Current research efforts in the areas of automotive control aim at developing new control algorithms so engine can work efficiently with different fuel compositions. Progressing in this direction, this thesis pioneers and researches novel control strategies to reduce the engine emissions gasses, Carbon Dioxide (CO2), Oxygen (O2), Carbon Monoxide (CO) and Nitric Oxide (NOx), while keeping optimum performance with unknown fuel mixtures. A two-zone engine combustion model is developed and thoroughly validated against the computational data from commercial engine simulation packages. The engine model is suited for the development and testing of control systems. The simulation uses the following fuel mixtures: isooctane (C8-H18), methanol (C1-H4-O1) and ethanol (C2-H6-O1). The results obtained provide better understanding of the control parameters, including fuel-to-air ratio, ignition timing, exhaust-valve timing and intake-valve timing. Moreover, the model facilitates control design. The novel engine controller is studied on the fuel composition as the additional parameter where such parameter has not been widely considered in engine control research. Efficient methodologies to estimate the original fuel composition by using the exhaust gas composition obtained from the engine are proposed and investigated. Two novel approaches based on feed-forward neural network and Adaptive Neuro-Fuzzy Interface System (ANFIS), respectively, are proposed. The portion of mixture for Isooctane-Methanol and Isooctane-Ethanol are effectively calculated. Moreover, results suggest that the feed-forward neural network outperforms the ANFIS approach and that the performance of the fuel estimator is stable in the continuous time process. Further in this research, a Multi-Input-Multi-Output (MIMO) engine control system is developed. The methodology used is a system identification employing a state-space model. In order to reduce the complexity of the state-space model, the developed AI fuel estimator is used to facilitate on the model reduction by feeding gains to controllers for the individual components. In addition, it uses the linear quadric regulator (LQR) method to find the closed-loop gain in the development of the closed-loop control system. The above techniques have been evaluated and results show that the controller is able to identify the minimum levels of the emission gases in terms of CO2, O2, CO and NOx in a continuously changing engine speed.

Transitional flow of fluids has been a subject of great interest in the field of aerodynamics. Reduction of drag through maintaining laminar flow and delaying the onset of boundary layer transition has become one of the key areas of research in this field. Laminar flow control has been achieved through the use of active and passive devises. However, a number of these solutions are difficult to implement because the mechanisms of the controlling techniques are not fully understood. This research focuses on comparing the aerodynamic performance of a number of novel solutions to obtain passive laminar flow control i.e. Natural Laminar flow control. Experimental work was undertaken on a flat plate with different leading edges varying from aspect ratio AR1 to AR12. At the same time, flat plate transition simulations were conducted for aspect ratio AR1 to AR20. The effects of these leading edges were recorded and compared with the results obtained through CFD. ANSYS FLUENT was the chosen solver and the CFD model was validated against a number of existing test cases from literature as well as our own cases. The simulations were performed using the [gamma]-Re[theta] model. The effects of changes in turbulence intensity and the velocity of incoming flow were also recorded to fully understand the transitional phenomenon of the flow. The simulations showed that AR20 is 4% better than the default AR12 leading edge configuration for the same velocity and turbulence intensity of the incoming flow. The use of wavy surfaces to delay transition has been undertaken in this research endeavour. The surface of the plate had a number of different wave configurations consisting of 32, 64,128 and 256 waves along a 2.4 meters long plate. For each of these wave configurations, the amplitude of the wave was changed and the influence of the amplitude change was studied. The presence of a wavy surface with the amplitude lesser than the laminar sub boundary layer resulted in delaying transition. In some cases, the presence of an extremely wavy surface i.e. 256 waves proved to be the best configuration and was roughly 4.1% better than the flat plate configuration. However, as the velocity increases the impact of a higher wavenumber plate starts to diminish. When the velocity is maintained 30 m/s and 50 m/s respectively, the 256 wave configuration has the best aerodynamic performance. When the velocity is increased to 80 m/s, the trend reverses and a 32 wave plate tends to have the best performance. Forward Facing steps find applications in aircraft wing repairs through the use of patches. The presence of a Forward Facing Step (FFS) to delay transition has also been discussed. Steps were placed at crucial locations within the laminar boundary layer on the flat plate in the research. Step heights were determined by using a constant-boundary thickness to step height ratio (o h). The results shown that the position of the step about 100 mm from the transition point with a o h ratio of 12 helped delay transition by roughly 3.2%. The effects of a plate moving in the direction perpendicular to the flow was studied experimentally and quantified. The influence of the motion on boundary layer transition was to bring forward the transition onset location. The aerodynamic performance was found to be worse when the flat plate is subjected to this motion as compared to a stationary flat plate.

