The potential impact of inlet flow distortion on the stability and performance of aircraft engines remains a key concern for engine-airframe integration. Current and future configurations, such as Unmanned Combat Air Vehicles (UCAVs), and possible civil aircraft with large rear-mounted engines, feature closely-coupled intake and airframe aerodynamics. Such configurations are susceptible to the ingestion of streamwise vorticity generated upstream on the aircraft. There is a dearth of understanding of this ingestion process which, crucially, determines the nature of the flow distortion presented to the turbomachinery. To assess the risk of engine stability and performance deterioration, it is therefore necessary to understand and model the vortex ingestion process. This research provides a novel application of Stereoscopic Particle Image Velocimetry (Stereo PIV) to obtain quantitative measurements of a streamwise vortex inside a contracting intake capture streamtube. The experiments were conducted in the 8’x6’ lowspeed wind tunnel using a 1/30th scale intake model. Vortex generators were employed to create a streamwise vortex in the flow upstream of the intake. The streamtube contraction levels, vortex generator type, and vortex generator configuration were varied to establish fundamental understanding on the flow physics of vortex ingestion. The vortex experiences notable levels of intensification as it passes through the contracting streamtube. The evolution of the vortex is strongly dependent on the streamtube contraction levels, the initial characteristics of the vortex prior to ingestion, and the trajectory that the vortex follows inside the capture streamtube. In addition, detailed studies have been performed using Computational Fluid Dynamics (CFD) to establish an approach to simulate vortex ingestion flows. A number of guidelines have been developed using experimental measurements to ensure that the flow physics of vortex ingestion are captured. This approach permits vortex ingestion simulations to be performed to evaluate the inlet flow distortion characteristics in full-scale intake flows.

This thesis outlines the development of a one-dimensional simulation of a 2.4-litre diesel engine used on a Wrightbus hybrid bus. The engine model, created using Ricardo WAVE, was validated against an extensive experimental data set and was shown to accurately predict key performance parameters such as in-cylinder pressures and fuel consumption. A turbogenerator was subsequently included on the exhaust line of the engine model and used to simulate the effects of recovering otherwise wasted energy. The turbogenerator size was optimised and a device that produced 7kW was shown to offer up to 2.7% improvement in brake specific fuel consumption (BSFC) at full engine load. The turbogenerator model was then run across a series of engine operating points and a modified engine BSFC map was produced which included the effects of the turbogenerator. This map was then used in a hybrid vehicle model, which simulated the diesel-electric hybrid bus platform. The hybrid vehicle model was modified to include the turbogenerator and the effects of recovering waste heat were then investigated over several real-world drive cycles. An improvement in fuel efficiency of 2.4% was shown by using the turbogenerator on one urban drive cycle, while after optimisation of the hybrid bus platform, the benefit increased to almost 4.4% over a mixture of urban and standardised test cycles.

There is currently considerable interest in new engine technologies to assist in the improvement of fuel economy and the reduction of carbon dioxide emissions from automotive vehicles. Within the current automotive market, legislative and economic forces are requiring automotive manufacturers to produce high performance engines with a reduced environmental impact and lower fuel consumption. To meet these targets, further understanding of the processes involved in in-cylinder combustion is required. This thesis discusses the effect of fuel spray structure, flame propagation and turbulent flow on DISI engine combustion. To investigate these flow processes within the fired single cylinder Jaguar optical engine a number of optical measurement techniques have been used, including high speed laser sheet flow visualisation (HSLSFV) and high speed digital particle image velocimetry (HSDPIV). Results obtained from dual location flame imaging has provided further understanding of the relationship between flame growth, engine performance and cycle-to-cycle variation. Detailed correlation analysis between flame growth speed and engine performance parameters demonstrated that it is the flow conditions local to the spark plug at the time of spark ignition that have greatest influence on combustion. It was also demonstrated that further gains in engine performance and stability can be achieved by optimising the fuel injection timing. The temporal and spatial development of flow field structures within the pent-roof combustion chamber at the time of spark ignition were quantified using HSDPIV. Decomposition analysis of the raw velocity data enabled the relationship between specific scales of turbulent flow structure and engine performance parameters to be investigated. Correlations between the high frequency turbulence component and pressure derivatives are shown, demonstrating that it is the frequencies of motion >600 Hz that have the greatest influence on early flame development and therefore rate of charge consumption, engine performance and combustion stability. A series of double fuel injection strategies were devised to investigate the potential for using the fuel injection event to influence flow field structures within the cylinder. Results demonstrated that while the fuel injection event had limited impact on bulk flow structures, there was an increase in turbulence post fuel injection, depending on the timing of the second injection pulse. However, this advantage was not sustained throughout the compression stroke to have significant impact on combustion. The final stage of research investigated fuel spray structure, flame propagation and charge motion at fuel impingement locations, comparing a single and triple injection strategy. A triple injection strategy is proposed that results in an improvement in the levels of fuel impingement on combustion chamber walls and a reduction in the high luminosity regions within the flame. Consequently, adopting the multiple injection strategy highlighted the potential for reducing unburned HC emissions and soot formation within homogeneous charge DISI engines.

