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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.

Dissertation submitted in fulfilment of the requirements for the degree Master of Technology: Quality in the Faculty of Engineering at the Cape Peninsula University of Technology, 2013 / Many top performing businesses, which achieve superior levels of success and sustainability, have a sound, implemented, and well maintained, Quality Management System (QMS). The correlation between business success and an implemented management system has been shown in numerous papers. This research, which culminates in a quantitative measure of QMS performance, was conducted at Eskom’s Koeberg Nuclear Power Station (KNPS). The power station is the operating leg of the Koeberg Operating Unit (KOU). The researcher is a QMS lead auditor in the KNPS Quality Assurance Department. A program of audits is planned based on the KOU quality and safety manual and the national regulatory licencing requirements. The audit monitoring program is then implemented over a three year period and considers all the management system processes which impact on nuclear safety and business performance. The individual audits each consider ISO 9001 criteria in context of the business area audited. Each major business area (e.g. design, maintenance, etc.) within the power station adheres to all generic ISO 9001 QMS clauses and considerations, such as documentation management, records management, etc. Each process or business area audit is thus effectively a QMS audit. The audit results, when combined are therefore a representative measure of the overall organisational QMS performance. The potential value to be gained from the audit results and data accrued over the monitoring period has not been optimised to maximise the return on investment to Eskom. The research problem statement thus proposes that the performance measurement capability of the quality management system at Eskom's Koeberg Power Station is insufficient. This diminishes management's ability to identify business risk resulting from management system deficiencies, which impacts negatively on business performance. The research question seeks to determine how the performance measurement capability of the QMS can be improved to assist management in identifying business risk resulting from quality management system deficiencies in order to improve business performance. The research objectives are supported by the literature study, which identifies the quality management methods currently used in order to measure and subsequently improve business performance. It also shows how QMS performance measurement, when deconstructed and analysed can provide the required insight for supporting management decision making. The research approach is considered inductive in that a theory is developed based on the collection and the analysis of that data. Applied research, will thus serve as the basis of the research methodology as it is considered the most appropriate research approach, based on the need to answer practical questions around the measurement of QMS performance philosophy. The research shows that by introducing additional theming and severity data into the secondary audit findings data, it is possible over time to extract high level strategic direction information when analysing the additional metadata. The dimensions and value of the QMS Performance measuring instrument are: Ø A cause and effect theming philosophy of audit findings providing an additional context to business improvement advice to management. Ø The provision of a QMS process deficiency locator / identifier which targets management action areas for improvement. Ø The provision of a quantitative measure of the management system performance, providing a reference from which to improve. By providing a quantifiable measure of an organisations QMS performance, a reference point is provided to gauge QMS performance and also render a definitive measure to enable performance improvement of the business.

Submitted in partial fulfilment of the requirements for the degree of Master of Technology (M Tech) Cape Peninsula University of Technology 2014 / The increased demand for electricity has persuaded a number of countries world-wide to re-evaluate their strategies on energy production. These strategies largely focus on expanding the power generation capacity and adjustment of the amount of energy generated from various sources, in the light of global climate change, security of energy supply and fossil fuel price volatility (OECD report, 2010). In the United States of America (USA), for example, according to Ansolabehere & Konisky (2009), a projection of 40% rise in electricity demand is forecast over the next three decades presenting a need for diversifying the energy mix and expanding power generation capacity. The need for expanding energy supply is increasingly becoming more pronounced in a number of developing countries as well. The demand for energy warrants generation of energy from a variety of sources: coal-fired power plants, gas turbines, wind farms and nuclear power facilities. In order to transmit electricity efficiently these facilities need to be located near residential centres. The challenges associated with the construction of such centres are multi-fold. The option of nuclear power generation is a very divisive issue with as many opponents as supporters, and it has certainly been put back on the agenda in many countries including China, India and Russia, with over 250 nuclear projects in the pipeline globally. The construction of nuclear power plants is often masked with opposition from the public resulting in huge delays in completing the projects yet, nuclear energy is considered as one of the most comprehensive and cost-effective generating options which has the potential to reduce carbon dioxide emissions, meet the ever-increasing demand for electricity as well as making a crucial contribution to energy independence and security of supply.

Thesis (DTech (Electrical Engineering))--Cape Peninsula University of Technology, 2016. / The widespread application of nuclear science and technology has been the subject of much concern as well as nuclear safety issues. And to ensure the safety of public life, property and environment, it is indispensable to improve the emergency system for nuclear accidents and the environmental monitoring system for nuclear radiation, so that the occurrence of nuclear accidents, terrorist incidents and the resulting hazards can be prevented or minimized. Due to the benefits of radiation which were earlier and now recognized in the use of X-rays for medical diagnosis and then later with the discoveries of radiation and radioactivity, there was rush in exploiting the medical benefits which eventually led fairly to the recognition of the risks and induced harm associated with it. Thus, only the most obvious harms resulting from high doses of radiation, such as radiation burns, were initially observed and protection efforts were focused on their prevention, mainly for practitioners rather than patients. Subsequently, it was gradually recognized that there were other, less obvious, harmful radiation effects such as radiation-induced cancer, for which there is certain risk even at low doses of radiation.