Rapid Prototyping & Manufacturing has recently emerged as a new manufacturing technology that allows the rapid creation of three-dimensional models and prototypes. It automates the fabrication of solid objects directly from designs created by CAD systems, without part-specific tooling or human intervention. From visualising designs to generating production tooling, the Rapid Prototyping & Manufacturing gives the advantages needed in today's competitive environment. There are many different rapid prototyping systems available. This proliferation of rapid prototyping systems has, to some degree, created some confusion in the market place. Whether the potential customer or user is thinking of using a rapid prototyping bureaux or purchasing a rapid prototyping system, the increasing number of systems coming onto the market and the ever improving capabilities of existing systems presents a significant problem in choosing the optimum system for a particular need. The aim of this project is to develop an intelligent rapid prototyping system selector based on the feature extraction from STL files to automatically select the most suitable rapid prototyping system for a given prototype. The combination of STL model feature extraction and expert system selection is an effective method of rapid prototyping process selection. By analysing the object's STL file, the object's feature representations are extracted. These features together with the user's requirements are used to determine the most suitable system on which to build, or the most suitable system to buy. Mathematical models for computing build time, accuracy, cost and mechanical properties are established. A knowledge-based system is developed for rapid prototyping system selection. An integrated software package for STL file feature extraction, rapid prototyping system simulation and knowledge-based rapid prototyping system selection has been developed.

Intermetallic NiAl has the potential to be used for elevated temperature applications. Self-propagating high-temperature synthesis (SHS) has been developed as a relatively simple route to obtain intermetallics. To date different ignition techniques have attempted to synthesize NiAI and produce coatings. Induction heating has been used to produce coatings and differs from conventional heating techniques in which the material is heated from the inside. This paper considers the use of induction heating to preheat and ignite the synthesis directly and investigates the effect of induction parameters on the phase transformation, microstructures and properties of Ni/ Al compacts synthesized by SHS. During synthesis the temperature profiles were measured with infrared thermometers and a high resolution thermal image camera to monitor the reaction process. Scanning electron microscopy (SEM), Energy Dispersive X-ray test (EDX) and X-ray Diffraction (XRD) were used to characterize products. The mechanical properties of the products were evaluated by measuring hardness. The results show that single phase NiAI can be produced by induction heating whilst processing parameters such as heating rates and green densities have a significant effect on the properties and structures of the sintered products. To further improve the mechanical properties and control the deformation of NiAI during combustion reaction caused by the formation of liquid, Al[sub]2O[sub]3 was used as an additive and dilution agent. The results show that single phase NiAI can be produced by this process regardless of the addition of Al[sub]2O[sub]3. However, the addition of Al[sub]2O[sub]3 is found to have a significant effect on heating rates, combustion behaviour and properties of the synthesized products. Additionally, there is a critical concentration for Al[sub]2O[sub]3 above which the compacts cannot be ignited by induction heating. Tests showed that the addition of Al[sub]2O[sub]3 can significantly improve the mechanical properties of NiAl. The synthesis of TiC and NiAl/TiC composites using induction heating via SHS process was also studied in this project. High density NiAl/TiC composites and two-layer TiC-NiAI structures were successfully produced using this process. The results show that the reaction was complete and that stoichiometric products of NiAI and TiC were produced. The properties of the NiAl/TiC composites were found to be functions of composition and processing parameters. The reaction mechanism was analyzed using temperature monitoring, thermodynamic analysis and microstructure investigation. A computer simulation using ANSYS was carried out to investigate the effects of processing parameters on the temperature distribution in induction heating. Experimental work has shown that the simulation results had a good agreement with experimental tests and the simulation can be applied to explain the heating behaviour during induction heating. The simulation was also used to investigate the solidification process to understand the cooling process during SHS.

