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By September 2009 the International Atomic Energy Agency reported that the number of commercially operated nuclear reactors in 30 countries across the world is 436, around 50 reactors are currently being constructed, 137 reactors have been ordered or is already planned, and there are around 295 proposed reactors. Pressurised water reactors (PWRs) make up the majority of these numbers. The growing number of carbon emissions and the ongoing fight against fossil fuel power stations might see the number of planned nuclear reactors increase even more to be able to satisfy the world’s need for cleaner energy. To ensure that technology keeps pace with this growing demand, ongoing research is essential. Not only is the research of new reactor technologies (i.e. High Temperature Reactors) important, but improving the current technologies (i.e. PWRs) is critical. With the increased contribution of nuclear generated electricity to our grids, it is becoming more common for nuclear reactors to be operated as load following units, and not base load units as they are more commonly being operated. Therefore a need exists to study and develop new strategies and technologies to improve the automatic load following capabilities of reactors. PWR power plants are multivariable systems. In this study a multivariable, more specifically, a model predictive controller (MPC) is developed for controlling the load following of a nuclear power plant, more specifically a PWR plant. In developing this controller system identification is employed to develop a model of the PWR plant. For the identification of the model, measured data from a computer based PWR simulator is used as the input. The identified plant model is used to develop the MPC controller. The controller is developed and tested on the plant model. The MPC controller is also evaluated against another set of measured data from the simulator. To compare the performance of the MPC controller to that of the conventional controller the ITAE performance index is employed. During the process Matlab ® , the System Identification Toolbox™, the MPC Toolbox™ and Simulink ® are used. The results reveal that MPC is practicable to be used in the control of non-linear systems such as PWR plants. The MPC controller showed good results for controlling the system and also outperformed the conventional controllers. A further result from the dissertation is that system identification can successfully be used to develop models for use in model based controllers like MPC controllers. The results of the research show that a need exists for future research to improve the methods to eventually have a controller that can be applied on a commercial plant. / Thesis (M.Ing. (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2010.

By September 2009 the International Atomic Energy Agency reported that the number of commercially operated nuclear reactors in 30 countries across the world is 436, around 50 reactors are currently being constructed, 137 reactors have been ordered or is already planned, and there are around 295 proposed reactors. Pressurised water reactors (PWRs) make up the majority of these numbers. The growing number of carbon emissions and the ongoing fight against fossil fuel power stations might see the number of planned nuclear reactors increase even more to be able to satisfy the world’s need for cleaner energy. To ensure that technology keeps pace with this growing demand, ongoing research is essential. Not only is the research of new reactor technologies (i.e. High Temperature Reactors) important, but improving the current technologies (i.e. PWRs) is critical. With the increased contribution of nuclear generated electricity to our grids, it is becoming more common for nuclear reactors to be operated as load following units, and not base load units as they are more commonly being operated. Therefore a need exists to study and develop new strategies and technologies to improve the automatic load following capabilities of reactors. PWR power plants are multivariable systems. In this study a multivariable, more specifically, a model predictive controller (MPC) is developed for controlling the load following of a nuclear power plant, more specifically a PWR plant. In developing this controller system identification is employed to develop a model of the PWR plant. For the identification of the model, measured data from a computer based PWR simulator is used as the input. The identified plant model is used to develop the MPC controller. The controller is developed and tested on the plant model. The MPC controller is also evaluated against another set of measured data from the simulator. To compare the performance of the MPC controller to that of the conventional controller the ITAE performance index is employed. During the process Matlab ® , the System Identification Toolbox™, the MPC Toolbox™ and Simulink ® are used. The results reveal that MPC is practicable to be used in the control of non-linear systems such as PWR plants. The MPC controller showed good results for controlling the system and also outperformed the conventional controllers. A further result from the dissertation is that system identification can successfully be used to develop models for use in model based controllers like MPC controllers. The results of the research show that a need exists for future research to improve the methods to eventually have a controller that can be applied on a commercial plant. / Thesis (M.Ing. (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2010.