The main goal of this Thesis was to measure tritium activity in the Vltava River and in the vicinity of Temelín Nuclear Power Plant (hereinafter referred to as JETE) with the following objectives: Possibility to use the outlet of waste water damping unit (hereinafter referred to as VTOOV) as a control alerting system for nonstandard events in JETE, furthermore, monitoring of possible correlations between volume activity of tritium measured in VTOOV and activity above the limit value of the first quality class in selected sections of the Vltava River as well as comparison of the measured values with the results of other authors, and, finally, assessment of the relevance of the water quality estimated by the volume activity of tritium to the water quality according to other ingredients, i.e., stable isotopes of some metals and risk elements as well as general physical and chemical indicators. Theoretical part of the Thesis deals with radioactivity in general, activity of tritium, with regard to operation of nuclear plants, over the world and, especially, in the Czech Republic. The actual work consisted of collection of samples at predetermined places, preparation of these samples for measurement and measurement of tritium activity using scintillation spectrometer with liquid scintillator. Furthermore, basic chemical and physical properties of water, concentration of selected elements and also some anions were determined. The collected data were used for classification of waters from individual collection places into quality classes according to ČSN 75 7221. In all analyzed cases no activities were found which exceeded the limit values of liquid outlets from Temelín Nuclear Power Plant, given by regulations issued on waters by the District Health Office in Ceske Budejovice according to §8 of Act No. 138/73 Coll., in compliance with SÚJB requirements. This Thesis could be beneficial for possible utilization of VTOOV as a control alerting system for nonstandard events in JETE and also for assessment of impact of wastewaters from JETE on waters of the Vltava River.

Ce travail de thèse est motivée par la possibilité de surveiller l'état des composants de systèmes d'énergie pour leur utilisation prolongée et sécuritaire, conformément à la pratique correcte de fonctionnement et des politiques adéquates de maintenance. La motivation est de développer des méthodes basées sur la régression à vecteurs de support pour la prédiction de données de séries chronologiques dans des conditions environnementales et opérationnelles stationnaire/ non-stationnaire. Les simples modèles et les ensembles de modèles à base de SVR sont développés pour attaquer la prédiction basée sur des petits et des grands ensembles de données. Des stratégies sont proposées pour la mise à jour de façon adaptative les simples modèles et les ensembles de modèles à base de SVR au cas du changement de la distribution générant les données. Les comparaisons avec d'autres méthodes d'apprentissage en ligne sont fournies en référence à des données de séries chronologiques d'un composant critique dans les centrales nucléaires fournis par Electricité de France (EDF). Les résultats montrent que les approches proposées permettent d'atteindre des résultats de prédiction comparables compte tenu de l'erreur quadratique moyenne et erreur relative, en beaucoup moins de temps de calcul. Par ailleurs, en analysant le sens géométrique de la méthode de la sélection de vecteurs caractéristiques(FVS) proposé dans la littérature, une nouvelle méthode géométriquement interprétable, nommé Reduced RankKernel Ridge Regression-II (RRKRR-II), est proposée pour décrire les relations linéaires entre un valeur prédite et les valeurs prédites des vecteurs caractéristiques sélectionné par FVS. Les comparaisons avec plusieurs méthodes sur un certain nombre de données publics prouvent la bonne précision de la prédiction et le réglage facile des hyperparamètres de RRKRR-II. / This Ph. D. work is motivated by the possibility of monitoring the conditions of components of energy systems for their extended and safe use, under proper practice of operation and adequate policies of maintenance. The aim is to develop a Support Vector Regression (SVR)-based framework for predicting time series data under stationary/nonstationary environmental and operational conditions. Single SVR and SVR-based ensemble approaches are developed to tackle the prediction problem based on both small and large datasets. Strategies are proposed for adaptively updating the single SVR and SVR-based ensemble models in the existence of pattern drifts. Comparisons with other online learning approaches for kernel-based modelling are provided with reference to time series data from a critical component in Nuclear Power Plants (NPPs) provided by Electricité de France (EDF). The results show that the proposed approaches achieve comparable prediction results, considering the Mean Squared Error (MSE) and Mean Relative Error (MRE), in much less computation time. Furthermore, by analyzing the geometrical meaning of the Feature Vector Selection (FVS) method proposed in the literature, a novel geometrically interpretable kernel method, named Reduced Rank Kernel Ridge Regression-II (RRKRR-II), is proposed to describe the linear relations between a predicted value and the predicted values of the Feature Vectors (FVs) selected by FVS. Comparisons with several kernel methods on a number of public datasets prove the good prediction accuracy and the easy-of-tuning of the hyperparameters of RRKRR-II.