This thesis examines the determinants of institutional quality and the process of convergence in the ECOWAS in order to inform policy about the region’s deep integration scheme. The first part of the thesis examines the historical changes that took place in the development of common institutions in West Africa in the pre-independence era. The findings demonstrated that the region exhibited some common institutions, including common currencies, standardised trade rules and protection of trade routes which facilitated regional and international trade. A single administration system helped in the effective implementation of the common institutions. Therefore, historical changes after independence led to the loss of some facets of these common institutions in West Africa. The second part examined determinants of institutional quality and the process of convergence using econometric analysis. The findings demonstrated that the process of convergence could be accelerated if WAMZ and WAEMU work together as one monetary zone under ECOWAS. Moreover, the findings also demonstrated that the level of development, state capacity, FDI, regional trade, history and regional trade partners institutional quality contain useful information in explaining the quality of institutions today. Therefore, ECOWAS’s deep integration goal would require improving some of these factors in order to facilitate the process of developing common institutions and improve their quality. In the long term, a single administration system akin to the colonial era and the Empires of Western Sudan would be desirable. This will require political commitment to do so. ECOWAS members should have the confidence that deep integration is feasible given that it existed in the region in the past.

In a dynamically monitored environment the analyst team need timely and accurate information to conduct proactive action over complex situations. Typically, there are thousands of reported activities in a real time operation, therefore steps are taken to direct the analyst’s attention to the most important activity. The data fusion community have introduced the information fusion model, with multiple situational assessments. Each process lends itself to ranking the most important activities into a predetermined order. Unfortunately, the capability of a real time system can be hindered by the knowledge limitation problem, particularly when the underlying system is processing multiple sensor information. Consequently, the situational awareness domains may not rank the identified situation as perfect, as desired by the decision-making resources. This thesis presents advanced research carried out to evaluate the ranking capability of information from the situational awareness domains: perception, comprehension and projection. The Ranking Capability Score (RCS) has been designed for evaluating the prioritisation process. The enhanced (RCS) has been designed for addressing the knowledge representation problem in the user system relation under a situational assessment where the proposed number of tracking activities are dynamically shifted. Finally, the Scheduling Capability Score was designed for evaluating the scheduling capability of the situational awareness system. The proposed performance metrics have been successful in fulfilling their objectives. Furthermore, they have been validated and evaluated using an analytical approach, through conducting a rigorous analysis of the prioritisation and scheduling processes, despite any constraints related to a domain-specific configuration.

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.

The InfiniBand Architecture (IBA) network has been proposed as a new industrial standard with high-bandwidth and low-latency suitable for constructing high-performance interconnected cluster computing systems. This architecture replaces the traditional bus-based interconnection with a switch-based network for the server Input-Output (I/O) and inter-processor communications. The efficient Quality-of-Service (QoS) mechanism is fundamental to ensure the import at QoS metrics, such as maximum throughput and minimum latency, leaving aside other aspects like guarantee to reduce the delay, blocking probability, and mean queue length, etc. Performance modelling and analysis has been and continues to be of great theoretical and practical importance in the design and development of communication networks. This thesis aims to investigate efficient and cost-effective QoS mechanisms for performance analysis and improvement of InfiniBand networks in cluster-based computing systems. Firstly, a rate-based source-response link-by-link admission and congestion control function with improved Explicit Congestion Notification (ECN) packet marking scheme is developed. This function adopts the rate control to reduce congestion of multiple-class traffic. Secondly, a credit-based flow control scheme is presented to reduce the mean queue length, throughput and response time of the system. In order to evaluate the performance of this scheme, a new queueing network model is developed. Theoretical analysis and simulation experiments show that these two schemes are quite effective and suitable for InfiniBand networks. Finally, to obtain a thorough and deep understanding of the performance attributes of InfiniBand Architecture network, two efficient threshold function flow control mechanisms are proposed to enhance the QoS of InfiniBand networks; one is Entry Threshold that sets the threshold for each entry in the arbitration table, and other is Arrival Job Threshold that sets the threshold based on the number of jobs in each Virtual Lane. Furthermore, the principle of Maximum Entropy is adopted to analyse these two new mechanisms with the Generalized Exponential (GE)-Type distribution for modelling the inter-arrival times and service times of the input traffic. Extensive simulation experiments are conducted to validate the accuracy of the analytical models.

