Thesis (Ph. D.)--University of Washington, 1995. / Vita. Includes bibliographical references (leaves [243]-247).

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Supervisor: S. Joe Qin. Vita. Includes bibliographical references.

The research expresses the PV potential in the UK and India by examining the performance and the cost of domestic grid-connected PV systems. Further, crystalline systems and two thin film system technologies (amorphous silicon and copper indium gallium diselenide), which are installed at a site in India, are examined in order to validate the simulated outputs compared to the systems’ field performance and to compare the behaviour of the different module technologies under the harsh climatic conditions of India. The aim of this study was to evaluate the PV system performance and to develop methods for expressing the PV systems lifetime energy generation and the levelized cost of energy (LCOE) in both countries as a function of location or other influencing parameters. In the beginning the study presents the UK and India climates and the solar databases with their limitations. Further, it discusses the simulation outputs and the annual energy predictions for the UK and India. It also presents the UK and India PV markets and their policies and the LCOE equation, which was formed, and the methodology used for the LCOE calculations. It discusses the LCOE results and presents indicative lifetime CO2 (carbon dioxide) emissions savings for the researched locations. Continuing, this study presents the model formed for the lifetime energy prediction and annual energy assessment based on PV system degradation and uncertainty factors. Finally, it summarises the technical and economic outputs of this research, by expressing the PV potentials in the UK and India. Even for these two countries, which are significantly different in respect to their solar resource, the PV systems may produce similar amounts of energy during their lifetime for reasonable assumptions of degradation rates and uncertainty levels. An uncertainty in the energy output makes the economic viability uncertain. Hence, the investor should be aware of the energy prediction risks, especially in investments where a minimum rate of return is specified. The intermediate lifetime energy range is 60,000-70,000 kWh for the UK while is between 70,000-100,000 kWh for India. The cost per kWh of a domestic PV system in India (range: 0.07-0.13 £/kWh) is lower than in the UK (range: 0.11-0.17 £/kWh) by considering only the net PV cost. However, it is more profitable with the current policies to install a domestic PV system in the UK rather than India. This shows that India has to reconsider its incentive policies for the domestic PV system deployment.