Neutron flux fluctuations are a natural phenomenon of nuclear reactors. Approximately since 2001, pressurized water reactors built by Kraftwerk Union AG have exhibited an unexplained cycle-by-cycle change of the magnitude of these fluctuations. The change has also drawn attention to long-known but also unexplained spatial correlations of the fluctuations in these reactors. The thesis at hand aims to contribute to a better understanding of both the observed change in magnitude and the immanent correlations. Based on the findings of previous research and on the own analysis of measured raw data, a hypothesis was developed, which states that a synchronous coolant-flow driven vibration of major parts of the fuel-assembly ensemble triggers the main contribution to the observed neutron flux fluctuations. The fluctuation correlations are supposed to result from the correlations of the fuel-assembly vibration. This idea was tested using the time-domain reactor dynamics code DYN3D and complementary using the frequency-domain neutronic tool CORE SIM. For this purpose, simplified mechanical models of the synchronous fuel-assembly vibration and models coupling the vibration to the neutron kinetics were developed and implemented. Two effects are distinguished: In case of the “reflector effect”, all fuel assemblies vibrate synchronously, in a way that the main resulting perturbation acts in the radial reflector as a fluctuation of the water layer between the outer fuel assemblies and the core shroud. In case of the “fuel-assembly pitch effect”, the fuel assemblies are unequally involved in the synchronous vibration, in a way that the main perturbations are induced within the reactor core as fluctuations of the fuel-assembly gaps. Both the simulations with DYN3D and the simulations with CORE SIM showed that a synchronized fuel-assembly vibration is a possible main source of the concerned neutron flux fluctuations. In particular, the uniform fluctuation of the gaps between all fuel assemblies, corresponding to high-amplitude fuel-assembly vibrations in the core center and low-amplitude fuel-assembly vibrations in the outer core regions, gave the best approximation to the measured data. A C-like axial vibration-shape provides the best agreement. The simulation results show that the developed hypothesis should be further investigated. In particular, the proposed synchronized vibration of the fuel assemblies suggest correlations of the neutron flux fluctuations with mechanical signals, which have not been taken into account so far. The simulations presented here enable further improvements of the understanding of the neutron flux fluctuations in the concerned reactors by additional measurements involving also specific modes of reactor operation.

The environmentally-assisted fatigue crack growth behaviour of austenitic stainless steels in deoxygenated high temperature water at low strain rates has been reported to be greatly affected by the sulphur (S) content of the specimen, with high S specimens exhibiting significant reduced crack growth rates (retardation) when compared to low S specimens. To further the understanding of the mechanistic behaviour, fatigue crack growth experiments have been performed on high and low sulphur Type 316 austenitic stainless steel specimens tested in high temperature water and evaluated via microstructural characterisation techniques. At high strain rates the enhanced crack growth for both specimens appeared to be crystallographic and associated with slip localization. Furthermore, matching fracture surface analysis indicated discrepancy of the slip steps and micro-cleavage cracks between the matching surfaces, suggesting that slip steps and micro-cleavage cracking occurred after the crack-tip had advanced. It was also postulated that their formation may involve cathodically-produced hydrogen and shear deformation on the fracture surface. However, when the loading frequency was decreased, the high S specimens retarded the crack growth and the path was no longer crystallographic. Significant differences in the crack-tip opening displacements were observed in both materials, with blunt crack-tips in the high sulphur specimen and sharp tips in the low sulphur specimen when the strain rate was low. EBSD analysis at the crack-tips of both specimens showed that the strain was more localised at the crack-tip of the low sulphur specimen whist the strain ahead of the high sulphur specimen was more homogenous. It is thus postulated that retardation occurs when slip localisation is no longer the dominant factor. The localised deformation during enhancement is believed to have been caused by hydrogen enhanced localised plasticity (HELP) which causes the crack-tip to sharpen. The diffused strain distribution during crack growth retardation is believed to have been caused by hydrogen enhanced creep (HEC) which causes the crack-tip to blunt. It is also believed that both enhancement and retardation mechanisms are associated with contrasting effects deriving from hydrogen enhanced plasticity. Oxide induced crack closure was excluded as a mechanism responsible for retardation of fatigue crack growth when the stress ratio is high. Effects of hydrogen induced alpha' and ε martensite phases on oxidation behaviour of austenitic stainless steels in deoxygenated high temperature water have also been studied. Microstructural characterisation shows that hydrogen induced alpha' martensite enhances oxidation of austenitic stainless steels in deoxygenated high temperature water. The implications of this finding on environmentally assisted cracking of austenitic stainless steels in deoxygenated high temperature water is discussed.