This work addresses various applications pertaining to the design, modelling and animation of parametric surfaces using elliptic Partial Differential Equations (PDE) which are produced via the PDE method. Compared with traditional surface generation techniques, the PDE method is an effective technique that can represent complex three-dimensional (3D) geometries in terms of a relatively small set of parameters. A PDE-based surface can be produced from a set of pre-configured curves that are used as the boundary conditions to solve a number of PDE. An important advantage of using this method is that most of the information required to define a surface is contained at its boundary. Thus, complex surfaces can be computed using only a small set of design parameters. In order to exploit the advantages of this methodology various applications were developed that vary from the interactive design of aircraft configurations to the animation of facial expressions in a computer-human interaction system that utilizes an artificial intelligence (AI) bot for real time conversation. Additional applications of generating cyclic motions for PDE based human character integrated in a Computer-Aided Design (CAD) package as well as developing techniques to describe a given mesh geometry by a set of boundary conditions, required to evaluate the PDE method, are presented. Each methodology presents a novel approach for interacting with parametric surfaces obtained by the PDE method. This is due to the several advantages this surface generation technique has to offer. Additionally, each application developed in this thesis focuses on a specific target that delivers efficiently various operations in the design, modelling and animation of such surfaces.

The failure of oil well drillstrings due to torsional and longitudinal stresses caused by stick-slip phenomena during the drilling operation causes great expense to industry. Due to the complicated and harsh drilling environment, modelling of the drillstring becomes an essential requirement in studies. Currently, this is achieved by modelling the drillstring as a torsional lumped model (which ignores the length of the drillstring) for real-time measurement and control. In this thesis, a distributed-lumped model including the effects of drillstring length was developed to represent the drillstring, and was used to simulate stick-slip vibration. The model was developed with increasing levels of detail and the resultant models were validated against typical measured signals from the published literature. The stick-slip model describes the friction model that exists between the cutting tool and the rock. Based on theoretical analysis and mathematical formulation an efficient and adaptable model was created which was then used in the application of a method of species conserving genetic algorithm (SCGA) to optimise the drilling parameters. In conclusion, it was shown that the distributed-lumped model showed improved detail in predicting the transient response and demonstrated the importance of including the drillstring length. Predicting the response of different parameters along the drillstring is now possible and this showed the significant effect of modelling the drillcollar. The model was shown to better represent real system and was therefore far more suited to use with real time measurements.

Desalination is a technique of producing fresh water from the saline water. Industrial desalination of sea water is becoming an essential part in providing sustainable source of fresh water for a large number of countries around the world. Thermal process being the oldest and most dominating for large scale production of freshwater in today¿s world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. In this work, a steady state mathematical model of Multistage Flash (MSF) desalination process is developed and validated against the results reported in the literature using gPROMS software. The model is then used for further investigation. First, a steady state calcium carbonate fouling resistance model has been developed and implemented in the full MSF mathematical model developed above using gPROMS modeling tool. This model takes into consideration the effect of stage temperature on the calcium carbonate fouling resistance in the flashing chambers in the heat recovery section, heat rejection section, and brine heaters of MSF desalination plants. The effect of seasonal variation of seawater temperature and top brine temperature on the calcium carbonate fouling resistance has been studied throughout the flashing stage. In addition, the total annual operating cost of the MSF process is selected to minimise, while optimising the operating parameters such as seawater rejected flow rate, brine recycle flow rate and steam temperature at different seawater temperature and fouling resistance. Secondly, an intermediate storage between the plant and the client is considered to provide additional flexibility in design and operation of the MSF process throughout the day. A simple polynomial based dynamic seawater temperature and different freshwater demand correlations are developed based on actual data. For different number of flash stages, operating parameters such as seawater rejected flow rate and brine recycle flow rate are optimised, while the total annual operating cost of the MSF process is selected to minimise.The results clearly show that the advantage of using the intermediate storage tank adds flexible scheduling in the MSF plant design and operation parameters to meet the variation in freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any time during the day by adjusting the number of stages. Furthermore, the effect of non-condensable gases (NCG) on the steady state mathematical model of MSF process is developed and implemented in the MSF model developed earlier. Then the model is used to study effect of NCG on the overall heat transfer coefficient. The simulation results showed a decrease in the overall heat transfer coefficient values as NCG concentrations increased. The model is then used to study the effect of NCG on the design and operation parameters of MSF process for fixed water demand. For a given plant configuration (fixed design) and at different seawater and steam temperatures, a 0.015 wt. % of NCG results in significantly different plant operations when compared with those obtained without the presence of NCG. Finally, for fixed water demand and in the presence of 0.015 wt. % NCGs, the performance is evaluated for different plant configurations and seawater temperature and compared with those obtained without the presence of NCG.