Thesis (MScIng)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: As result of the increasingly competitive performance in today’s industrial environment, it has become necessary for production facilities to increase their efficiency. An essential step towards increasing the efficiency of these production facilities is through tighter processes control. Process control is a monitoring and modelling problem, and improvements in these areas will also lead to better process control. Given the difficulties of obtaining theoretical process models, it has become important to identify models from process data. The irregular behaviour of many chemical processes, which do not seem to be inherently stochastic, can be explained by analysing time series data from these systems in terms of their nonlinear dynamics. Since the discovery of time delay embedding for state space analysis of time series, a lot of time has been devoted to the development of techniques to extract information through analysis of the geometrical structure of the attractor underlying the time series. Nearly all of these techniques assume that the dynamical process under question is stationary, i.e. the dynamics of the process did not change during the observation period. The ability to detect dynamic changes in processes, from process data, is crucial to the reliability of these state space techniques. Detecting dynamic changes in processes is also important when using advanced control systems. Process characteristics are always changing, so that model parameters have to be recalibrated, models have to be updated and control settings have to be maintained. More reliable detection of changes in processes will improve the performance and adaptability of process models used in these control systems. This will lead to better automation and enormous cost savings. This work investigates and assesses techniques for detecting dynamical changes in processes, from process data. These measures include the use of multilayer perceptron (MLP) neural networks, nonlinear cross predictions and the correlation dimension statistic.The change detection techniques are evaluated by applying them to three case studies that exhibit (possible) nonstationary behaviour. From the research, it is evident that the performance of process models suffers when there are nonstationarities in the data. This can serve as an indication of changes in the process parameters. The nonlinear cross prediction algorithm gives a better indication of possible nonstationarities in the process data; except for instances where the data series is very short. Exploiting the correlation dimension statistic proved to be the most accurate method of detecting dynamic changes. Apart from positively identifying nonstationary in each of the case studies, it was also able to detect the parameter changes sooner than any other method tested. The way in which this technique is applied, also makes it ideal for online detection of dynamic changes in chemical processes. / AFRIKAANSE OPSOMMING: Dit is belangrik om produksie aanlegte so effektief moontlik te bedryf. Indien nie, staar hulle die moontlikheid van finansiële ondergang in die gesig – veral as gevolg van toenemende mededinging die industrie. Die effektiwiteit van produksie aanlegte kan verhoog word deur verbeterde prosesbeheer. Prosesbeheer is ‘n moniterings en modellerings probleem, en vooruitgang in hierdie areas sal noodwendig ook lei tot beter prosesbeheer. Omdat dit moeilik is om teoretiese proses modelle af te lei, word dit al hoe belangriker om modelle vanuit proses data te identifiseer. Die ongewone optrede van baie chemiese prosesse, wat nie inherent stogasties blyk te wees nie, kan meestal verklaar word deur tydreeks data vanaf hierdie prosesse te analiseer in terme van hul nie-liniêre dinamika. Sedert die ontdekking van tydreeksontvouing vir toestandveranderlike stelsels, is baie tyd daaraan spandeer om tegnieke te ontwikkel wat inligting uit tydreekse kan onttrek deur die onderliggende geometriese struktuur van die attraktor te bestudeer. Byna al hierdie tegnieke aanvaar dat die dinamiese proses stationêr is, m.a.w dat die dinamika van die proses nie verander het tydens die observasie periode nie. Die vermoë om hierdie dinamiese proses veranderinge te kan identifiseer, is daarom baie belangrik. Ook in gevorderde beheerstelsels is vroegtydige identifisering van dinamiese veranderinge in prosesse belangrik. Proses karakteristieke is altyd besig om te verander, sodat model parameters herkalibreer moet word, modelle opgedateer moet word en beheer setpunte onderhou moet word. Meer betroubare tegnieke om veranderinge in prosesse te identifiseer sal die aanpasbaarheid van proses modelle in hierdie beheerstelsels verbeter. Dit sal lei tot beter outomatisering en sodoende lei tot enorme kostebesparings. Hierdie werk ondersoek tegnieke om dinamiese veranderinge in prosesse te identifiseer, deur die analise van proses data. Die tegnieke wat gebruik word sluit die volgende in:multilaag-perseptron neurale netwerke, nie-liniêre kruisvoorspelling statistieke en die korrelasie dimensie statistiek. Die tegnieke is op drie gevallestudies toegepas om te sien of hulle die dinamiese veranderinge in die data kan identifiseer. Vanuit die navorsing is dit duidelik dat proses modelle nadelig beinvloed word deur niestationêre data. Dit kan dien as ‘n indikasie van veranderinge in die proses parameters. Die nie-liniêre kruisvoorspellings algoritme gee ‘n beter indikasie van dinamiese veranderinge in die proses data, behalwe waar die tydreeks baie kort is. Toepassings van die korrelasie dimensie statistiek gee die beste resultate. Hierdie tegniek kon dinamiese veranderinge vinniger as enige ander tegniek identifiseer, en die manier waarop dit gebruik word maak dit ideaal vir die identifisering van dinamiese veranderinge in chemiese prosesse.

