Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering In the Faculty of Engineering at the Cape Peninsula University of Technology, 2013 / The French South African Institute of Technology (F’SATI) at the Cape Peninsula University of Technology (CPUT) began a program in Satellite Systems Engineering in 2009 and is developing its first satellites. The satellites are based on the CubeSat standard, which defines one unit (1U) as a cube with a maximum weight of 1 kg and volume of 1dm3, and can be scaled up to three units (3U) for increased functionality. ZACUBE-1, a 1U CubeSat that is being developed, will be launched into a sun synchronous orbit in 2013. The main payload of the 1U CubeSat under development is a space weather experiment (beacon transmitter). The beacon transmitter is a scientific payload, which is being developed in collaboration with SANSA Space Science (SANSA SS) in Hermanus, South Africa. The beacon signal will be used to characterise the space weather radar antenna array at the South African National Antarctic Expedition (SANAE IV) base in Antarctica. The SANAE IV radar forms part of the SuperDARN (Dual Auroral Radar Network) project. This phased array antenna network comprises 16 radiating elements, with a 3o beam width that can be steered in 16 different directions to span the azimuth sector. These antennas are spread over both the northern and southern hemispheres. They operate in the HF band between 8 to 20 MHz and are used to primarily monitor the convection of the Earth’s magnetic field by monitoring coherent scatter from it. Orbital analyses were conducted to determine how the choice of the orbit affects the coverage of the array’s field-of-view. Propagation analyses were conducted to investigate how space weather variations affect HF signal propagation. The beacon signal will be used as an active target source and will enable the determination of the phase response of the array, thereby determining the direction-of-arrival of the signal. This will allow the experimental verification of the antenna’s beam pattern. The beacon signal prototype board was developed by using an RFID transceiver that operates in the HF band, capable of delivering up to 200 mW. Position determination of the satellite will be done by using two line elements (TLE) data. Experimental data will be available once ZACUBE-1 is in orbit; therefore, the work presented here documents a feasibility study and design of the experiment that will be conducted once the satellite is in orbit.

Thesis (MTech (Electrical Engineering)--Cape Peninsula University of Technology, 2011 / Modern technologies have led to extensive digital music reproduction and distribution. It is fitting then that digital audio be amplified directly from its source rather than being converted to an analogue waveform before amplification. The benefits of using a digital controller for audio processing include being able to easily reconfigure the system and to add additional functions at a later stage. Digital audio is primarily stored as Pulse Code Modulation (PCM) while Pulse Width Modulation (PWM) is the most popular scheme used to drive a class-D amplifier. The class-D amplifier is selected in many applications due to its very high energy efficiency. Conventional PCM to PWM conversion is inherently nonlinear. Various interpolation schemes are presented in this research project which help to address the nonlinearity. Digitally generated PWM has a limited resolution which is constrained by the system clock. This thesis presents noise shaping techniques which increase the effective resolution of the PWM process without having to use an excessively high system clock. Noise shaping allows a low resolution modulator to be used to reproduce high resolution audio.

The Department of Electrical Engineering in fulfilment of the requirements for the Magister Technologiae in Electrical Engineering at the Cape Peninsula University of Technology November 2013 / Pole mounted transformers (PMT) in rural areas present an opportunity for local utilities to do current monitoring on these systems. These transformers are exposed to abnormal amounts of stress due to the vast power demand in these areas. The aim of this study is to develop a more cost-effective condition monitoring system. Transformer current monitoring can be a dangerous practice if not done by suitably trained utility electricians. Hence this study is partly aimed at the elimination of hazardous working environments associated with manual electrical measurements. An investigation to determine a safe and cost-effective way to obtain the electrical measurements required from PMTs is undertaken. Although current measurements can be done with a current clamp-on meter, these measurements still take place at the phases of the transformer and are unsafe. The possibility of implementing wireless data gathering on current clamp-on meters is therefore investigated. This is made possible by a wireless sensor node (WSN) which gathers information and transmits it wirelessly to a WSN base station. This wireless solution is battery powered, necessitating battery replacements, therefore leading to the investigation of magnetic fields, magnetic materials and magnetic induction. A current clamp able to generate a high voltage (HV) output with minimal magnetic field strength is developed. The magnetic fields produced by the transformer’s phase cables are used to generate an alternating voltage. With the help of a microcontroller and an energy harvesting circuit, this voltage is converted and used to charge supercapacitors. The magnetic fields are also used to determine the current flow in the transformer phase cables when the device is not in energy harvesting mode. The device will then undergo comprehensive laboratory testing to determine its accuracy and durability, and is then used to do ‘real life’ current measurements, the results of which are compared against an off-the-shelf current monitoring device.

