This thesis sets out to compare five well known design rules for the design of model reference adaptive systems. These are the M.I.T. rule, the Liapunov synthesis, the gradient rules of Dressier and Price, and the Monopoli design rule. A systematic performance comparison is made using two low order gain adjustment systems simulated on a digital computer. Step, sinusoidal and stochastic input signals are used and the system state variables and performance criteria are all expressed as dimensionless quantities. The results clearly demonstrate the superior performance of the Liapunov and Monopoli designs. The main disadvantage of other designs is that the dimensionless performance criteria is not a monotonic decreasing function of the dimensionless gain parameter. An analysis of the noisy case is then performed and this further points out the flexibility of the Liapunov synthesis. The next objective of the research is to extend the scope of application of the Liapunov designs. First a modification of the usual design algorithm for multivariable systems is made sc that a wider class of plants, in which the adjustable parameters may appear simultaneously in two or more elements of the plant and control matrices, can be readily treated. Examples are given to illustrate the design procedures and the typical performance of such designs. Secondly, the simultaneous parameter and state estimation system using model reference methods is investigated. Landau's hyperstability design, which can be shown to be equivalent to the Liapunov design, is preferred for this problem. To distinguish this design from the well known Generalized Equation Error (G.E.E.) design, we have called it the Stable Response Error (S.R.E.) design. The practical difficulty of using this globally stable design rule is found to be the implementation of the series (derivative) compensator. It is then shown how the problem is solved by using the state variable filters. Various simulation results substantiate the characteristics (namely unbiased estimates and very fast convergence) of the resulting design. The recovery of the simultaneous state estimates when the state variable filters are used with the S.R.E. design is then considered. With a moderate rate of convergence, the quality of the state estimates is found to be good. The main disadvantage of the S.R.E. method is that the range of parameter variations must be known a priori in order to design the series compensator which ensures the global stability. Finally, the extensions of the S.R.E. method to treat nonlinear and multivariable systems are presented. The main effort here is to find the appropriate structures of the estimation model. To conclude the thesis, a real case study is presented. This is the modelling of a nonlinear, third order internal combustion engine by a linear, first order model. The parameters of the model are adjusted according to the S.R.E. design rule. The practical results obtained demonstrate the feasibility of using the model reference method in a real physical system. Then some of the experiments are repeated with the estimation system based on the G.E.E. design rule. The results are found much inferior to those of the S.R.E. design.

Integrated Gasification Combined Cycle (IGCC) is considered as a viable option for low emission power generation and carbon-dioxide sequestration. Modelling development and simulation study is essential part for the process of IGCC design and development. This PhD project is aiming to conduct the modelling and simulation study of IGCC power plant by building sub-modules such as gasifier, water gas shift reactor, acid gas removal unit, gas turbine and HRSG, etc. and connecting these modules together for the whole process study. In addition, the impact for the integration of IGCC with activated carbons-based pressure swing adsorption carbon capture process is investigated by using a PSA model developed and validated by University of Birmingham. A simplified zero dimension gasification model is developed based on Texaco gasifier and validated by reference and industry data. The model development is based on mass balance, chemical equilibrium and energy balance. The prediction results for syngas contents concentrations are proved to be reasonably acceptable and the syngas contents changes with key input parameters changes are studied. The model is then used to generate a variable syngas stream to study the dynamic performance of the other sub-modules. A one dimension dynamic model based on Shell slagging gasifier is developed. The model can successfully show the characteristics of slag layers formation and the syngas stream change with response to input parameters change. By using step rise of oxygen input and steam blast input, the dynamic performance of syngas temperature, syngas contents, slag mass flow rate and slag layers thickness is analysed and compared. It is found that oxygen input show relative larger impact on gasifier operation than steam blast for the studied working conditions. Auxiliary modules in a gasification enabled plant and combined cycle power plant are modelled with Thermolib Software. Basic principles of this software are introduced. Simplified quench process, WGS with heat recovery, acid gas removal unit, gas turbine, HRSG and electrical generator are modelled by using the blocks from Thermolib. The simulation results show the dynamic changes of key output variables such as power output, syngas temperature and contents concentrations. PSA model developed by UoB based on ACs is introduced and a 9 step 8 beds cycle model is used for the integration with IGCC model. This PSA model can achieve 80.89% CO2 capture rate with 87.33% of N2 recovery rate without any additional equipment. N2 is used to represent H2 for the simulation. Four cases for IGCC integrated with carbon capture are studied for the energy penalty analysis. It is predicted that the efficiency loss for IGCC power plant with 80.89% carbon capture will be 10.96%. The limitations of using N2 to represent H2 for the PSA model are discussed and it is predicted the real efficiency loss will be lower than the simulation results.

