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.

Yes / Although batch reactive distillation process outperforms traditional reactor-distillation processes due to simultaneous reaction and separation of products for many reaction systems, synthesis of Methyl lactate (ML) through esterification of lactic acid (LA) with methanol in such process is very challenging due to difficulty of keeping the reactants together when one of the reactants (in this case methanol) has the lowest boiling point than the reaction products. To overcome this challenge, two novel reactive distillation column configurations are proposed in this work and are investigated in detail. These are: (1) integrated conventional batch distillation column (i-CBD) with recycled methanol and (2) integrated semi-batch and conventional batch distillation columns (i-SBD) with methanol recovery and recycle. Performances of each of these configurations are evaluated in terms of profitability for a defined separation task. In i-SBD column, an additional constraint is included to avoid overflow of the reboiler due to continuous feeding of methanol into the reboiler as the reboiler is initially charged to its maximum capacity. This study clearly indicates that both integrated column configurations outperform the traditional column configurations (batch or semi-batch) in terms of batch time, energy consumption, conversion of LA to ML, and the achievable profit.

Yes / Energy saving is an important consideration in process design for low cost sustainable production with reduced environmental impacts (carbon footprint). In our earlier laboratory scale pilot plant study of catalytic wet air oxidation (CWAO) of phenol (a typical compound found in wastewater), the energy recovery was not an issue due to small amount of energy usage. However, this cannot be ignored for a large scale reactor operating around 140–160 °C due to high total energy requirement. In this work, energy savings in a large scale CWAO process is explored. The hot and cold streams of the process are paired up using 3 heat exchangers recovering significant amount of energy from the hot streams to be re-used in the process leading to over 40% less external energy consumption. In addition, overall cost (capital and operating) savings of the proposed process is more than 20% compared to that without energy recovery option.

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 / Batch reactive distillation is well known for improved conversion and separation of desired reaction products. However, for a number of reactions, the distillation can separate the reactants depending on their boiling points of them and thus not only reduces the benefit of the reactive distillation but also offers operational challenges for keeping the reactants together. Methyl lactate (ML) synthesis via the esterification of lactic acid (LA) with methanol in a reactive distillation falls into this category and perhaps that is why this process has not been explored in the past. The boiling points of the reactants (LA, methanol) are about 490 K and 337 K while those of the products (ML, water) are 417 K and 373 K respectively. Clearly in a conventional reactive distillation (batch or continuous) methanol will be separated from the LA and will reduce the conversion of LA to ML significantly. Here, first the limitations of the use of conventional batch distillation column (CBD) for the synthesis of ML is investigated in detail and a semi-batch reactive distillation (SBD) configuration is studied in detail where LA is the limiting reactant and methanol is continuously fed in excess in the reboiler allowing the reactants to be together for a longer period. However, this poses an operational challenge that the column has to be carefully controlled to avoid overflow of the reboiler at any time of the operation. In this work, the performance of SBD for the synthesis of ML is evaluated using model based optimization in which operational constraints are embedded. The results clearly demonstrate the viability of the system for the synthesis of ML.

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 / Fluidized catalytic cracking (FCC) is regarded one of the most significant operations in the oil refining industries to convert feedstock (mainly vacuum gasoil) to valuable products (namely gasoline and diesel). The behavior of the fluidized catalytic cracking process is playing a main part on the overall benefits of refinery units and improving in process or control of fluidized catalytic cracking plants will result in exciting benefits economically. According to these highlights, this study is aimed to develop a new mathematical model for the FCC process taking into account the complex hydrodynamics of the reactor regenerator system with a new six lumps kinetic model for the riser. The mathematical model, simulation and optimization have done utilizing vacuum gas oil (VGO) as a feedstock and zeolite as a catalyst under the following operating conditions: temperature (733K, 783K, and 813K), weight hourly space velocity (5, 20 and 30hr−1) and catalyst to oil ratio (4, 7 and 10). The best kinetic parameters of the relevant reactions are estimated using the optimization technique based on the experimental results taken from literature. The effect of operating condition (mainly, reaction temp (T), catalyst to oil ratio (CTO) and weight hourly space velocity (WHSV) on the product composition has also been discussed. The optimal kinetic parameters obtained from the pilot plant scale have been employed to develop an industrial FCC process, where optimal operating condition based on maximum conversion of VGO with minimum cost in addition to maximizing the octane number of gasoline (GLN), have been studied. Minimum coke content deposition the catalyst within the regenerator is also investigated here. New results (the highest conversion and octane number, and the lowest coke content) have obtained in comparison with those reported in the literature.

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.

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.