The present dissertation describes the efforts directed towards the development of computational tools to support process modeling. This work is also a further development of the Thermoslag® software developed in the Division of Materials Process Science, KTH. The essential parts of the thesis are a) development of a semi-empirical model for the estimation of the molar volumes/densities of multicomponent slags with a view to incorporate the same in the model for viscosities and b) further development of the viscosity model for application towards fluoride- and manganese containing slags, as for example, mould flux slags and manganese slags used in ferromanganese production. c) estimating fluoride emissions from industrial slags and mould fluxes. d) study the reaction between carbon particles, hematite containing slags and in oxygen containing atmosphere. The model for the estimation of molar volume is based on a correlation between the relative integral molar volume of a slag system and the relative integral molar enthalpies of mixing of the same system. The integral molar enthalpies of the relevant systems could be evaluated from the Gibbs energy data available in the Thermoslag® software. The binary parameters were evaluated from experimental measurements of the molar volumes. Satisfactory correlations were obtained in the case of the binary silicate and aluminate systems. The model was extended to ternary and multi component systems by computing the molar volumes using the binary parameters. The model predictions showed agreements with the molar volume data available in literature. The model was used to estimate the molar volumes of industrial slags as well as to trace the trends in molar volume due to enable prediction of molar volumes of slags that are compatible with the thermodynamic data available. With a view to extend the existing model for viscosities to F--containing slags, the viscosities of mould flux slags for continuous casting in steel production have been investigated in the present work. The measurements were carried out utilizing the rotating cylinder method. Seven mould fluxes used in the Swedish steel industry and the impact of Al2O3 pick up by mould flux slags on viscosities were included in the study. The results showed that even relatively small additions of Al2O3 are related with a significant increase in viscosity. A similar experimental technique was employed to estimate the viscosity of twelve synthetic slags corresponding to composition of the raw materials used in ferromanganese production. The flow rate of the liquid slag, which is determined by the slag viscosity, is an important parameter affecting the reduction rate of manganese oxide. The results show a clear correlation between manganese oxide content and viscosity. An increase of MnO in the slag lowers the viscosity. The measured viscosities have also been connected to the structure of the silicates. The fluoride loss from the binary slag systems Al2O3-SiO2, CaO-SiO2 and MgOSiO2 with additions of CaF2 was studied by thermogravimetric (TGA) studies. The Arrhenius activation energy for the evaporation reaction of fluorides was found to be dependent on temperature and slag chemistry for the slags studied. A correlation between the activation energy for fluoride evaporation and activity of SiO2 in the slag melt was established. This relationship obtained for the binary systems appears also to be suitable for the ternary systems Al2O3-CaO-SiO2 with CaF2 addition, which indicates a possibility to estimate the fluoride emissions from industrial slags and mould fluxes. A Confocal Scanning Laser Microscopy was used to investigate the reaction between carbon particles in hematite containing slags and in oxygen containing atmosphere. Experiments with varying temperature and slags with varying FeOx content were carried out. The general trends were that the particle size decrease was more rapid with increase of FeOx amount and/or temperature was increased. / QC 20100812

No description available.

The radiation heat transfer from an argon and a nitrogen transferred-arc column to a cylindrical enclosure was measured. The rate of heat transfer was successfully correlated in a non-dimensional manner, with respect to the arc length within the enclosure and the enclosure diameter for the section of the arc column located within the enclosure, and with respect to the arc length outside the enclosure and the enclosure diameter for the section of the arc column outside the enclosure. / It was discovered that tangential injection of a particulate feed material into the cylindrical enclosure led to the formation of destabilizing lump-like deposits on the roof and wall of the enclosure. Feeding vertically through the roof of the enclosure in the presence of a vortex resulted in the formation of a uniform film deposit and stable operation. Under these conditions, up to 49% of the incident radiant energy emanating from the arc column to the sleeve surface was absorbed by the feed. / The carbothermic reduction of a fine (3-10$ mu$m) V$ sb2$O$ sb5$ powder in the plasma furnace resulted in the production of a commercial ferrovanadium alloy of controllable vanadium content. Particulate losses to the exhaust gases were very low, in the order of 2%. Specific energy consumption was 17kWh/kg of vanadium produced. Based on the results of these tests, specific energy consumption at a larger scale would be reduced by at least 50%.

Thesis (M.S.)--Rochester Institute of Technology, 1987. / Typescript. Includes bibliographical references (leaves 79-81).