Thesis submitted in fulfilment of the requirements for the degree of Masters of Technology: Chemical Engineering in the Faculty of Engineering Cape Peninsula University of Technology, South Africa Supervisor: Prof TV Ojumu Cape Town Campus September 2013 / Jarosite formation is regarded as undesirable in the bioleaching processes as it depletes ferric reagent; a critical reagent for the oxidation of most sulphide minerals, from bioleach solution. It creates kinetic barriers and clogs on mineral surfaces, thereby retarding leach rates of most minerals. However, jarosite has also been shown to serve as support for the attachment of bioleaching microbes, facilitating a high ferric-iron generation rate. In this study, a series of experiments on microbial ferrous-iron oxidation by a mesophilic microbe were carried out in a novel packed-column bioreactor with a view to investigating the potential use of solution pH to manage jarosite accumulation in the bioreactor. The kinetics of the oxidation was also investigated to establish base case data for the novel bioreactor. The bioreactor was packed with glass balls 15 mm in diameter. The experiments were conducted at a constant temperature of 38.6 °C, residence time of 18 hrs, airflow rate of 20 mL.s-1 and at desired solution pHs (1.3, 1.5 and 1.7). The results showed that the amount of jarosite accumulation is proportional to the operating solution pH and also to the duration of operation of the bioreactor. Jarosite precipitate of 4.95, 5.89 and 7.08 g.L-1 were obtained after 10 days of continuous operation at solution pH of 1.3, 1.5 and 1.7 respectively, while after 15 days the precipitate concentration increased to 5.50, 7.90 and 9.98 g.L-1respectively. The results also showed that a 33% and 52% reduction in jarosite accumulation could be achieved by a gradual decrease of the bioreactor solution pH after being continuously operated for 10 days from pH 1.7 to 1.5 and pH 1.7 to 1.3, respectively, for an additional five days of continuous operation. The results of the ferrous-iron biooxidation kinetics investigated at pH 1.3 show a maximum ferrous oxidation rate ( max 2 Fe r ) of 6.85 mmol.L-1.h-1 and apparent affinity kinetics constants (   2 Fe K , 2 Fe K ) of 0.001 mmol Fe2+.L-1 and 0.006 (dimensionless) using Hansford and Monod equations, respectively. Although a direct relationship exists between jarosite formation and solution pH, the results of this study may be relevant in bioleach heaps, or at least in column bioreactors, to manage and control jarosite accumulation, thereby improving leach kinetics of sulphide minerals.