An accurate model for RO process has significant importance in the simulation and optimization proposes. A steady state model of RO process is developed based on solution diffusion theory to describe the permeation through membrane and thin film approach is used to describe the concentration polarization. The model is validated against the operation data reported in the literature. For the sake of clear understanding of the interaction of feed temperature and salinity on the design and operation of RO based desalination systems, simultaneous optimization of design and operation of RO network is investigated based on two-stage RO superstructure via MINLP approach. Different cases with several feed concentrations and seasonal variation of seawater temperature are presented. Also, the possibility of flexible scheduling in terms of the number of membrane modules required in operation in high and low temperature seasons is investigated A simultaneous modelling and optimization method for RO system including boron removal is then presented. A superstructure of the RO network is developed based on double pass RO network (two-stage seawater pass and one-stage brackish water pass). The MINLP problem based on the superstructure is used to find out an optimal RO network which will minimize the total annualized cost while fulfilling a given boron content limit. The effect of pH on boron rejection is investigated at deferent seawater temperatures. The optimal operation policy of RO system is then studied in this work considering variations in freshwater demand and with changing seawater temperature throughout the day. A storage tank is added to the RO layout to provide additional operational flexibility and to ensure the availability of freshwater at all times. Two optimization problems are solved incorporating two seawater temperature profiles, representing summer and winter seasons. The possibility of flexible scheduling of cleaning and maintenance of membrane modules is investigated. Then, the optimal design and operation of RO process is studied in the presence of membrane fouling and including several operational variations such as variable seawater temperature. The cleaning schedule of single stage RO process is formulated as MINLP problem using spiral wound modules. NNs based correlation has been developed based on the actual fouling data which can be used for estimating the permeability decline factors. The correlation based on actual data to predict the annual seawater temperature profile is also incorporated in the model. The proposed optimization procedure identified simultaneously the optimal maintenance schedule of RO network including its design parameters and operating policy. The steady state model of RO process is used to study the sensitivity of different operating and design parameters on the plant performance. A non-linear optimization problem is formulated to minimize specific energy consumption at fixed product flow rate and quality while optimizing the design and operating parameters. Then the MINLP formulation is used to find the optimal designs of RO layout for brackish water desalination. A variable fouling profile along the membrane stages is introduced to see how the network design and operation of the RO system are to be adjusted Finally, a preliminary control strategy for RO process is developed based on PID control algorithm and a first order transfer function (presented in the Appendix).