Dissertation (PhD)--University of Stellenbosch, 2000. / ENGLISH ABSTRACT: Silver/Zinc batteries are extensively used for applications where a power source with a high energy density is needed. A reactor was developed to manufacture the zinc electrodes for these batteries. The parameters for the control of this reactor were identified. The interaction and relationships between the set of parameters were established and quantified. The novel design of the reactor includes features such as continuous replenishment of the constituting chemicals, parallel flow of the plating fluid, inert anodes and a serial electrical layout. The controlling parameters consist of both chemical and physical parameters. They are - zincate concentration, hydroxyl concentration, density, temperature, flow rate of the plating fluid, and current density. The unique solubility characteristics of zinc oxide in potassium hydroxide lend themselves to a novel approach for the determination of the zincate concentration in· the plating solution. A set of conditions for the manufacturing of electrodes, with the required characteristics, was identified. The requirements are densely packed zinc dendrite morphology with high porosity and mechanical stability. The designed reactor complies with the industries safety requirements. The batteries were successfully applied in their operational domain (torpedoes) after this extensive research project was completed. / AFRIKAANSE OPSOMMING: Silwer/Sink batterye word intensief aangewend in gebruike waar 'n kragbron met hoë energie digtheid benodig word. 'n Reaktor is ontwikkel wat die sink elektrodes van die tipes batterye vervaardig. Die veranderlikes vir die beheer van die reaktor is bepaal. Die interaksie en verwantskap tussen die stel veranderlikes is verkry en gekwantifiseer. Die unieke ontwerp van die reaktor het die volgende karakteristieke, nl. aaneenlopende vervanging van die chemikalië verbruik, parallelle vloei van die plateringsvloeistof, inerte anodes en elektriese uitleg in serie. Die chemiese en fisiese veranderlikes is beide beherende veranderlikes. Hierdie fisiese en chemiese veranderlikes wat die proses beheer is die sinkaat konsentrasie, hidroksiel konsentrasie, digtheid, temperatuur, vloeitempo van die plateringsvloeistof en die stroomdigtheid. Die unieke oplossingskarakteristieke van sinkoksied in kalsium· hidroksied leen hom tot die unieke proses om die sinkaat konsentrasie in die plateringsvloeistof te bepaal. 'n Steloperasionele kondisies vir die vervaardiging van die elektrodes met die spesifieke spesifikasies soos verlang, is geïdentifiseer. Hierdie kondisies is die diggepakte sinkdendriet morfologie met 'n hoë porositeit en meganiese stabiliteit. Die ontwerpte reaktor voldoen aan die industriële veiligheidsvereistes en die ergonomiese maatstawwe. Die batterye is suksesvol gebruik in hulle industriële aanwending as gevolg van die suksesvolle afhandeling van die stuk navorsing.

Thesis (PhD)--University of Stellenbosch, 2002. / ENGLISH ABSTRACT: The availability of vast deposits of high-grade ore bodies are rapidly becoming something of the past in the modern mining and metallurgical scenario. Apart from the lower grade content of these ore bodies, complex mineralogy are an even greater obstacle in the recovery of valuable metal species. The development of new technology to deal with these type of ore bodies is therefore critical and worth investigating, as the world's easily exploitable high grade ore deposits are decreasing. Valuable species can be recovered from sparingly soluble solids, which slightly dissociate to give traces of the valuable ions in solution, with the use of ion-exchange resins in a slurry mixture. A dissociation equilibrium exists between the dissolved ions in solution and the solid ore body. Jf the dissolved ions are removed from the solution by ion-exchange, the solid / liquid dissociation equilibrium is continually displaced. According to Le Chatelier's principle further dissolution of the sparingly soluble solid is required to restore the equilibrium concentration of the valuable species in solution. It is possible to recover valuable metal species from metal precipitates, such as metal sulphides, by contacting a slurry of the precipitate with a suitable ion-exchange resin. The resulting ion exchange reaction between the valuable metal species and counter ions creates electrolyte solutions that may facilitate the further dissolution of the metal precipitate. These counter ion electrolyte solutions may easily become significantly concentrated. This occurs in the event of a Resin-in-Leach (RIL) mixture that results in a continuous ion-exchange reaction taking place due to the continually changing electrolyte composition of the mixture, which significantly changes the activities and hence the solubility of the valuable metal species in solution. Complete dissolution and liberation of the metal precipitate can often be achieved provided that a sufficient amount of a suitable high capacity ion-exchange resin is used in a properly engineered Resin-in- Leach (RIL) circuit. The simultaneous dissolution and adsorption of various base metal precipitates were tested. Various interactions that take place in the slurry at molecular level as well as the effects of various variables on the "adsorption by dissolution process" are discussed through the development of fundamental thermodynamic models. These thermodynamic mathematical models are developed for the three phase system that exists in a Resin-in- Leach mixture, i.e. the solid ore body, the electrolyte solution and the ion-exchange resin, and can be used for possible other applications such as the recovery of rare earths from low grade ores in the minerals processing industry. A typical example of an industrial process for the recovery of rare earth species is the percolation leaching of rare earths from low-grade kaolinitic ores, which continually shifts the solid / liquid dissociation