Matching networks are widely used to enhance active power transfer when radio frequency generators drive complex loads. The tuning of the network for varying loads typically involves searching for optimum matching conditions. However, improving the matching condition of the network does not necessarily indicate an increase in active power transfer. As an example, a 71 network with three adjustable elements may achieve comparable matches for a variety of elements' settings, each matching triple exhibiting a different transferred active power. Furthermore, the influence of the transmission lines used to connect the matching network to its source and load is rarely taken into account. The purpose of the work is to optimise the power gain of a narrowband matching sys-tem in the frequency range of 1.8 — 30 MHz. The system consists of a source, a match-ing network, a load and two interconnecting lines whose characteristic impedance is complex. The optimisation process involves optimum choice of the transmission lines' lengths and development of a matching strategy. Its objective is to ensure automatic and continuous adjustment of the matching network for optimum ac¬tive power transfer to its load while matching the network's input impedance to a resistive source. The network topologies employed are limited to the most common 71 and T networks consisting of two variable capacitors and one central inductor. Losses are assumed to be mainly caused by the inductor. An appropriate simple and synthetic model of the losses is proposed which is suitable for active power transfer optimisation. The model is validated against losses of inductors derived by different works. After choosing a proper network parametrisation and exact inclusion of the losses during network design, the losses of a network terminated by a resistance and de¬signed to match (exactly) a source resistance at its input are derived. Then its power gain is optimised by a proper choice of the network's parameter and the impact of changing the purely resistive termination to impedances exhibiting capacitive or in¬ductive imaginary parts is considered. An explicit solution is calculated for networks with a constant Q factor central inductor, its differences from the approximate solu¬tion (network elements designed as if the network would be lossless) are considered. Example diagrams are given illustrating those differences and power gain contour Smith charts are drawn for typical ranges of the L, iv, and T networks' elements. Combining the results of the different approaches yields an optimum matching strat¬egy. The losses of transmission lines connecting source and network of load and network are determined, where the lines' complex characteristic impedance is taken into account. Those losses are included in a power gain optimisation of the complete matching system. Finally, an experimental setup is designed under which the matching strategy of the network is tested and validated.

This thesis presents the findings of an investigation into hybrid mode feed horns for use in the next generation of reflector antennas for satellite communications at Ka- band. Within the thesis, general field theory is developed and subsequently applied to specific horn-types in an effort to understand and explore the limits of the bandwidth over which they can offer suitable radiation characteristics. Studies into the use of both corrugated and dielectric-loaded horns identify a shortfall in their performance, particularly in the context as feeds for elliptical reflector antennas at Ka-band, as a consequence of the sizeable frequency separation between the Transmit and Receive functions. The need to operate at two widely separated bands, with little concern for the performance at all frequencies in between, affords the opportunity to take advantage of two exclusive mechanisms to independently optimise the performance at two sub- bands, corresponding to the Transmit and Receive functions. The 'dual-band' concept is explored by extending the field theory developed earlier in the thesis, this being applied to a corrugated structure with secondary mechanism that takes effect once the performance as a consequence of the corrugations themselves begins to degrade. The theory is tested by way of a practical investigation comparing the measured performance of different horn types, including a novel horn borne out of the dual- band concept described above. This led to the need to develop, construct and evaluate a suitable anechoic chamber, the work associated with this also being included in the thesis as an appendix. The results are reviewed in the context of the Ka-band application against both RF and practical design goals with the conclusion that the novel dual-band horn offers superior performance with respect to the state-of-the-art.

This research is in the area of Thermal Energy Conversion, more specifically, in the conversion of solar thermal energy. This form of renewable energy can be utilised for production of power by using thermo-mechanical conversion systems – Stirling engines. The advantage of such the systems is in their capability to work on low and high temperature differences which is created by the concentrated solar radiation. To design and build efficient, high performance engines in a feasible period of time it is necessary to develop advanced mathematical models based on thermodynamic analysis which accurately describe heat and mass transfer processes taking place inside machines. The aim of this work was to develop such models, evaluate their accuracy by calibrating them against published and available experimental data and against more advanced three-dimensional Computational Fluid Dynamics models. The refined mathematical models then were coupled to Genetic Algorithm optimisation codes to find a rational set of engine’s design parameters which would ensure the high performance of machines. The validation of the developed Stirling engine models demonstrated that there was a good agreement between numerical results and published experimental data. The new set of design parameters of the engine obtained from the optimisation procedure provides further enhancement of the engine performance. The mathematical modelling and design approaches developed in this study with the use of optimization procedures can be successfully applied in practice for creation of more efficient and advanced Stirling engines for power production.

