood ratio test (LRT). Results showed that power and accuracy of the GMM to correctly enumerate latent trajectory classes were positively related to greater between-class separation, greater proportion of total variance explained by growth parameters, larger sample sizes, greater numbers of repeated measures, and larger negative correlations between intercepts and slopes; and inversely related to greater proportions of missing data. Results of the Monte Carlo simulations were field tested using specific design and population characteristics from an evaluation of a longitudinal demonstration project. This test compared estimates of power and accuracy generated via Monte Carlo simulation to estimates predicted from a regression of derived λ2 values. Results of this motivating example indicated that knowledge of λ2 can be useful in the two-class case for predicting power and accuracy without extensive Monte Carlo simulations.

Abstract not available

This work reports the results of a systematic study of the factors that affect the bridging behaviour of bagasse. It shows that traditional bulk solids theory is inappropriate for predicting bagasse flow mainly because of the impossibility of obtaining a reliable measure of internal friction. It demonstrates the significant influence of fibre length and moisture content on its handling charateristics. Correlations of pertinent bulk properties such as compactibility, tensile strength, surface friction and translation of vertical into horizontal pressure have been developed. These were derived as a result of measurements in equipment that was designed for the purpose. Finally, an empirical model utilising these correlations is proposed by which the likelihood of bridge formation in any piece of bagasse handling equipment can be determined. The validity of the model is assessed by comparison with bridging tests that were performed under controlled conditions. / Thesis (Ph.D.)-University of Natal, 1996

Thesis (MScEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Hydrocyclones are stationary separating machines that separate materials based on centrifugal separation and are widely used in chemical engineering and mineral processing industries. Their design and operation, compact structure, low running costs and versatility all contribute to their applications in liquid clarification, slurry thickening, solid washing and classification. With any of these operations, the overall profitability of the process relies on the effective control of the process equipment. However, in practice, hydrocyclones are difficult to monitor and control, owing to the complexity and difficulty in measuring internal flows in the equipment. Several studies have indicated that hydrocyclone underflow images can be used to monitor process conditions. The research described in this thesis considers the use of image analysis to monitor particle size and solids concentration in the underflow discharge of a hydrocyclone. The experimental work consisted of laboratory and industrial-based case studies. The laboratory cyclone used was a 76 mm general laboratory cyclone. A Canon EOS 400D digital camera was used for the underflow imaging. Image features such as pixel intensity values, underflow discharge width and grey level co-occurrence matrix (GLCM) were extracted from the images using MATLAB Toolbox software. Linear discriminant analysis (LDA) and neural network (NN) classification models were used to discriminate between different PGM ore types based on features extracted from the underflow of the hydrocyclone. Likewise, multiple linear regression and neural network models were used to estimate the underflow solids content and mean particle size in the hydrocyclone underflow. The LDA model could predict the PGM ore types with 61% reliability, while the NN model could do so with a statistically similar 62% reliability. The multiple linear regression models could explain 56% and 40% of variance in the mean particle size and solids content respectively. In contrast, the neural network model could explain 67% and 45% of the variance of the mean particle size and solids content respectively. For the industrial system, a 100% correct classification was achieved with all methods. However, these results are regarded as unreliable, owing to the insufficient data used in the models. / AFRIKAANSE OPSOMMING: Hidrosiklone is stasionêre skeidingsmasjiene wat materiale skei op grond van sentrifugale skeiding en word algemeen gebruik in die chemiese ingenieurswese en mineraalprosessering industrieë. Hul ontwerp en werking, kompakte struktuur, lae bedryfskoste en veelsydigheid dra by tot hul gebruik vir toepassings in vloeistofsuiwering, slykverdikking, vastestof wassing en klassifikasie. In enige van hierdie prosesse hang die oorhoofse winsgewendheid van die proses af van die effektiewe beheer van die prosestoerusting. In die praktyk is hidrosiklone egter moeilik om te monitor en beheer weens die kompleksiteit en moeilikheidsgraad daarvan om die interne vloei in die apparaat te meet. Verskeie studies het aangedui dat hidrosikloon ondervloeibeelde gebruik kan word om die proseskondisies te monitor. Die navorsing beskryf in hierdie tesis maak gebruik van beeldanalise moniteringstegnieke om die ertstipes en grootte- verspreidingsgebiede/ klasse van die ondervloei afvoerpartikels te bepaal. Sodoende word ‘n grondslag gelê vir verbeterde sikloon monitering en beheer. Die eksperimentele werk het bestaan uit beide laboratorium en industrieel-gebaseerde studies. Die laboratorium sikloon wat gebruik is, was ‘n 76 mm algemene laboratorium sikloon. ‘n Canon EOS 400D digitale kamera is gebruik om die hidrosikloon ondervloei beelde vas te vang. Beeldeienskappe soos beeldelement intensiteitswaardes, ondervloei afvoerwydte en grysvlak mede-voorkoms matriks is onttrek uit die beelde deur gebruik te maak van MATLAB Toolbox sagteware. Lineêre diskriminantanalise (LDA) en neural netwerk (NN) klassifikasiemodelle is gebou om te onderskei tussen die verskillende PGM ertse en gebaseer op veranderlikes wat afgelei is uit beelde van die ondervloei van die sikloon. Net so is daar ook gebruik gemaak van lineêre regressie- en neural netwerkmodelle om die vasestofkonsentrasie en gemiddelde partikelgrootte in die ondervloei van die sikloon te beraam. Die LDA model kon die PGM ertstipes met 61% betroubaarheid voorspel, terwyl die neural netwerkmodel dit kon doen met statisties dieselfde betroubaarheid van 62%. Die lineêre regressiemodelle kon onderskeidelik 56% en 40% van die variansie in die gemiddelde partikelgrootte en vastestofkonsentrasie verduidelik. In teenstelling iermee, kon die neurale netwerkmodel 67% en 45% van die variansie in die gemiddelde partikelgrootte en vastestofkonsentrasie verduidelik. In die nywerheidstelsel kon beide tipe modelle perfekte onderskeid tref tussen die partikelgroottes wat gemeet is op opeenvolgende dae van die bedryf van die siklone. Hierdie resultate is egter nie betroubaar nie, a.g.v. die beperkte hoeveelheid data wat beskikbaar was vir modellering.