equilibrium condition. The rare earth content of these ores is usually between 0.05%and 0.3 %, which is very low by any modern industrial extraction and refining standards. / AFRIKAANSE OPSOMMING: Die beskikbaarheid van ryk mineraal ertsneerslae is spoedig besig om iets van die verlede te word in die huidige mineraalontginning en metallurgiese veredelings industrie. Afgesien van die lae graad van die huidige mineraal ertsneerslae, blyk die komplekse mineralogiese samestelling van hierdie neerslae In veel groter struikelblok te wees in die herwinning en veredeling van die edelmetale teenwoordig in hierdie ertse. Die ontwikkeling van nuwe veredelings en ekstratiewe tegnologie vir die herwinning van edel metale, vanuit hierdie lae graad mineraal ertsneerslae, word dus benodig wat verdere navorsing in hierdie gebied regverdig. Dit is wel moontlik om metaal spesies afkomstig van ertse met 'n baie lae oplosbaarheid in waterige oplossings te herwin met ioon-uitruilings harse vanweë die feit dat die metaal spesies wel teen baie lae konsentrasies in die waterige oplossings teenwoordig is. Die metaal spesies los op in die waterige oplossings volgens hulle karakteristieke oplossings termodinamika. Indien die opgeloste metaal spesies vanuit die waterige oplossing verwyder word, sal die vaste stof / vloeistof ewewigs balans weer herstel word deurdat die vaste stof verder saloplos as gevolg van Le Chatelier se beginsel. Dit is dus moontlik om metaalagtige spesies, soos metaal sulfiedes, te herwin deur 'n waterige oplossing wat die metaal erts bevat in kontak te bring met 'n ioon-uitruilings hars. Die daaropvolgende ioon-uitruilings reaksie tussen die metaalagtige spesies en die spesies teenswoordig op die ioon-uitruilingshars het tot gevolg dat die elektrolitiese samestelling van die waterige oplossing verander. Dit is die gevolg van die migrasie van spesies aanvanklik teenswoordig op die hars wat in die waterige fase eindig. Die veranderende samestelling van die waterige oplossing mag verder tot gevolg hê dat die oplosbaarheid van die metaalagtige spesie verder verhoog mag word. Die gevolg van bogenoemde reaksies is dat die waterige oplossing ionies sterk gekonsentreerd kan word soos meer en meer spesies aanvanklik teenswoordig op die hars migreer na die oplossing. Die ioniese verandering van die waterige oplossing van 'n suiwer waterige fase tot 'n ionies sterk gekonsentreerde oplossing vind plaas tydens die oplos van erste in 'n hars-inpulp (HIP) oplossing. Die nuwe ioniese aktiwiteit in die oplossing kan die oplosbaarheid van die vaste stof drasties verander. Die volledige oplossing van 'n bepaalde kwantiteit van die vaste stof kan bereik word deur die genoegsame toevoeging van 'n geskikte hars tot die waterige oplossing wat die vaste stofbevat. Die gelyktydige oplossing en absorpsie van die metaalagtige vastestowwe vanuit waterige oplossings met behulp van ioon-uitruilings harse is eksperimenteel getoets vir die doeleindes van hierdie werkstuk. Verskeie interaksies wat op molekulêre vlak in die pulp plaasvind asook die adsorpsie proses van die spesies vanuit die waterige oplossing op die harse word bespreek en gemodelleer. Wiskundige modelle wat die termodinamika van die verskillende fases wiskundig verteenwoordig is ontwikkel vanaf bestaande termodinamiese beginsels. Die drie verskillende fases wat in ag geneem is, is die waterige fase met opgeloste metaal spesies, die vaste stof fase wat as die erts in bostaande paragrawe beskryf is en die ioon-uitruilings fase wat 'n komplekse vastestof en water fase gekombineerd is. Die doel van die werkstuk is om die basis te skep vir die ontwikkeling van modelle wat gebruik kan word om die herwinning van skaars-aarde mertale vanuit lae oplosbare erstse te modelleer en beskryf. 'n Tipiese industriële voorbeeld is die herwinning van skaars-aarde metale van lae-graadse kalkagtige erste deur gebruik te maak van perkolerende logings reaksies wat geduring die vastestof / vloeistof ewewig versteur. Die konsentrasie van die skaars-aarde metale in hierde erts gesteentes kan wissel vanaf so laag as 0.05% tot 0.3% per massa. Hierdie konsentrasies is uiters laag gesien vanuit enige industriële herwinnings proses oogpunt.

Thesis (PhD)--Stellenbosch University, 1992. / ENGLISH ABSTRACT: The dissolution of gold from refractory ores is a complex kinetic problem involving a number of chemical, mass transport and mineralogical factors. In most Witwatersrand ores in South Africa more than 97 % of the gold is dissolved in cyanide medium after a residence time of about 16 hours in pachuca tanks. This high percentage may be the reason why so little fundamental research has been done into the mechanism and kinetics of the leaching process. With the increasingly lower grades of ore mined, the introduction of backfill mining, and the reduction of profit margins, it has become imperative to increase the efficiency of gold dissolution. The effects of the chemistry and particle size on the dissolution of gold in each sample of ore were studied in detail. The emphasis in this study is on the effect of the leaching behaviour of various ore constituents on the rate of gold dissolution. Interferences with the leaching of gold in contact with other minerals or metals could be attributed to the galvanic interaction (electrical conductivity) between the gold and the mineral and to the formation of a surface film on the gold surface. Sulphide minerals and their oxidation products cause the largest decrease in gold dissolution rate. Galena enhances the rate of gold dissolution owing to dissolved Pb(II)-ions. Gold in contact with conductive minerals passivates as a result of the enhanced magnitude of the cathodic cu1Tent. In all experiments the rotating disc of gold passivated so that the rate of dissolution was much slower than that predicted by a mass-transport limiting model. The various films that form on the surface of the gold and associated minerals, as well as the galvanic