Dynamic modelling and optimization of three different processes namely (a) bulk polymerization of styrene, (b) solution polymerization of methyl methacrylate (MMA) and (c) emulsion copolymerization of Styrene and MMA in batch and semi-batch reactors are the focus of this work. In this work, models are presented as sets of differential-algebraic equations describing the process. Different optimization problems such as (a) maximum conversion (Xn), (b) maximum number average molecular weight (Mn) and (c) minimum time to achieve the desired polymer molecular properties (defined as pre-specified values of monomer conversion and number average molecular weight) are formulated. Reactor temperature, jacket temperature, initial initiator concentration, monomer feed rate, initiator feed rate and surfactant feed rate are used as optimization variables in the optimization formulations. The dynamic optimization problems were converted into nonlinear programming problem using the CVP techniques which were solved using efficient SQP (Successive Quadratic Programming) method available within the gPROMS (general PROcess Modelling System) software. The process model used for bulk polystyrene polymerization in batch reactors, using 2, 2 azobisisobutyronitrile catalyst (AIBN) as initiator was improved by including the gel and glass effects. The results obtained from this work when compared with the previous study by other researcher which disregarded the gel and glass effect in their study which show that the batch time operation are significantly reduced while the amount of the initial initiator concentration required increases. Also, the termination rate constant decreases as the concentration of the mixture increases, resulting rapid monomer conversion. The process model used for solution polymerization of methyl methacrylate (MMA) in batch reactors, using AIBN as the initiator and Toluene as the solvent was improved by including the free volume theory to calculate the initiator efficiency, f. The effects of different f was examined and compared with previous work which used a constant value of f 0.53. The results of these studies show that initiator efficiency, f is not constant but decreases with the increase of monomer conversion along the process. The determination of optimal control trajectories for emulsion copolymerization of Styrene and MMA with the objective of maximizing the number average molecular weight (Mn) and overall conversion (Xn) were carried out in batch and semi-batch reactors. The initiator used in this work is Persulfate K2S2O8 and the surfactant is Sodium Dodecyl Sulfate (SDS). Reduction of the pre-batch time increases the Mn but decreases the conversion (Xn). The sooner the addition of monomer into the reactor, the earlier the growth of the polymer chain leading to higher Mn. Besides that, Mn also can be increased by decreasing the initial initiator concentration (Ci0). Less oligomeric radicals will be produced with low Ci0, leading to reduced polymerization loci thus lowering the overall conversion. On the other hand, increases of reaction temperature (Tr) will decrease the Mn since transfer coefficient is increased at higher Tr leading to increase of the monomeric radicals resulting in an increase in termination reaction.

The synthesis of a number of alkyl esters such as methyl lactate, methyl decanoate, and ethyl benzoate via esterification in a reactive distillation is quite challenging. It is due to the complexity in the thermodynamic behaviour of the chemical species in the reaction mixture in addition to the difficulty of keeping the reactants together in the reaction section. One of the reactants (in these esterification reactions) having the lowest boiling point can separate from the other reactant as the distillation continues. This can result in a significant drop in the reaction conversion in a conventional reactive distillation whether it is a batch or a continuous column. To overcome this challenge, new different types of batch reactive distillation column configurations: (1) integrated conventional (2) semi-batch (3) integrated semi-batch (4) integrated dividing-wall batch distillation columns have been proposed here. Four esterification reaction schemes such as (a) esterification of lactic acid (b) esterification of decanoic acid (c) esterification of benzoic acid (d) esterification of acetic acid are investigated here. A detailed dynamic model based on mass, energy balances, chemical reaction, and rigorous thermodynamic (chemical and physical) properties is considered and incorporated in the optimisation framework within gPROMS (general PROcess Modelling System) software. It is found that for the methyl lactate system, the i-SBD operation outperforms the classical batch operations (CBD or SBD columns) to satisfy the product constraints. While, for the methyl decanoate system, the i-DWCBD operation outperforms all CBD, DWBD and sr-DWBD configurations by achieving the higher reaction conversion and the maximum product purity. For the ethyl benzoate system, the performance of i-CBD column is superior to the CBD process in terms of product quality, and conversion rate of acid. The CBD process is found to be a more attractive in terms of operating time saving, and annual profit improvement compared to the IBD, and MVD processes for the benzyl acetate system.