The main objective of the research work presented in this thesis is the development of a single aerodynamic CFD code for the analysis of complex turbulent flow unsteady aerodynamics such as those encountered in horizontal and vertical axis wind turbines. The finite volume parallel CFD Optimized Structured multi-block Algorithm (COSA) research code solves the Navier-Stokes equations on structured multi-block grids and models turbulence effects with Menter's shear stress transport turbulence model. The novel algorithmic contribution of this research is the successful development of a Harmonic Balance (HB) solver which can reduce the run-time required to compute nonlinear periodic flow fields with respect to the conventional time-domain (TD) approach. The thesis also presents a semi-implicit integration based on LU factorisation and a successfully LAPACK libraries integration to massively improve the computational efficiency of the integration of the HB RANS equations and the turbulence model of Menter. The main computational results of this research are for two low-speed renewable energy applications. The former application is a turbulent unsteady flow analysis of a vertical axis wind turbine working in a low-speed turbulent regime for a wide range of operating conditions. The test case is first solved using the COSA TD turbulent solver to analyse and discuss in great detail the unsteady aerodynamic phenomena occurring in all regimes of this complex device. During the turbine rotation there is a generation of blade vortex shedding and wakes all around the rotor which interacts with the blades itself on the returning side. The most important features of the investigated devices were captured with CFD. In addition, a series of investigations have been conducted to analyse the effects of computational domain refinement, number of time steps per revolution and distance of the farfield boundary from the rotor centre on prediction accuracy. The solution of the turbulent flow solver is validated by comparing torque and power coefficients with experimental data and numerical solutions obtained with a state-of-the-art time-domain of commercial package regularly used by the industry and the Academia worldwide. A detailed selection of results is presented, dealing with the various investigated issues. Afterwards, the COSA HB turbulent solver is used to solve the problem and compare the HB resolution and speed-ups with the TD results. The main motivation for analysing this problem is to highlight the predictive capabilities and the numerical robustness of the developed turbulent HB flow solver for complex realistic problems with a strong nonlinearity and to shed more light on the complex physics of this renewable energy device. The latter application regards the turbulent unsteady flow analysis of horizontal axis wind turbine blade sections in yawed wind regime. The TD and HB turbulent flow analysis of a 164 m-diameter wind turbine rotor is performed. CFD represents an accurate design tool to get a better understanding of the physical behaviour of the flow field past wind turbine rotors and the importance of accurate design is increased as the machines tend to become larger. A study at 30% and at 85% blade section is carried out, allowing the analysis of the unsteady forces acting on two different blade sections. The aim of these analyses is to assess the computational benefits achievable by using the HB method for a common nonlinear flow problem and also to further demonstrate the predictive capabilities of the developed CFD system. The turbulent HB solutions highlight that is possible to obtain an accurate analysis as its TD counterparts can do. Moreover, the results highlight that the turbulent HB solver can compute the hysteresis force cycles of the turbine blade more than 10 times faster than the TD approach. The purpose of proving the turbulent COSA HB capabilities for studying the flow field of wind turbines rotor has been fully achieved and this research represent one of the first turbulent HB RANS applications to the analysis of periodic horizontal axis wind turbine flows, and the first application to vertical axis wind turbine flows.

Ultrasonic cutting technology has been introduced for surgical applications since the 1950s. Ultrasonic bone cutting applies high frequency mechanical vibration of a blade tuned at a specific frequency to make incision on human hard tissues. It offers advantages such as improved safety, smooth and precise cutting. To facilitate the design of high performance surgical ultrasonic bone cutting blades, this thesis is devoted to the modelling and designing of ultrasonic blades with an attempt to better understand the dynamic characteristics of blade and improve the conventional design method. A non-coupled vibration analytical model which deals with four modes of vibration, including longitudinal oscillation, flexural bending, lateral bending, and torsional vibration of ultrasonic blades, was proposed based on one-dimensional theories. The model allows the estimation of the modal parameters of a blade without establishing a 3D model. The experimental study of this model using a uniform beam and a sectional ultrasonic blade showed that the model predicted the modal frequencies of these structures with satisfactory accuracy. This suggested that the analytical model can be used as an alternative method to FEA in the characterisation of ultrasonic blades. Two coupled models, a parametric vibration model and a longitudinal-bending coupled vibration model, were proposed to study the coupled vibration of ultrasonic blades. The parametric vibration model formulated the coupled vibration using a lumped mass beam. This enabled the investigation of interaction between the vibration modes based on a simple one-dimensional structure. However, this model resulted in governing equations of considerable complexity, which were considered to be more suitable for the purpose of theoretical study instead of performance prediction. In addition, a longitudinal-bending coupled model was proposed in this study with an attempt to understand a type of coupled vibration that is commonly observed in ultrasonic blades of beam-like profile. The model was established by introducing an extra rotation moment in the one-dimensional bending equation. Two numerical iteration approaches, with their implementation and error analysis detailed, were proposed to solve this model. An optimal design method was proposed in this study with an aim to improve the conventional design process of ultrasonic blades by applying mathematical algorithms instead of the designers' experience and intuition to optimise the design. The method was introduced based on the concept of performance indicators that measure specific physical characteristics of a blade using mathematical functions. Four kinds of indicators, the frequency based, gain based, displacement based and stress based indicators, which evaluate the main dynamic characteristics of ultrasonic blades, were detailed in this study. The process of the optimal design method consists of three major stages: formulation, optimisation and verification. The concept of the proposed method is to maximise the blade performance through the optimisation of the performance indicators. This can improve the quality of design by making sure the most desired characteristics are achieved in the blade. A software toolkit was developed using the Abaqus script interface and Python language in order to apply this method in the design of ultrasonic blades. Five ultrasonic bone cutting blades with different types of cutting edges were designed using either the conventional or the optimal design method. These blades were subjected to ultrasonic cutting tests under various cutting conditions. Ultrasonic cutting performed on biomechanical samples, ovine femur and rat bones showed that the blades were capable of making incisions on bones without the requirement of large applied force. Positive linear correlation between the applied force and the cutting speed was found in the ultrasonic cutting carried out under static applied force, and positive linear relationship between the applied force and the surface temperature was observed in the ultrasonic cutting carried out under sliding motion. The presence of elevated temperatures in the cutting tests suggested that the blades require the application of cooling in ultrasonic bone cutting. The study confirmed that the proposed optimal design method was an effective design approach. The blades were designed with expected vibration characteristics and satisfactory cutting performance.