interaction, depend largely on the pretreatment of the ore. Pre-elimination of host minerals from the gold bearing ore increases the dissolution rate of gold, and explains the kinetics of reaction on the gold surface to a large extent. The selective destruction of the various minerals with oxidative acid leaches destroys and/or decomposes certain minerals which may form films on the gold surface by precipitation. The chemical composition of these films and precipitates depends on the mineralogy of the sample. These films may be oxides, sulphides, carbonates and cyanide complexes. The complexes can be destroyed, depending on the nature of the film, by interstage dilute acid and/or cyanide washes in an agitated vessel. The destruction of the films exposes the gold surface for cyanidation. A simple distribution function similar to the King liberation model is proposed and tested to describe the dissolution step in the multi-step leaching mechanism. For the King model, good agreement is shown with experimental results. For the liberation results obtained by leaching in this study, the trend is co1Tect, but calibration is required for a close fit. A potentially important use for the liberation model by leaching is to predict the leachable or free gold in an ore from the free gold in the complete sample. This approach for studying the leaching behaviour of different gold bearing minerals has provided reasons why some ores leach better than others. / AFRIKAANSE OPSOMMING: Die loging van goud vanuit weerbarstige ertse is 'n komplekse kinetiese probleem wat verskeie faktore soos massa-oordrag, chemiese aspekte en mineralogiese ingeweefdheid insluit. Goud ekstraksies so hoog as 97 % in sianied oplossings in Pachuca reaktore na ongeveer 16 uur logingstyd word behaal in die meeste Witwatersrand ertse in Suid-Afrika. Hierdie hoë ekstraksies mag dalk die rede wees vir die min fundamentele navorsing oor die ekstraksie van goud vanuit minerale in 'n spesifieke erts. Die dalende erts grade, die verlaging van winsgrense en die terugplaas van geloogde erts in die myn noodsaak verbeterde goud ekstraksie. Verkeie faktore nl., chemie, diffusie, partikelgrootte en oplosbaarheid van goud in elke monster erts is in hierdie studie ondersoek. Die sentrale tema was om die logingsgedrag van goud vanuit verskeie minerale in 'n erts te bepaal. Galvaniese interaksie (hou verband met elektriese geleidingsvermoeë) en film vorming is die belangrikste faktore wat die loging van goud in kontak met minerale nadelig beïnvloed. Sulfied minerale en hul oksidasie produkte speel die grootste rol in die verlaging van die tempo van goudloging. Galena verhoog die tempo van goudloging as gevolg van die Pb (II)- ione in oplossing. Goud in kontak met geleidende minerale passiveer as gevolg van die verhoogde katodiese stroomdigtheid. In alle eksperimente met die roterende skyf (goudskyf) apparaat, passiveer die goudskyf in so 'n mate dat die logingstempo baie stadiger is as wat voorspel word met die massa-oordrags model. Die onderskeie films wat vorm op die goud- en geassosieerde minerale se oppervlaktes, asook die galvaniese interaksies, is 'n funksie van die voorafbehandeling van die erts. Die selektiewe eliminering van minerale vanuit 'n gouddraende erts verhoog die tempo van goudloging drasties en dit beskryf die kinetika van goudloging op die goudoppervlak in 'n groot mate. Die selektiewe eliminering van minerale deur gebruik te maak van oksiderende suurlogings, vernietig sekere van die minerale wat films op die goudoppervlakte kan veroorsaak deur middel van presipitasie. Die chemiese samestelling van hierdie films hang af van die mineralogie van die monster. Dit bestaan meestal uit oksiedes, sulfiedes, karbonate en sianiedkomplekse en hulle kan vernietig word deur middel van inter-stadia verdunde suur-en/of sianied wasse. 'n Eenvoudige distribusiefunksie, soortgelyk aan die King bevrydingsmodel word voorgestel en eksperimenteel getoets om die logingstap in die multi-stadia logingsmeganisme te beskryf. Vir bevryding deur loging, is die neiging van King se model korrek, maar kalibrasie word benodig vir goeie passing. 'n Potensiele gebruik van die aangepaste model is om vrye of loogbare goud in 'n spesi fieke partikel grootte fraksie van 'n erts te voorspel as die vry goud in die totale fraksie bekend is. Die resultate uit hierdie studie kan gebruik word om die logingsgedrag van gouddraende minerale te voorspel en te beskryf, en dus veduidelik hoekom goud uit sekere ertse beter loog as uit ander.

Thesis (MScIng)--University of Stellenbosch, 2003. / ENGLISH ABSTRACT: Physical systems encountered in process engineering are invariably ill-defined, multivariate, and exhibit complex nonlinear dynamical behaviour. The increasing demands for better process efficiency and high product quality have led to the development and implementation of advanced control strategies in process plants. These modern control strategies are based on the use of a mathematical model defined for the process. Traditionally, linear models have been used to approximate the dynamics of processes whereas most processes are governed by nonlinear mechanisms. Since linear systems theory is well-established whereas nonlinear systems theory is not, recent developments in nonlinear dynamical systems theory present opportunities for improved approaches in modelling these process systems. It is now known that a nonlinear description of a process can be obtained from using time-delayed copies reconstructed from measurements taken from the process. Due to low signal to noise ratios associated with measured data it is logical to exploit redundant information in multivariate time signals taken from the systems in reconstructing the underlying dynamics. This study investigated the extension of univariate nonlinear time series analysis to the situation where multivariate measurements are available. Using simulated data from a coupled continuously stirred tank reactor and