The original turbulent energy cascade of eddy dissipation concept (EDC) has been extended to the LES framework, assuming that there is always a structure level on which the typical length scale is equivalent to the filter width of large eddy simulation (LES). The velocity scale on this structure level could be calculated from the sub-grid scale (SGS) kinetic energy, provided that this kinetic energy transport equation is solved in LES. All other quantities would thus be calculated on this structure level according to the general formulations from the original turbulent energy cascade. Based on this known structure level, the total kinetic energy and dissipation rate could be estimated with the integral length scale being assumed to be equivalent to the characteristic length of fire plume. Consequently, the Kolmogorov time scale and the integral time scale could also be calculated and then applied in the soot model development. The laminar based smoke point soot model (SPSM) is also extended to the LES framework. The filtered soot mass fraction transport equation is solved with the thermophoresis term neglected. The filtered soot formation rate is treated using the concept of partially stirred reactor (PaSR). This rate is thus associated with the laminar based soot formation rate substituted with the filtered properties through the expression of K. Note that in K the soot formation chemical time scale is assumed to be proportional to the laminar smoke point height (SPH) while its turbulent mixing time is supposed to be the. geometric mean of the Kolmogorov time scale and integral time scale. Furthermore, a new soot oxidation model is developed by imitating the gas phase combustion model, i.e. EDC, as the soot particles are assumed to be the solid phase of the fuel. Note that the turbulent mixing time scale for soot oxidation has been chosen to be the same as soot formation. The soot formation and oxidation models are coupled to treat the effect of soot on the fuel distribution and energy transport. The approaches to calculate flame height, radiative fraction, and surface emissive power (SEP) have also been developed for sooty flames. The models and approaches mentioned above are implemented into FireFOAM, which is a fully compressible solver based on the platform of OpenFOAM. A series of fire scenarios, involved with different fuels including methanol, methane, heptane and toluene, and with different scales ranging from 30 em to 56 m, are performed for validation studies. The detailed comparisons, such as mean velocity and its fluctuation, mean temperature and its fluctuation, soot volume fraction and its fluctuation, turbulent heat flux, time scales and length scales, flame height, radiative fraction, SEP and so on, between predictions and measurements demonstrate the capability of the current models.

Advance Composite Materials have found various applications due to their unique properties over the past years. Properties such as high specific strength and stiffness, corrosion resistance and fatigue resistance that can be adjusted to specific requirements have made these materials as one of the main candidate considered during design process. The high energy absorbing capabilities of FRP composite materials is one of the main factors in their application in automotive and aerospace structures. They also provide other functional and economic benefits such as enhanced strength, durability, weight reduction and hence lower fuel consumption. The brittle nature of most composites accompanying other forms of energy absorption mechanisms such as fibre breakage, matrix cracking, deboning at the fibre-matrix interface and especially plies delaminations which play important roles on progressive failure mode and energy absorption capability of composite structures. Delamination which is known as principle mode of failure of layered composites due to separation along the interfaces of layers is one of the main concerns in designing of composite structures. This factor plays an important role on progressive failure mode and energy absorption capability of composite structures. Delamination can occur due to various reasons such as impact, imperfection in manufacturing, high stress concentration, environmental effects and post-processing. In this project an advanced manufacturing methods will be applied to stitch carbon-fibre composite testing specimens using sustainable natural flax fibres. The natural fibres running through the thickness of laminated composite structures will increase the resistance to crack propagation and consequently the energy absorption capability of composite absorbers. Natural flax fibres have the main advantage over the synthetic fibres (e.g. carbon and glass) of providing both resistance and progressive failure (effective crack growth resistance) in the wall of composite box absorbers. Progressive failure can provide high energy absorption in a controllable behaviour which reduces the main injuries and death during a crash event.

In this study, the effect of nozzle geometries and processing controls during Flame Spray Pyrolysis (FSP) process were investigated theoretically on a pilot-scale reactor (production rates up to 5 kg h-1 zirconia) and lab scale reactor (production rates up to 74 g h-1 titania). The focus was on the controlled synthesis and continuous production of nanoparticles at high production rates as well as the study of particle formation and growth inside spray flames. The computational models developed in this study were validated by the measured data available from literature for particle dynamics in spray flames and used to process optimization and reactor design. Chapter one presents an overview of applications of nanoparticles and recent advances in synthesis of nanoparticles by Vapour-fed Flame Synthesis (VFS) and Flame Spray Pyrolysis (FSP). A general introduction on the formation and growth of nanoparticles in the gas-phase synthesis of nanoparticles is presented with emphasis on the mechanisms that control the particle morphology after the initial formation of the monomers. Finally, some existing models in the field are presented and compared. The mathematical models adopted in this study are fully described in chapter two. Several numerical models were developed to predict dynamic viscosity and surface tension of precursor solutions, the pumping pressure of precursor solution, the sauter mean diameter (SMD) of droplets during atomization and the particle growth inside the flame by coagulation and sintering. These models were coupled with the computational fluid dynamic (CFD) code to simulate FSP process. The models were validated by comparison with experimental data developed in this study and literatures. In chapter four, the effect of reactor geometries and processing parameters on the temperature and velocity profiles, droplet evaporation and particle growth were predicted using the validated computational models. The results show that the oxidant/dispersion gas gap size and the oxygen content of oxidant/dispersion gas have a big impact on the flame structure and ultimately the particle growth in the flame. In chapter five, investigation is performed to examine the effect of process parameters on the growth of zirconia particles at low, medium and high precursor concentrations. The results show that fine nanoparticles could be synthesized at low precursor concentration and medium production rates while further studies are needed at higher precursor concentrations and production rates. Therefore, in the sixth chapter, emphasis is placed on industrial production of nanoparticles at higher precursor concentrations. A process operation window for industrial-scale production of zirconia nanoparticles using medium and high precursor concentration was developed. The possible solutions to optimize pump performance and atomization quality at industrial scale production rates using high precursor concentration in FSP were investigated. The quantitative results given in this section can be used as a design guide for a prototype industrial FSP nanoparticle production line. Chapter seven extends the work above and investigates the possibility of quenching the FSP flames at industrial scale production rate by using different reactor configurations. The simulations show how choosing the right configuration and process parameters can affect the characteristics and collection of particles at above the burner. In chapter eight, the applicability of the developed approach for particle simulation of zirconia in the previous chapters is examined for flame spray synthesis of titania. In addition, a series of parametric studies was performed to assist better understanding and control over FSP synthesis of Ti02 nanoparticles. In the ninth chapter, a short summary is given along with recommendations for future investigations.