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically.

The value of integrating a heat storage into a geothermal district heating system has been investigated. The behaviour of the system under a novel operational strategy has been simulated focusing on the energetic, economic and environmental effects of the new strategy of incorporation of the heat storage within the system. A typical geothermal district heating system consists of several production wells, a system of pipelines for the transportation of the hot water to end-users, one or more re-injection wells and peak-up devices (usually fossil-fuel boilers). Traditionally in these systems, the production wells change their production rate throughout the day according to heat demand, and if their maximum capacity is exceeded the peak-up devices are used to meet the balance of the heat demand. In this study, it is proposed to maintain a constant geothermal production and add heat storage into the network. Subsequently, hot water will be stored when heat demand is lower than the production and the stored hot water will be released into the system to cover the peak demands (or part of these). It is not intended to totally phase-out the peak-up devices, but to decrease their use, as these will often be installed anyway for back-up purposes. Both the integration of a heat storage in such a system as well as the novel operational strategy are the main novelties of this thesis. A robust algorithm for the sizing of these systems has been developed. The main inputs are the geothermal production data, the heat demand data throughout one year or more and the topology of the installation. The outputs are the sizing of the whole system, including the necessary number of production wells, the size of the heat storage and the dimensions of the pipelines amongst others. The results provide several useful insights into the initial design considerations for these systems, emphasizing particularly the importance of heat losses. Simulations are carried out for three different cases of sizing of the installation (small, medium and large) to examine the influence of system scale. In the second phase of work, two algorithms are developed which study in detail the operation of the installation throughout a random day and a whole year, respectively. The first algorithm can be a potentially powerful tool for the operators of the installation, who can know a priori how to operate the installation on a random day given the heat demand. The second algorithm is used to obtain the amount of electricity used by the pumps as well as the amount of fuel used by the peak-up boilers over a whole year. These comprise the main operational costs of the installation and are among the main inputs of the third part of the study. In the third part of the study, an integrated energetic, economic and environmental analysis of the studied installation is carried out together with a comparison with the traditional case. The results show that by implementing heat storage under the novel operational strategy, heat is generated more cheaply as all the financial indices improve, more geothermal energy is utilised and less fuel is used in the peak-up boilers, with subsequent environmental benefits, when compared to the traditional case. Furthermore, it is shown that the most attractive case of sizing is the large one, although the addition of the heat storage most greatly impacts the medium case of sizing. In other words, the geothermal component of the installation should be sized as large as possible. This analysis indicates that the proposed solution is beneficial from energetic, economic, and environmental perspectives. Therefore, it can be stated that the aim of this study is achieved in its full potential. Furthermore, the new models for the sizing, operation and economic/energetic/environmental analyses of these kind of systems can be used with few adaptations for real cases, making the practical applicability of this study evident. Having this study as a starting point, further work could include the integration of these systems with end-user demands, further analysis of component parts of the installation (such as the heat exchangers) and the integration of a heat pump to maximise utilisation of geothermal energy.