measured data from a flotation process system, the comparative advantages of using multivariate and univariate state space reconstructions were investigated. With respect to detection of nonlinearity multivariate surrogate analysis were found to give potentially robust results because of preservation of cross-correlations among components in the surrogate data. Multivariate local linear models showed a deterministic structure in both small and large neighbourhood sizes whereas for scalar embeddings determinism was defined only in smaller neighbourhood sizes. Non-uniform multivariate embeddings gave local linear models that resembled models from a trivial reconstruction of the original state space variables. With regard to global nonlinear modelling, multivariate embeddings gave models with better predictability irrespective of the model class used. Further improvements in the performance of models were obtained for multivariate non-uniform embeddings. A relatively new statistical learning algorithm, the least-squares support vector machine (LSSVM), was evaluated using multilayer perceptrons (MLP) as a benchmark in modelling nonlinear time series using simulated and plant data. It was observed that in the absence of autocorrelations in the variables and sparse data LSSVMs performed better than MLPs. Simulation of trained models gave consistent results for the LSSVMs, which was not the case for MLPs. However, the computational costs incurred in training the LSSVM model was significantly higher than for MLPs. LSSVMs were found to be insensitive to dimensionality reduction methods whereas the performance of MLPs degraded with increasing complexity of the dimension reduction method. No relative merits were found for using complex subspace dimension reduction methods for the data used. No general conclusions could be drawn with respect to the relative superiority of one class of models method over the other. Spatiotemporal structures are routinely observed in many chemical systems, such as reactive-diffusion and other pattern forming systems. We investigated the modelling of spatiotemporal time series using the coupled logistic map lattice as a case study. It was found that including both spatial and temporal information improved the performance of the fitted models. However, the superiority of spatiotemporal embeddings over individual time series was found to be defined for certain choices of the spatial and temporal embedding parameters. / AFRIKAANSE OPSOMMING: Fisiese stelsels wat in prosesingenieurswese voorkom is dikwels nie goed gedefinieer nie, multiveranderlik en vertoon komplekse nie-lineˆere gedrag. Toenemende vereistes vir ho¨e prosesdoeltreffendheid en produkgehalte het gelei tot die ontwikkeling en implementering van gevorderde beheerstrategie¨e vir prosesaanlegte. Hierdie morderne beheerstrategie¨e is gebaseer op die gebruik van wiskundige prosesmodelle. Lineˆere modelle word gewoonlik ontwikkel, al is die onderliggende prosesmeganismes in die algemeen nie-lineˆere, aangesien lineˆere stetselteorie goed gevestig is, en nie-line¨ere stelselteorie nie. Onlangse verwikkelinge in die teorie van nie-lineˆeredinamiese stelsels bied egter geleenthede vir verbeterde modellering van prosesstelsels. Dit is bekend dat ‘n nie-lineˆere beskrywing van ‘n progses verkry kan word deur tydvertraagde kopie¨e van metings van die prosesse te rekonstrueer. Met die lae seintot- geraasverhoudings wat met gemete data geassosieer word, is dit logies om die oortollige informasie in meerveranderlike seine te benut tydens die rekonstruksie van die onderliggende prosesdinamika. In die tesis is die uitbreiding van enkel-veranderlike nie-lineˆere tydreeksontleding na meer-veranderlike stelsels ondersoek. Met data van twee aaneengeskakelde gesimuleerde geroerde tenkreaktore en werklike data van ‘n flottasieproses, is die meriete van enkel- en meerveranderlike rekonstruksies van toestandruimtes ondersoek. Meerveranderlike surrogaatdata-ontleding het nie-lineariteite in die data op ‘n meer robuuste wyse ge¨ıdentifiseer, a.g.v. die behoud van kruis-korrelasies in die komponente van die data. Meerveranderlike lokale lineˆere modelle het ‘n deterministiese struktuur in beide klein en groot naasliggende omgewings ge¨ıdentifiseer, terwyl enkelveranderlike metodes dit slegs vir klein naasliggende omgewings kon doen. Nie-uniforme meerveranderlike inbeddings het lokale lineˆere modelle gegenereer wat soos globale modelle afkomstig van triviale rekonstruksies van die data gelyk het. M.b.t globale nie-lineˆere modellering, het meerveranderlike inbedding deurgaans beter modelle opgelewer. Verdere verbetering in die prestasie van modelle kon verkry word d.m.v. meerveranderlike nie-uniforme inbedding. ‘n Relatief nuwe statistiese algoritme, die kleinste-kwadrate-steunvektormasjien (KKSVM) is ge¨evalueer teenoor multilaag-perseptrons (MLP) as ‘n standaard vir die modellering van nie-lineˆere tydreekse, deur gebruik te maak van gesimuleerde en werklike aanlegdata. Daar is gevind dat die KKSVM beter presteer het as die MLPs wanneer die opeenvolgende waarnemings swak gekorreleer en min was relatief tot die aantal veranderlikes. Die KKSVMs het beduidend langer geneem as die MLPs om te ontwikkel. Hulle was ook minder sensitief vir die metodes wat gevolg is om die dimensionaliteit van die data te verlaag, anders as die MLPs. Ook is gevind dat meer komplekse metodes tot die verlaging van die dimensionaliteit weinig nut gehad het. Geen algemene gevolgtrekkings kan egter gemaak word m.b.t die verskillende modelle nie. Ruimtelik-temporale strukture word algemeen waargeneem in baie chemiese stelsels, soos reaktiewe diffusie e.a. patroonvormende sisteme. Die modellering van ruimtelik-temporale stelsels is bestudeer aan die hand van ‘n gekoppelde logistiese projeksierooster. Insluiting van beide die ruimtelike en temporale inligting het tot beduidend beter modelle gelei, solank as wat di´e inligting op die regte wyse ontsluit is.