Thesis submitted in fulfilment of the requirements for the degree of Masters of Technology: Chemical Engineering in the Faculty of Engineering Cape Peninsula University of Technology, South Africa, 2013 / Jarosite formation is regarded as undesirable in the bioleaching processes as it depletes ferric reagent; a critical reagent for the oxidation of most sulphide minerals, from bioleach solution. It creates kinetic barriers and clogs on mineral surfaces, thereby retarding leach rates of most minerals. However, jarosite has also been shown to serve as support for the attachment of bioleaching microbes, facilitating a high ferric-iron generation rate. In this study, a series of experiments on microbial ferrous-iron oxidation by a mesophilic microbe were carried out in a novel packed-column bioreactor with a view to investigating the potential use of solution pH to manage jarosite accumulation in the bioreactor. The kinetics of the oxidation was also investigated to establish base case data for the novel bioreactor. The bioreactor was packed with glass balls 15 mm in diameter. The experiments were conducted at a constant temperature of 38.6 °C, residence time of 18 hrs, airflow rate of 20 mL.s-1 and at desired solution pHs (1.3, 1.5 and 1.7). The results showed that the amount of jarosite accumulation is proportional to the operating solution pH and also to the duration of operation of the bioreactor. Jarosite precipitate of 4.95, 5.89 and 7.08 g.L-1 were obtained after 10 days of continuous operation at solution pH of 1.3, 1.5 and 1.7 respectively, while after 15 days the precipitate concentration increased to 5.50, 7.90 and 9.98 g.L-1respectively. The results also showed that a 33% and 52% reduction in jarosite accumulation could be achieved by a gradual decrease of the bioreactor solution pH after being continuously operated for 10 days from pH 1.7 to 1.5 and pH 1.7 to 1.3, respectively, for an additional five days of continuous operation. The results of the ferrous-iron biooxidation kinetics investigated at pH 1.3 show a maximum ferrous oxidation rate ( max 2 Fe r ) of 6.85 mmol.L-1.h-1 and apparent affinity kinetics constants (   2 Fe K , 2 Fe K ) of 0.001 mmol Fe2+.L-1 and 0.006 (dimensionless) using Hansford and Monod equations, respectively. Although a direct relationship exists between jarosite formation and solution pH, the results of this study may be relevant in bioleach heaps, or at least in column bioreactors, to manage and control jarosite accumulation, thereby improving leach kinetics of sulphide minerals.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Business Administration in Project Management in the Faculty of Business at the Cape Peninsula University of Technology 2013 / The nuclear industry has established stringent controls to ensure that electricity is produced in a safe and reliable manner. It is expected that a nuclear power plant should be operated safely, adheres to processes and procedures that govern those safe operations, and implements projects or modifications that are of a high quality; and this would be considered as ‘business as usual’. This is crucial for an industry that is under constant scrutiny, since every project or modification, which is implemented, is critically judged. One important contributing factor to the successful operation of any nuclear power plant is the implementation of projects and modifications in accordance with respective nuclear codes and standards, specifications, processes and procedures. The industry demands that this should be a norm, as quality is synonymous with safety and reliability; factors that cannot be compromised or divorced from each other on a nuclear power plant. Recently, however, there has been great concern relating to non-conformances experienced throughout the project lifecycle, which ultimately affects the quality of modifications and projects, which are implemented at the plant. The research project investigates factors that affect project quality at a nuclear power plant in South Africa. Against the above backdrop, the research problem was “the delivery of poor quality projects have an adverse effect on modifications and projects, which are implemented at the nuclear power plant in South Africa”. The primary research objectives of this study are the following: · To investigate the root cause and impact of inconsistent project quality practices on the project lifecycle; and · To recommend measures that should be established to improve the way in which project quality is conducted throughout the project lifecycle.

A Thesis Submitted Towards the Partial Fulfilment Degree of Master of Technology (M.Tech.) FACULTY OF ENGINEERING MECHANICAL ENGINEERING DEPARTMENT Cape Peninsula University of Technology 2011 / The split Hopkinson pressure bar (SHPB) test is the most commonly used method for determining material properties at high rates of strain. The theory governing the specifics of Hopkinson bar testing has been around for decades; however, it has only been for the last decade or so that significant data processing advancements have been made. It is the intent of this thesis to offer the insight of application of SHPB to determine the compressive dynamic behaviour for welded low carbon steel (mild steel). It also focuses on the tensile behaviour for unheat-treated and heat-treated welded carbon steel. The split Hopkinson Pressure bar apparatus consists of two long slender bars that sandwich a short cylindrical specimen between them. By striking the end of a bar, a compressive stress wave is generated that immediately begins to traverse towards the specimen. Upon arrival at the specimen, the wave partially reflects back towards the impact end. The remainder of the wave transmits through the specimen and into the second bar, causing irreversible plastic deformation in the specimen. It is shown that the reflected and transmitted waves are proportional to the specimen's strain rate and stress, respectively. Specimen strain can be determined by integrating the strain rate. By monitoring the strains in the two bars and the specimen's material, stress-strain properties can be calculated. Several factors influence the accuracy of the results, including the size and type of the data logger, impedance mismatch of the bars with the specimens, the utilization of the appropriate strain gauges and the strain amplifier properties, among others. A particular area of advancement is a new technique to determine the wave's velocity in the specimen with respect to change in medium and mechanical properties, and hence increasing the range of application of SHPB. It is shown that by choosing specimen dimensions based on their impedance, the transmitted stress signal-to-noise ratio can be improved. An in depth discussion of realistic expectations of strain gages is presented, along with closed form solutions validating any claims. The thesis concludes with an analysis of experimental and predicted results. Several recommendations and conclusions are made with regard to the results obtained and areas of improvement are suggested in order to achieve accurate and more meaningful results.