Biomass is characterized by highly variable properties. It can be converted to more valuable energy forms and products through a variety of conversion processes. This thesis focuses on addressing several important issues related to combustion and pulping. Experimental investigations were carried out on a biomass-fired industrial fluidized-bed boiler. The observed combustion asymmetry was explained by an imbalance in the fuel feed. Increased levels of carbon monoxide were detected close to boiler walls which contribute significantly to the risk of wall corrosion. Moreover, extensive literature analysis showed that near-infrared spectroscopy (NIRS) has a great potential to provide property information for heterogeneous feedstocks or products, and to directly monitor processes producing/processing biofuels in real-time. The developed NIRS-based models were able to predict characteristics such as heating value, ash content and glass content. A study focusing on the influence of different spectra acquisition parameters on lignin quantification was carried out. Spectral data acquired on moving woodchips were found to increase the representativeness of the spectral measurements leading to improvements in model performance. The present thesis demonstrates the potential of developing NIRS-based soft-sensors for characterization of biomass properties. The on-line installation of such sensors in an industrial setting can enable feed-forward process control, diagnostics and optimization.

Slagg har historiskt använts som konstruktionsmaterial i olika applikationer. Alla typer av slagg passar inte på grund av otillräckliga egenskaper. Vid produktion av höglegerat rostfritt stål så är slaggen mycket kalkrik, vilket leder till sönderfall på grund av absorption av vatten. Vissa stålsorter hos Sandvik tillverkas med ett tvåslaggsförfarande där en första reduceringsslagg först används för att sedan ersättas av en raffineringsslagg. Denna rapport behandlar förändringar i slaggsammansättning för att förbättra slaggens egenskaper gällande volymstabilitet efter deponering. I synnerhet så behandlas volymstabilitet av reduceringsslagg och om möjligheterfinns att kombinera bra stålproduktion med volymstabil slagg.Projektet har syftat till att kartlägga hur slaggen fungerar i dagsläget med provtagning nära konverter men även hur förändrade sammansättningar påverkar slaggen som svalnar enligt normal praxis utanför stålverket. Slagger som faller sönder av fasomvandlingar har observerats. Slutligenhar en sammansättning som ser lovande ut ur produktionsperspektiv och stabilitetsperspektivhittats. Slaggen blir då stabil även efter försök att orsaka sönderfall i extrem miljö. Vid produktionmed minskad kalktillsats under reducering kan ungefär två tredjedelar av ingående charger somska reduceras med aluminium hanteras. Med en mindre förändring i AOD processen vid reduceringså skulle ca 6000ton/år kunna skiftas från att sönderfalla till att bli stabil. / Slag has historically been used as a construction material in different applications. All types of slags are not suitable due to insufficient properties. Production of high alloy stainless steels leads to a slag which is rich in lime, which leads to disintegration due to absorption of water. Certain steel qualities at Sandvik is manufactured with a two slagg procedure where a first reduction slag is use that is replaced with a refining slag. This report looks into changes in the slag-composition to improve the properties in regards to volumetric stability after disposal. Especially it investigates volumetric stability of the reduction slag and if it is possible to combinea production of high quality steel with a stable slag. Further investigations during the project has looked at how the slag works today, with sampling close to the AOD converter but also how different slag compositions affects the slag that is disposed of outside the steelplant with todays disposal routine. Slag that disintegrates due to phase changes during cooling has been observed. A slag composition that seems promising from aproduction and stability perspective has been found. It results in a slag that remain stable even after enduring harsch enviroments. A production with less lime addition during the reduction phase can handle about two thirds of the aluminum reduced steel batches. With this small changein the AOD process roughly 6000tonnes/year of slag could be shifted from disintegration to stable material.

Thesis (Sc.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Bibliography: leaves 412-417. / by Siri Jirapongphan. / Sc.D.