Magnetic non-destructive methods utilising the Magnetic Flux Leakage (MFL) and Magnetic Barkhausen Noise (MBN) phenomena are widely used in the evaluation of the structural integrity of steel components. The MFL method is effectively applied for in-service flaw monitoring of oil and gas pipelines, fuel storage tank floors and rails; whereas the MBN method, due to high sensitivity of Barkhausen emission to residual and applied stress, has become one of the most popular NDE tools for investigating this condition of steels. Despite the affirming research and successful applications, which helped these methods to gain acceptance as a viable non-destructive tools, there is still a requirement for establishing a quantitative links between magnetic and mechanical properties of steel which would enable their further understanding and optimisation. In this thesis the applications of MFL and MBN methods for flaw and stress detection are analysed via analytical and numerical modelling. A new model relating the MBN amplitude and stress for materials having different magnetostrictive behaviour under load is proposed and validated in the quantitative stress evaluation of different grades of steel. Moreover, a new method for determining depth dependence of stress from measured magnetic Barkhausen signals is presented. A complete set of newly derived equations describing the detected Barkhausen signals in terms of the actual emissions that are generated inside the material and how these appear when they propagate to the surface is given. The results from finite element modelling of magnetic flux leakage signals above unflawed and flawed rails energised in various directions are presented. These results enabled to identify the most effective current injection procedure and optimise the probability of transverse flaw detection in the rail inspection. The agreement between modelled and measured electromagnetic signals indicating presence of transverse rail defects has been justified.

This thesis covers two main areas of investigation, the production and recovery of process dusts formed in the steelmaking industry, and secondly the study of the utilisation of coals for injection in a blast furnace and during co-firing with biomass in a utility boiler. These are linked by an overall aim to research the environmental and economic sustainability of industrial processes through increased process efficiency, decreased environmental impacts, and increased recovery of waste. It comprises a summary of the research contribution from six first-author peer reviewed journal publications and nine supplementary contributions for the submission of a PhD by published works. Process dust research was carried out on a 300t vessel requiring the development of a novel industrial scale isokinetic sampling methodology, capable of sampling frequently enough to measure and analyse mass flow profiles and zinc mass contamination profiles at a higher level of detail than in prior research. A new understanding of the impact of inprocess iron ore additions and waste oxide additions were correlated with additional dust and zinc mass peaks. This methodology was also used to prove that a new process change involving a galvanised scrap holding stage could be applied to successfully reduce the zinc contamination. Research into a modified hydrometallurgical leaching method for blast furnace dust gave high zinc extraction, but with low iron extraction, by the novel utilisation of the substituent group effect of carboxylic acid leaching. Further research also identified that improvements in the zinc extraction selectivity could be achieved using a non-aqueous solvent to utilise the Lewis acid effect. In terms of solid fuel utilisation, factors such as the physical properties, cost, and availability result in end users blending coals to meet their needs. The use of higher volatile matter coals was found to benefit blends with low volatile coal in the context of the blast furnace, but research conducted on a 500MW utility boiler showed that carbon monoxide and dust levels increase. Although grinding coals to a pulverised specification has been proved to benefit utilisation, new findings show that the additional grinding alters the surface chemistry and reactivity of many coals and was related to reduced burnouts compared to some larger particle size specifications. Research on industrial processes is challenging, but these papers aim to address sustainability issues in terms of the efficient use and recovery of materials.

This thesis examines the influence of asperities such as found on the teeth of gears and discs, and failure mechanisms associated with rough surface Elastohydrodynamic Lubrication (EHL). The principal outcomes of the research provide a good insight into fatigue life, residual stress effects, damage prediction and surface contact failures. In particular, the study is intended to provide understanding into the residual stress distribution resulting from plastic deformation of surface asperities in the running in process. The residual stress is then added to the asperity elastic stress distribution and examined in detail to see the effects on fatigue damage and fatigue life. So, a theoretical model has been developed to assist design against the residual stress effect and surface contact fatigue, such as micropitting. The technique used in the study starts with developing an elastic plastic model of the rough surface by using the Abaqus Finite Element analysis software package. This is a nonlinear problem and ranges of applied loads have been applied to the as-manufactured surfaces causing the asperity features to experience varying degrees of plastic deformation. The pre and post running roughness profiles are studied in order to assess the level of plastic deformation actually occurring at significant surface asperity features by aligning the pre and post running profiles. This results in a new technique that has helped to identify the level of plastic deformation occurring in the practice, and also to make a comparison with FEA contact analysis for the same asperity features to identify the appropriate residual stress field. The residual stress field associated with the plastic deformation was extracted and evaluated. The extracted residual stress field was transferred to a form that facilitated IV inclusion in stress evaluation code to obtain the stress history for the material subject to loading in an EHL contact. The research carried out considers surface fatigue analysis with and without a residual stress field, so as to establish the influence of asperity plastic deformation on the fatigue properties of the surface. All the work is based on numerical simulation of surface fatigue failure in EHL situations and carried out numerically. The procedure can be applied quickly and gives the opportunity to apply several models and investigate the influence of all the model parameters on material deformation and fatigue life.

No description available.