Thesis Submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology, 2012 / The widespread deregulation and restructuring of electric power utilities throughout the world and the surge in competition amongst utility companies has brought about the desire for improved economic efficiency of electric utilities and the provision of better service to energy consumers. These end users are usually connected to the distribution network. Thus, there is a growing research interest in distribution network fault detection and diagnosis algorithms for reducing the down-time due to faults. This is done so as to improve the reliability indices of utility companies and enhance the availability of power supply to customers. The application of signal processing and computational intelligence techniques in power systems protection, automation, and control cannot be overemphasized. This research work focuses on power system distribution network and is aimed at the development of versatile algorithms capable of accurate fault detection and diagnosis of all fault types for operation in balanced/unbalanced distribution networks, under varying fault resistances, fault inception angles, load angles, and system operating conditions. Therefore, different simulation scenarios encompassing various fault types at several locations with different load angles, fault resistances, fault inception angles, capacitor switching, and load switching were applied to the IEEE 34 Node Test Feeder in order to generate the data needed. In particular, the effects of system changes were investigated by integrating various Distributed Generators (DGs) into the distribution feeder. The length of the feeder was also extended and investigations carried out. This was implemented by modelling the IEEE 34-node benchmark test feeder in DIgSILENT PowerFactory (DPF). In the course of this research, a hybrid combination of Discrete Wavelet Transform (DWT), decision-taking rule-based algorithms, and Artificial Neural Networks (ANNs) algorithms for electric power distribution network fault detection and diagnosis was developed. The integrated algorithms were capable of fault detection, fault type classification, identification of the faulty line segment, and fault location respectively. Several scenarios were simulated in the test feeder. The resulting waveforms were exported as ASCII or COMTRADE files to MATLAB for DWT signal processing. Experiments with various DWT mother wavelets were carried out on the waveforms obtained from the simulations. In particular, Daubechies db-2, db-3, db-4, db-5, and db-8 were considered. Others are Coiflet-3 and Symlet-4 mother wavelets respectively. The energy and entropy of the detail coefficients for each decomposition level based on a sampling frequency of 7.68 kHz were analysed. The best decomposition level for the diagnostic tasks was then selected based on the analysis of the wavelet energies and entropy in each level of decomposition. Consequently, level-1 db-4 detail coefficients were selected for the fault detection task, while level-5 db4 detail coefficients were used to compute the wavelet entropy per unit indices which were then used for fault classification, fault section identification, and fault location tasks respectively. Decision-taking rule-based algorithms were used for the fault detection and fault classification tasks respectively. The fault detection task verifies if a fault did indeed occur or not, while the fault classification task determines the fault class and the faulted phase(s). Similarly, Artificial Neural Networks (ANNs) were used for the fault section identification and fault location tasks respectively. For the fault section identification task, the ANNs were trained for pattern classification to identify the lateral or segment affected by the fault. Conversely, the fault location ANNs were trained for function approximation to predict the location of the fault from the substation in kilometres. Also, the IEEE 13 Node Benchmark Test Feeder was modelled in RSCAD software and batch mode simulations were carried out using the Real-Time Digital Simulator (RTDS) as a ‘proof of concept’ for the proposed method, in order to demonstrate the scalability, and to further validate the developed algorithms. The COMTRADE files of disturbance records retrieved from an external IED connected in closed-loop with the RTDS and the runtime simulation waveforms were used as test inputs to the developed Hybrid Fault Detection and Diagnosis (HFDD) method. Comparison of the method based on entropy with statistical methods based on standard deviation and Mean Absolute Deviation (MAD) has shown that the method based on entropy is very reliable, accurate, and robust. Results of preliminary studies carried out showed that the proposed HFDD method can be applied to any power system network irrespective of changes in the operating characteristics. However, certain decision indices would change and the decision-taking rules and ANN algorithms would need to be updated. The HFDD method is promising and would serve as a useful decision support tool for system operators and engineers to aid them in fault diagnosis thereby helping to reduce system down-time and improve the reliability and availability of electric power supply. Key words: Artificial neural network, discrete wavelet transform, distribution network, fault simulation, fault detection and diagnosis, power system protection, RTDS.