The present computation investigates a turbine blade with trailing-edge cutback coolant ejection designs, aiming for a comparison study of aerothermal performances such as discharge coefficient and film cooling effectiveness due to the change of trailing-edge geometries and blowing ratios. The shear-stress transport (SST) k-w turbulence model is adopted and numerical studies are carried out by two-stage investigations:- firstly, validation of an existing cutback blade model with staggered circular pin-fins array inside the cooling passage that has been extensively studied by other researchers and predicted internal passage discharge coefficient and film-cooling effectiveness along the cutback surface are compared to experimental measurements. RANS/URANS and DES are applied during this stage; secondly, further investigation of four main cases considering different key design parameters such as the ratio of lip thickness to slot height (t/H = 0.25, 0.5, 1.0 and 1.5), the design of internal features (i.e. circular pin-fin array, elliptic pin-fin array, and empty duct), the coolant ejection angle (alpha = 5 degrees, 10 degrees and 15 degrees). In addition, a trailing-edge cutback model with suction-side (SS) ─ pressure-side (PS) walls and lands is considered to create a more realistic blade design. The results show that both steady and unsteady RANS predictions are able to produce discharge coefficients in fairly good agreement with test data, but not the film-cooling effectiveness on cutback surfaces which over-predicts in far-field wake region. Further prediction improvements can be made by using unsteady DES approach. In terms of film-cooling effectiveness and shedding frequency, computational results indicate a strong dependency on those aforementioned key design parameters. This film-cooling effectiveness is strongly affected by turbulent flow structures along the cutback region, which is representing the dynamic mixing process between the mainstream flow and the ejecting coolant from the slot-exit. The use of elliptic pin-fin inside the cooling passage and thin lip thickness could improve the effectiveness of film-cooling. The increase of ejection angle yields almost near unity cooling effectiveness along the protected wall. Significant improvements on cooling performance are also achieved with higher blowing ratios. Computations of the trailing-edge cutback cooling with pressure-side (PS) and suction-side (SS) wall demonstrates that performance of the case without lands is better than that of the case with lands by discrepancy up to 18% in terms of overall-averaged film-cooling effectiveness. The blade trailing-edge design with lands causes a rapid decay of the averaged film-cooling effectiveness.

Truck manufacturers are currently under pressure to reduce pollution and cost of transportation. The cost efficient way to reduce CO[sub]2 and cost is to reduce fuel consumption by adaptation of the vehicle speed to the driving conditions - by heuristic knowledge or mathematical optimisation. Due to their experience, professional drivers are capable of driving with great efficiency in terms of fuel consumption. The key research question addressed in this work is the comparison of the fuel efficiency for an unassisted drive by an experienced professional driver versus an enhanced drive using driver assistance system. The motivation for this is based on the advantage of such a system in terms of price (lower than driver's training) but potentially it can be challenging to obtain drivers' acceptance of the system. There is a range of fundamental issued that have to be addressed prior to the design and implementation of the driver assistance system. The first issue is related to the evaluation of the correctness of the prediction model under development, due to a range of inaccuracies introduced by slope errors in digital maps, imprecise modelling of combustion engine, vehicle physics etc. The second issue is related to the challenge in selecting a suitable method for optimisation of mixed integer non-linear systems. Dynamic Programming proved to be very suitable for this work and some methods of search space reduction are presented here. Also an analytical solution of the Bernoulli differential equation of the vehicle dynamics is presented and used here in order to reduce computing effort. Extensive simulation and driving tests were performed using different driving approaches to compare well trained human experts with a range of different driving assistance systems based on standard cruise control, heuristic and mathematical optimisation. Finally the acceptance of the systems by drivers been evaluated.

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