In this thesis we study a novel type of hydropower generation which uses a Venturi contraction to amplify the pressure drop across a turbine, allow- ing for cost-effective hydropower generation in situations where the head drop is small, such as in rivers and weirs. The efficiency is sensitive to how the secondary flow, which passes through the turbine, mixes with the accelerated primary flow, which is diverted around the turbine, within the confines of a closed geometry. In particular, it is important to understand the behaviour of the turbulent shear layers between the primary and sec- ondary flows, which grow downstream, mixing the flows together. The behaviour of the shear layers in the expanding part of the Venturi con- traction is strongly dependent on the shape of the channel. An important consequence of the channel shape, and hence the flow behaviour, is the degree of pressure amplification across the turbine, which determines the amount of generated power. We focus on mathematically modelling the mixing of the flows in turbu- lent shear layers, and we investigate two different ways to increase pres- sure amplification: optimising the shape of the channel, and using swirl to enhance mixing. The channel shape optimisation reveals an interest- ing balance between the effects of mixing and wall drag. Wide channel expansion tends to accentuate non-uniform flow, causing poor pressure amplification, whilst shallow expansion creates enhanced wall drag, which is also detrimental to pressure amplification. We show how the maximum power is generated with a channel shape that strikes a balance between these two effects. We find that swirl enhances mixing by increasing shear layer growth rates, but it produces large pressure losses in doing so, and for large amounts of swirl a slowly recirculating region can form along the channel centreline. Whilst swirl does not improve efficiency, there may be some inevitable swirl present in the flow, and we show how this affects the optimum channel shape. We also establish the criteria for the existence of such a recirculation region so that it may be avoided.

The purpose of this thesis is to generate a deeper understanding of the representation of hydropower in long-term models. This is done by mapping and modelling (cascading) hydropower in Sweden with the Open Source energy MOdelling SYStem (OSeMOSYS). The first part of the thesis builds on a literature review and provides an introduction to hydropower in Sweden. The second part focuses on implementing the storage equations in OSeMOSYS. These are applied by modelling hydropower at various levels of detail to evaluate the result when the depth of detail of the storage modelling is increased. First, a model of Sweden without hydropower storage is modelled. Then, two models were set up which include storage; one with one hydropower storage for all of Sweden, one with nine rivers with storage. Finally, two models considering cascading hydropower with storage were developed; where the first is an expansion of the model with one storage for all of Sweden and the second model examine two rivers more thorough. The remain-ing power system is represented in a stylised fashion, compliant with prevailing long-term energy modelling techniques. The implications of the different levels of detail are compared and discussed. The comparisons show that it is important to consider the lev-el of detail when looking at the short-term effects of long-term energy models.

This thesis deals with the application of optimisation based Validation and Verification (V&V) analysis on aerospace vehicles in order to determine their worst case performance metrics. To this end, three aerospace models relating to satellite and launcher vehicles provided by European Space Agency (ESA) on various projects are utilised. As a means to quicken the process of optimisation based V&V analysis, surrogate models are developed using polynomial chaos method. Surro- gate models provide a quick way to ascertain the worst case directions as computation time required for evaluating them is very small. A sin- gle evaluation of a surrogate model takes less than a second. Another contribution of this thesis is the evaluation of operational safety margin metric with the help of surrogate models. Operational safety margin is a metric defined in the uncertain parameter space and is related to the distance between the nominal parameter value and the first instance of performance criteria violation. This metric can help to gauge the robustness of the controller but requires the evaluation of the model in the constraint function and hence could be computationally intensive. As surrogate models are computationally very cheap, they are utilised to rapidly compute the operational safety margin metric. But this metric focuses only on finding a safe region around the nominal parameter value and the possibility of other disjoint safe regions are not explored. In order to find other safe or failure regions in the param- eter space, the method of Bernstein expansion method is utilised on surrogate polynomial models to help characterise the uncertain param- eter space into safe and failure regions. Furthermore, Binomial failure analysis is used to assign failure probabilities to failure regions which might help the designer to determine if a re-design of the controller is required or not. The methodologies of optimisation based V&V, surrogate modelling, operational safety margin, Bernstein expansion method and risk assessment have been combined together to form the WCAT-II MATLAB toolbox.

Yes / The synthesis of ethyl benzoate (EtBZ) via esterification of benzoic acid (BeZ) with ethanol in a reactive distillation is challenging due to complex thermodynamic behaviour of the chemical reaction and the difficulty of keeping the reactants together in the reaction zone (ethanol having the lowest boiling point can separate from the BeZ as the distillation proceeds) causing a significant decrease in the conversion of BeZ in a conventional reactive distillation column (batch or continuous). This might be the reason of not reporting the use of reactive distillation for EtBZ synthesis although the study of BeZ esterification reaction is available in the public literature. Our recently developed Integrated Conventional Batch Distillation (i-CBD) column offers the prospect of revisiting such reactions for the synthesis of EtBZ, which is the focus of this work. Clearly, i-CBD column outperforms the Conventional Batch Distillation (CBD) column in terms of product amount, purity and conversion of BeZ and eliminates the requirement of excess use of ethanol. For example, compared with CBD column, the i-CBD operation can yield EtBZ at a much higher purity (0.925 compared to 0.730) and can convert more benzoic acid (93.57% as opposed to only 74.38%).