Thesis submitted in fulfilment of the requirements for the degree of Master of Technology in Mechanical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology, 2012 / Our planet is continuously being depleted of its natural resources leading to a need to conserve energy and the environment. One of the major energy consumers is the conventional internal combustion engine. Many attempts have been made to make these conventional internal combustion engines more efficient focussing mostly on the combustion side of the engine. The focus of this study is on the modification of the reciprocating and rotating components of the sub-assembly of a conventional internal combustion engine. An in-depth review was carried out on the fundamentals of spark ignition internal combustion engines and savings on fuel consumptions. A prototype single piston internal combustion engine was developed that can adjust its stroke length. Lengthening or shortening the stroke and simultaneously extending or retracting the connecting rod’s travel distance, allows the internal combustion engine to function very efficiently consequently reducing the free space between the piston and cylinder head at TDC position. This allows the internal combustion engine to alter its power capability on demand whilst maintaining relatively high compression efficiency. The method of altering the stroke length is achieved by manipulating gears situated internally and externally of the engine sub-assembly. The control of these eccentric gears lowers or lifts the crankshaft in a radial motion. The eccentrics also control the automatic extension or retraction of the connecting rod’s travel distance. The externally concentric gears control the mechanism that allows the internal combustion engine to change its capacity easily as adapted for automation. This study does not extend into the automation issues of the external mechanism. The prototype engine that was built could not endure vigorous testing and it failed after running for a short while. The primary focus had been on the kinematics of the engine mechanism – and to show whether the idea was feasible. The engine passed the kinematics test but failed possibly due to dynamic loads. Investigating this requires measuring instantaneous temperatures from which peak pressures can be deduced. This was not done because it was outside the scope of the project.

In many engineering applications, it is desirable to know the behaviour of structures and systems under loading conditions. One reason is to help optimize the design and prevent damage and failure which might occur during in service and operation. Damage represents a serious problem which can cause catastrophic failure of structures, machines and systems. Therefore for safe operation, efficient and reliable methods for inspection and monitoring of damage are required. Different methods for health monitoring of structures such as non destructive testing (NDT) and strain gauges are widely used. These methods have proven to be efficient in terms of resolution and response. However, some disadvantages associated with them include the vicinity of the area under inspection which must be well known, equipment to acquire the necessary information is expensive and in many cases high skills are required for operation. On the other hand, advances in materials science and MEMS systems has promoted the use of new materials with piezoelectric properties. This include mainly polymeric and ceramic materials which after processed can be used for structural health monitoring. These materials offer a number of advantages such as lightweight, sensitivity, toughness, durability, and low cost. The present research work investigates the feasibility of using a polymeric material, Polyvinylidene Fluoride (PVDF) as a sensor for deformation and defect detection in structures. The sensors are embedded in composite cantilevered type beams to detect defects at distinct locations along the beam’s length. The defect detection method proposed is based on experimental tests and Finite Element simulations. Experimental tests on defect free and beams with manufactured internal flaws were conducted. Numerical (FEM) simulations of defect free and flawed beam models containing sections of reduced elastic modulus to represent the damage were conducted using ANSYS software. The experimental tests have been used for the validation of the numerical solution. Results have shown that the defect location changes the stiffness and indeed the frequency of vibration. For flaws near the fixed end of the beams, lower frequencies are obtained as compared to flaws away from the fixed end. PVDF sensors were used to acquire the natural frequencies of the beams for the first mode of vibration. Good agreement was verified between experimental and numerical simulation results. The work has demonstrated that PVDF film sensors can be used as possible candidates for defect detection. The analysis of the behaviour embedded PVDF sensors near the fixed end of cantilever beams, represents an initial and important step towards the application of measuring static and dynamic behaviour of structures as part of a health monitoring process.