Thesis (MScEng)--University of Stellenbosch, 2002. / ENGLISH ABSTRACT: Metallurgical processes are often high dimensional and non-linear making them difficult to understand, model and control. Whereas the human eye has extensively been used in discerning temporal patterns in historical process data from these processes, the systematic study of such data has only recently come to the forefront. This resulted predominantly from the inadequacy of previously used linear techniques and the computational power required when analysing the non-linear dynamics underlying these systems. Furthermore, owing to the recent progress made with regard to the identification of non-linear systems and the increased availability of computational power, the application of non-linear modelling techniques for the development of neural network models to be used in advanced control systems has become a potential alternative to operator experience. The objective of this study was the development ofa non-linear, dynamic model of an autogenous mill for use in an advanced control system. This was accomplished through system identification, modelling and prediction, and application to control. For system identification, the attractor was reconstructed based on Taken's theorem making use of both the Method Of Delays and singular spectrum analysis. Modelling consisted of the development of multi-layer perceptron neural network, radial basis function neural network, and support vector machine models for the prediction of the power drawn by an autogenous mill. The best model was subsequently selected and validated through its application to control. This was accomplished by means of developing a neurocontroller, which was tested under simulation. Initial inspection of the process data to be modelled indicated that it contained a considerable amount noise. However, using the method of surrogate data, it was found that the time series representing the power drawn by the autogenous mill clearly exhibited deterministic character, making it suitable for predictive modelling. It was subsequently found that, when using the data for attractor reconstruction, a connection existed between the embedding strategy used, the quality of the reconstructed attractor, and the quality of the resulting model. Owing to the high degree of noise in the data it was found that the singular spectrum analysis embeddings resulted in better quality reconstructed attractors that covered a larger part of the state space when compared to the method of delays embeddings; the data embedded using singular spectrum analysis also resulting in the development of better quality models. From a modelling perspective it was found that the multi-layer perceptron neural network models generally performed the best; a multi-layer perceptron neural network model having an appropriately embedded multi-dimensional input space outperforming all the other developed models with regard to free-run prediction success. However, none of the non-linear models performed significantly better than the ARX model with regard to one-step prediction results (based on the R2 statistic); the one-step predictions having a prediction interval of 30 seconds. In general the best model was a multi-layer perceptron neural network model having an input space consisting of the FAG mill power (XI), the FAG mill load (X2), the FAG mill coarse ore feed rate (X3), the FAG mill fine ore feed rate (X4), the FAG mill inlet water flow rate (X7) and the FAG mill discharge flow rates (X9, XIO). Since the accuracy of any neural network model is highly dependent on its training data, a process model diagnostic system was developed to accompany the process model. Linear principal component analysis was used for this purposes and the resulting diagnostic system was successfully used for data validation. One of the models developed during this research was also successfully used for the development of a neurocontroller, proving its possible use in an advanced control system. / AFRIKAANSE OPSOMMING: Metallurgiese prosesse is gewoonlik hoogs dimensioneel en nie-lineêr, wat dit moeilik maak om te verstaan, modelleer, en te beheer. Alhoewel die menslike oog alreeds wyd gebruik word om temporale patrone in historiese proses data te onderskei, het die sistematiese studie van hierdie tipe data eers onlangs na vore gekom. Dit is hoofsaaklik na aanleiding van die onvoldoende resultate wat verkry is deur van voorafgaande lineêre tegnieke gebruik te maak, asook die beperkende berekenings vermoë wat beskikbaar was vir analise van onderliggend nie-lineêre dinamiese stelsels. 'n Verder bydraende faktor is die onlangse vordering wat gemaak is met betrekking tot die identifikasie van nie-lineêre stelsels en die toename in beskikbaarheid van rekenaar-vermoë. Die toepassing van nie-lineêre modellerings tegnieke vir die ontwikkeling van neurale netwerke om gebruik te word in gevorderde beheerstelsels, het 'n potensiële alternatief geword tot operateur ondervinding. Die doelwit van hierdie studie was die ontwikkeling van 'n gevorderde beheerstelsel vir 'n outogene meul gebaseer op 'n nie-lineêre, dinamiese model. Dit is bereik deur middel van stelsel-identifikasie, modellering en voorspelling, en laastens implementering van die beheerstelsel. Vir stelsel-identifikasie is die attraktor van die stelsel bepaal soos gebaseer op Taken se teorema deur gebruik te maak van beide die metode van vertraging en enkelvoudige spektrum analise. Modellering van die stelsel vir die voorspelling van krag-verbruik deur die outogene meul het bestaan uit die ontwikkeling van multilaag-perseptron-neurale netwerke, radiaalbasisfunksie-neurale netwerke, en steunvektor-masjien-modelle. Die beste model is daarna gekies vir validasie deur middel van toepassing vir beheer. Dit is bereik deur 'n neurobeheerder te ontwikkel en te toets deur middel van simulasie. Die aanvanklike inspeksie van proses data wat gebruik sou word vir modellering het egter getoon dat die data 'n aansienlike hoeveelheid geraas bevat. Nietemin, deur die gebruik van 'n surrogaat-data-metode, is dit bevind dat die tyd-reeks wat die krag verbruik van die outogene meul beskryf, duidelik deterministiese karakter toon en dat dit dus wenslik is om 'n nie-lineêre voorspellings-model, soos 'n neurale netwerk te gruik. Gevolglik is gevind dat, wanneer die data vir attraktor hersamestelling gebruik word, 'n verband bestaan tussen die ontvouing-strategie wat gebruik word, die kwaliteit van die gerekonstrueerde attraktor, en die kwaliteit van die daaropvolgende model. As gevolg van die geraas in die data is gevind dat die ontvouing gebaseer op enkelvoudige spektrum analise 'n beter kwaliteit attraktor hersamestelling lewer. So ook is gevind dat 'n groter deel van die toestandruimte gedek word in vergelyking met die metode van vertraging-ontvouing. Deur gebruik te maak van enkelvoudige spektrum-analise, het die dataontvouing ook beter kwaliteit modelle opgelewer. Vanuit 'n modellerings-perspektief is gevind dat die multilaag-perseptron-neurale netwerk-modelle in die algemeen die beste gevaar het. 'n Multilaag-perseptronneurale netwerk met 'n gepaste ontvoude multidimensionele invoer-spasie het die beste gevaar van al die ontwikkelde modelle met betrekking tot vryloopvoorspellings. Geen van die nie-lineêre modelle het egter beduidend (op 'n R2 basis) beter gevaar as die ARX model wanneer daar na die eenstap-voorspellings (oor 'n 30 sekonde interval) gekyk word nie. Die multilaag-perseptron-neurale netwerk met 'n invoer-spasie bestaande uit die meul krag-verbruik (XI), die meullading (X2), die meul growwe-erts voertempo (X3), die meul fyn-erts voertemp ('4), die meul inlaat-water vloeitempo (X7) en die meul uitlaat vloeitempo's (X9, XIO) het in die algemeen die beste gevaar. Aangesien die akkuraatheid van emge neurale netwerk afhanklik is van die data waarmee dit aanvanklik opgestel is, is 'n diagnostiese proses modelontwikkel om die proses-model te vergesel. Lineêre hoofkomponent analise is vir hierdie doel aangewend en die gevolglike diagnostiese stelsel is suksesvol aangewend vir datavalidasie. Een van die modelle ontwikkel gedurende hierdie navorsing is ook suksesvol gebruik vir die ontwikkeling van 'n neurobeheerder wat dien as bewys dat die model goed gebruik kan word in 'n gevorderde beheerstelsel.