Yes / Reverse osmosis (RO) has found extensive applications in industry as an efficient separation process in comparison with thermal process. In this study, a one-dimensional distributed model based on a wastewater treatment spiral-wound RO system is developed to simulate the transport phenomena of solute and water through the membrane and describe the variation of operating parameters along the x-axis of membrane. The distributed model is tested against experimental data available in the literature derived from a chlorophenol rejection system implemented on a pilot-scale cross-flow RO filtration system with an individual spiral-wound membrane at different operating conditions. The proposed model is then used to carry out an optimisation study using a genetic algorithm (GA). The GA is developed to solve a formulated optimisation problem involving two objective functions of RO wastewater system performance. The model code is written in MATLAB, and the optimisation problem is solved using an optimisation platform written in C++. The objective function is to maximize the solute rejection at different cases of feed concentration and minimize the operating pressure to improve economic aspects. The operating feed flow rate, pressure and temperature are considered as decision variables. The optimisation problem is subjected to a number of upper and lower limits of decision variables, as recommended by the module’s manufacturer, and the constraint of the pressure loss along the membrane length to be within the allowable value. The algorithm developed has yielded a low optimisation execution time and resulted in improved unit performance based on a set of optimal operating conditions.

Yes / The content and concentration of beta-carotene, tocopherol and free fatty acid is one of the important parameters that affect the quality of edible oil. In simulation based studies for refined palm oil process, three variables are usually used as input parameters which are feed flow rate (F), column temperature (T) and pressure (P). These parameters influence the output concentration of beta-carotene, tocopherol and free fatty acid. In this work, we develop 2 different ANN models; the first ANN model based on 3 inputs (F, T, P) and the second model based on 2 inputs (T and P). Artificial neural network (ANN) models are set up to describe the simulation. Feed forward back propagation neural networks are designed using different architecture in MATLAB toolbox. The effects of numbers for neurons and layers are examined. The correlation coefficient for this study is greater than 0.99; it is in good agreement during training and testing the models. Moreover, it is found that ANN can model the process accurately, and is able to predict the model outputs very close to those predicted by ASPEN HYSYS simulator for refined palm oil process. Optimization of the refined palm oil process is performed using ANN based model to maximize the concentration of beta-carotene and tocopherol at residue and free fatty acid at distillate.

No

Yes / N-nitrosamine in wastewater treatment processes can contribute to several public health impacts including human carcinogens even at very low concentration. In this work, spiral-wound reverse osmosis (SWRO) process is used to remove N-nitrosamine compounds from wastewater. Effects of operating parameters of the SWRO process on the removal of N-nitrosamine, total water recovery, and specific energy consumption for a SWRO configurations are evaluated via simulation and optimisation. For this purpose, the one-dimensional distributed model developed earlier by the authors is modified by including different mass transfer coefficient correlation, temperature dependent water and solute permeability correlations and energy equations. The model is first validated by estimating a new set of model parameters using eight set of experimental data from the literature and is then used to simulate the process with and without energy recovery device to facilitate deeper insight of the effect of operating conditions on the process performance. The model is then embedded within an optimisation framework and optimisation problems to maximise N-nitrosamine rejections and to minimise specific energy consumption are formulated and solved while the operating conditions are optimized simultaneously.

Among many seawater desalination processes, the multistage flash (MSF) desalination process is a major source of fresh water around the world. The most costly design and operation problem in seawater desalination is due to scale formation and corrosion problems. Fouling factor is one of the many important parameters that affect the operation of MSF processes. This thesis therefore focuses on determining the optimal design and operation strategy of MSF desalinations processes under fouling which will meet variable demand of freshwater. First, a steady state model of MSF is developed based on the basic laws of mass balance, energy balance, and heat transfer equations with supporting correlations for physical properties. gPROMS software is used to develop the model which is validated against the results reported in the literature. The model is then used in further investigations. Based on actual plant data, a simple dynamic fouling factor profile is developed which allows calculation of fouling factor at different time (season of the year). The role of changing brine heater fouling factor with varying seawater temperatures (during the year) on the plant performance and the monthly operating costs for fixed water demand and fixed top brine temperature are then studied. The total monthly operation cost of the process are minimised while the operating parameters such as make up, brine recycle flow rate and steam temperature are optimised. It was found that the seasonal variation in seawater temperature and brine heater fouling factor results in significant variations in the operating parameters and operating costs. The design and operation of the MSF process are optimized in order to meet variable demands of freshwater with changing seawater temperature throughout the day and throughout the year. On the basis of actual data, the neural network (NN) technique has been used to develop a correlation for calculating dynamic freshwater demand/consumption profiles at different times of the day and season. Also, a simple polynomial based dynamic seawater temperature correlation is developed based on actual data. An intermediate storage tank between the plant and the client is considered. The MSF process model developed earlier is coupled with the dynamic model for the storage tank and is incorporated into the optimization framework within gPROMS. Four main seasons are considered in a year and for each season, with variable freshwater demand and seawater temperature, the operating parameters are optimized at discrete time intervals, while minimizing the total daily costs. The intermediate storage tank adds flexible scheduling and maintenance opportunity of individual flash stages and makes it possible to meet variable freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any-time during the day and for any season. Finally, the purity of freshwater coming from MSF desalination plants is very important when the water is used for industrial services such as feed of boiler to produce steam. In this work, for fixed water demand and top brine temperature, the effect of separation efficiency of demister with seasonal variation of seawater temperatures on the final purity of freshwater for both cleaned and fouled demister conditions is studied. It was found that the purity of freshwater is affected by the total number of stages. Also to maintain the purity of freshwater product, comparatively large number of flash stage is required for fouled demister.