Thesis (PhD)--University of Stellenbosch, 2004. / 388 leaves printed on single pages, preliminary pages i- xv and numbered pages 1-371. Includes bibliography, list of tables and figures. / Digitized at 330 dpi black and white and 330 dpi color PDF format (OCR), using KODAK i 1220 PLUS scanner. / ENGLISH ABSTRACT: Bath type furnaces have become an established technology for the intensive smelting, converting and refining of primary and secondary raw materials. Since these furnaces normally have large inventories, long time constants and complex metallurgies, a dynamic model-based prediction strategy is the only feasible approach to operator decision support and process control. This dissertation presents a semi-empirical approach to the stochastic modelling of bath-type pyrometallurgical reactors, which leads to a generic model type called the Equilib-ARMAX model. The modelling approach is applied to three case studies: • A nickel-copper matte converting operation using a submerged lance injection reactor • A chromite smelting operation to produce high carbon ferrochrome using a direct current (DC) plasma smelting furnace • An ilmenite smelting operation to produce high titania slag and pig iron, using a direct current (DC) plasma smelting furnace. In each case, the industrial operations were analysed with regard to the practical and technological constraints which influence the type and quality of the process data. The fundamental process phenomena associated with each operation have been analysed to ascertain which fundamental variables should be included within the overall semi-empirical approach, without sacrificing model transparency, simplicity, accuracy and calculation time. It was considered that an overly complex model would be inappropriate given that data from industrial smelting operations show significant random variance. The thermochemistry and phase equilibria associated with each operation are discussed in detail, as they become the fundamental backbone of the semi-empirical models. The equilibria have been modelled with software that uses non-ideal solutions models and Gibbs free energy minimisation to predict the phase and chemical equilibria that could be expected for a given feed recipe and operating temperature. As the thermodynamic modelling software is not stable within an industrial environment, an artificial intelligent mapping technique has been developed to map process inputs to equilibrium outputs. A multi-layer perceptron neural network has been used as the convenient mapping method to represent equilibrium. The neural networks were trained using tens of thousands of feed recipes, where the feed component ratios were varied based on a 3N factorial design. The amounts and chemistries of all equilibrium phases could be calculated with high accuracies (R2 > 0.95) in all cases. Further stochastic analysis and modelling require additional information about the property distributions associated with each measurement. The homogeneities of the furnace products (slag, alloy and flue dust) critically influence the level of confidence that one can associate with plant measurements. The homogeneities were characterised for the DC plasma arc furnaces and they were benchmarked against a submerged arc furnace. It was found that the homogeneity varied per element, with silicon and sulphur tending to show highest variations in the alloy melts. The observation that the variation in these two elements are both high can partially be attributed to the fact that SiS evaporates from the bath surface, especially in regions close to the arc attachment zone. A significant negative correlation was found between the relative standard deviation per tap (using silicon) and the degree of superheat / subcooling of the alloy, indicating that the homogeneity can be strongly influenced by the changes in rheology due to subcooling below the liquidus (which leads to the precipitation of solid phases and increases the observed melt viscosity). Mixedness or homogeneity and data uncertainty are therefore inseparably linked. The relative standard deviations associated with the homogeneity characterisation, as well as known sampling and assaying variances were used to develop reconciled material balances based on measured plant data. Material balance closure was therefore obtained within the inherent uncertainties of the plant data. Biases in the plant data were identified simultaneously with data reconciliation. Moreover, it was shown using Fast Fourier Power Spectra and statespace analysis that the data reconciliation was a good low-pass filter, as it extracted the major process trends components in the noisy data and it also improved the overall dynamic behaviour characteristics of the data. Finally systems identification techniques were used to develop dynamic transfer function models that were linear in the parameters to be estimated. These systems models were based on the reconciled plant data and equilibrium predictions. The final systems models are therefore equilibrium-autoregressive-moving-average models with exogenous variables (Equilib-ARMAX). The model parameters can be estimated recursively using a simple least squares method. The final models could dynamically predict the metallurgy of the subsequent tap 4-6 hours in advance, based on a given suite of set-points, within the inherent accuracy of the data. These models may be used to suggest the optimal operating conditions through an operator guidance system, or more simply, the models are simple enough to be used in a spreadsheet on a manager's desk. / AFRIKAANSE OPSOMMING: Bad-tipe oonde is reeds 'n gevestigde tegnologie wat algemeen gebruik word vir die intensiewe smelting, omsetting en raffinering van primere en sekondere roumateriale. Aangesien hierdie oonde normaalweg groot inventarisse, lang tydkonstantes en komplekse metallurgiee het, is dinamiese, modelgebaseerde voorspelling die enigste uitvoerbare benadering tot operateur besluitnemingsteunstelsels en prosesbeheer. Hierdie proefskrif stel 'n nuwe generiese, semi-empiriese benadering voor om die bad-tipe oonde stogasties te modelleer en lei tot die sogenaamde Equilib-ARMAX model. Die modelleringsbenadering word geevalueer deur drie gevallestudies: • 'n Nikkel-koper swawelsteen omsettingsproses in 'n dompel-Ians inspuit reaktor • 'n Chromiet smeltingsproses om hoe-koolstof ferrochroom te produseer in 'n gelykstroom (GS) plasmaboogoond • 'n Ilmeniet smeltingsproses om hoe titania slak en ruyster te produseer in 'n gelykstroom (GS) plasmaboogoond. In elke geval is die industriele prosesse ontleed met betrekking tot die praktiese en tegnologiese beperkings wat die tipe en die gehalte van die prosesdata beinvloed. Die fundamentele prosesgedrag van elke proses is ontleed om te bepaal welke fundamentele veranderlikes ingesluit moet word in die semi-empiriese benadering, sonder om model deursigtigheid, eenvoud, akkuraatheid en berekeningstyd in te boet. Die ontwikkeling van oor-komplekse modelle is beskou as ongepas, gegewe dat die data van industriele smeltingsprosesse beduidende onsekerhede toon. Die termochemiese en fase-ewewigte geassosieer met elke proses word breedvoerig bespreek, aangesien dit die fundamente1e grondslag van die semi-empiriese modelle verskaf. Die ewewigte is gemodelleer met rekenaar simulasie-programmatuur wat nie-ideale oplossingsmodelle en Gibbs vrye-energie minimering gebruik om die fase en chemiese ewewigte, wat verwag kan word vir 'n gegewe toevoerresep en bedryfstemperatuur, te voorspel. Aangesien termodinamiese modelleringsprogrammatuur normaalweg nie stabiele gedrag toon in 'n intydse industriele omgewing nie, word kunsmatig intelligente projeksietegnieke gebruik om prosesinsette te projekteer na die ekwavilente ewewigsvoorspellings. 'n Multilaag perseptron neurale netwerk is gebruik as 'n eenvoudige metode om hierdie ewewigsprojeksies voor te stel. Die neurale netwerke is afgerig deur van tienduisende toevoer resepte gebruik te maak. Die verhoudings van die komponente in die voer is gewissel gebaseer op 'n 3N faktoriaalontwerp. Die hoeveelhede en samestelling van al die ewewigsfases kon in alle gevalle bereken word met hoe akkuraatheid (R2 > 0.95). Verdere stogastiese analise en modellering is slegs moontlik met kennis oor die eienskapsverspreidings geassosieer met elke komponent. Die homogeniteite van die oondprodukte (slak, legering en vlieg-as) bepaal, tot 'n groot mate, die betroubaarheidsvlak van die aanlegmetings. Homogeniteite is gekarakteriseer vir die GS-plasmaboogoonde en is vergelyk met die homogeniteite wat in dompelboogoonde gevind word. Die homogeniteite het gevarieer per komponent. Silikon en swawel neig om die grootste ruimtelike variasies te toon in die legerings wat bestudeer is. 'n Beduidende negatiewe korrelasie is gevind tussen die relatiewe standaardafwyking per tap (gebaseer op silikon) en die graad van superverhitting / onderverkoeling van die legering. Dit dui aan dat die homogeniteit sterk beinvloed word deur veranderinge in die smelt reologie. Vermenging, reologie, homogeniteit en data onsekerheid (integriteit) is daarom ten nouste gekoppel. Die relatiewe standaardafwykings geassosieer met die homogeniteitsbepaling, asook die monsternemings- en ontledingsvariansies, is gebruik om die aanlegdata te rekonsilieer onderhewig aan die behoud van die komponent en totale stroom massabalanse. Die massabalanse is dus gesluit deur aanpassings aan die metings te maak binne die inherente onsekerhede in die data. Sistematiese foute in die data is gelyktydig met die rekonsiliasie geidentifiseer. Verder is deur diskrete Fourier energiespektra en toestand-ruimte analises getoon dat massabalans-rekonsiliasie dien as 'n goeie seinfilter om hoe-frekwensie geraas te verminder en tergelykertyd die dinamiese gedragseienskappe van die data te verbeter. Stelsel-identifikasietegnieke is gebruik om dinamiese oordragsfunksiemodelle te ontwikkel wat linieer is met betrekking tot die modelparameters. Hierdie stelselmodelle is gebaseer op gerekonsilieerde data, eksogene prosesdata en ewewigsberekeninge, en word vervolgens ewewigs-autoregressiewe-lopende-gemiddelde modelle met eksogene veranderlikes (Equilib ARMAX) genoem. Die modelparameters kan deur gewone kleinste-kwadrate metodes beraam word. Die finale modelle kan die metallurgie van toekomstige tappe 4-6 uur voortydig voorspel, gebaseer op beskikbare stelpunte en binne die inherente presisie van die data. Hierdie modelle kan gebruik word om optimale bedryfskondisies vir prosesbeheer te identifiseer, en is eenvoudig genoeg om in sigbladformaat op 'n aanlegbetuurder se rekenaar gebruik te kan word.