Kinetic modelling of aftertreatment systems have become a major part of catalyst evaluation and development. A large number of kinetic models have appeared in literature over the past number of decades, varying in application from single reaction models to models capable of simulating a full reaction set for automotive application. All the kinetic models however use either one of two approaches, global kinetics or microkinetics. The kinetic model developed in this work uses both kinetic approaches, allowing the user to select the kinetic approach required for the simulation for each individual reaction. The work presented in this report details the theory behind the kinetic model and development of the micro kinetic and dual kinetic routines. The model is validated against a range of experimental data consisting of end pipe, spatially resolved and vehicle data. Simulations conducted using the -kinetic model proves accurate for each of the kinetic approaches used (global kinetics, micro-kinetics and dual kinetics). with a comparison of each kinetic approach conducted throughout. Integrating micro-kinetics into the kinetic model increased the accuracy of the simulations for the conditions conducted, providing more information for the CO oxidation than previously available using the global kinetic approach. The dual kinetic approach incorporating global kinetics and micro-kinetics provided more accurate results than a purely global kinetic model. The model has been developed to support the further development and expansion of the micro-kinetic reactions.

This thesis describes experimental and theoretical investigations into oil stiction effects in automatic compressor valves. The experimental programme involved the testing of disc valves in a compressor in which the working fluid could be varied and the oil circulation controlled. The main purpose of the experiment was to measure, in as direct a manner as possible, the time lag in valve opening due to the presence of oil between the valve disc and its seat. The design of the apparatus also allowed the pressure difference across the valve, required to open it, to be measured. These tests were carried out under various conditions of back pressure and rate of change of pressure. The experimental progranme also involved the measurement of the stiction force in a test rig in which the parameters of seat geometry, oil viscosity, and rate of application of lift on the valve disc could be controlled. The stages involved in the rupture of the oil film are described and coefficients obtained from the analysis of these test results are utilised in conputer programs which simulate the stiction process in a working compressor. The theoretical model, for the simulation of the phenomena during the initial opening phase of the valve, is based on the Navier-Stokes Equations lasing thin film approximations. The theoretical model is programmed for use in a digital computer. Subroutines in the programs take account of surface tension and cavitation in the oil film. The model is not completely analytical. As stated above, it utilises a number of experimentally determined coefficients, modified to suit conditions in a working compressor. Both the effect of rate of change of pressure across the valve and flexure of the valve are shown by the mathematical model to be significant. Trends indicated by variation of these parameters and others, such as seat geometry and oil viscosity, are mirrored by experimental results.

No description available.

No description available.

Heavy goods vehicles (HGVs) are synonymous with high fuel consumption due to their weight and bluff nature. At a time when fuel prices are high and haulage operators have an environmental responsibility to reduce CO2 emissions, there is great interest in the possible methods of curbing fuel consumption. With up to 50 percent of HGV fuel consumption attributed to aerodynamic drag, there are improvements which can be made to the design and manufacture of haulage trailers in order to reduce fuel consumption and reduce CO2 emissions. Various design modifications, both those able to be retrofitted and only possible at the point of manufacture, are tested using computational fluid dynamics (CFD), to establish the potential drag reduction when compared to a baseline case. These are evaluated in both normal and side-wind conditions. The baseline case is modelled to represent a HGV combination that is representative of the average trailer in operation in the UK industry. It is found that in combination, the trailer modifications analysed can reduce the aerodynamic drag of the overall vehicle geometry by up to 26%. Additional geometry is also tested that is specific to the UK industry due to the lack of a limitation on overall vehicle height. These tests highlight the consequences of unchecked vehicle geometry and the effects that inappropriate truck and trailer matching can have on the overall drag contribution of the vehicle. These cases along with the comparative and baseline cases show that the ow characteristics of the vehicle geometry differs greatly between normal and conditions of side-wind. This in turn dictates the e effctiveness of the geometry modifications dependent on their intended area of drag improvement, and can inform design decisions when incorporating these at the point of manufacture.

Technological developments are causing a proliferation of computing devices in every day life, with the availability of high compute power, small size, and the capability for wireless communication leading to consideration of how to off-load human tasks to devices which can manage themselves. Similarly, the science of how artificial systems can operate in an environment, sensing, reasoning, and taking action, has become increasingly mature. These developments lead to the opportunity for artificial entities to undertake activities in the real world, but facing significant challenges in reasoning about the environment and social interaction with humans. The concept of artificial entities operating amongst humans raises a set of socio-cognitive problems, that is, issues where reasoning is required both about the environment and human activity, raising the challenge of the need to understand the cultural and contextual aspects of a situation. Further challenges stem from giving intelligent entities the autonomy to pursue their own goals. Firstly, how to manage the situation when, in simple terms, an entity does not know what to do, for example it has no appropriate knowledge of how to handle the situation it finds itself in, or enters into a conflict which it cannot resolve by itself. Secondly, we consider the challenge of how an entity's pursuit of its own goals can be balanced against the greater social welfare, where an entity may be taking action which is to the detriment of the wider population, or where coordination of its action could result in benefit for others. In broad terms, we consider these as issues relating to an entity's understanding of the environment in which it operates, and we adopt the concept of Situational Awareness as a means to analyse this understanding. We consider an entity's understanding as being built up from low level perceptions (where events in the environment are sensed) to an increased understanding at the comprehension level (where possible meanings of the perceptions are generated) through to a high level projection understanding (of the likely future state of the environment). We refine these issues into a number of problem statements which we see artificial socio-cognitive systems (ASCS) facing, and propose the approach of attempting to build an explicit representation of SA at different levels, and how to move data, information and knowledge upwards through them. We then explore this by grounding experimentation in the domain of intelligent vehicles. This problem space contains a number of characteristics which make it suitable for our work: there is complex human interaction, rules which may not completely govern the situation or be adhered to, and technological developments in autonomous vehicles, all of which can be represented in scenarios in order to assess our approach. We use this domain to illustrate our proposed approach, and rather than develop solutions for this specific domain we remain abstract as far as possible in order to be able to offer conclusions that can find application in other domains. We describe a framework where distributed components are brought together to support investigation into these problem areas. A generalised message exchange approach is adopted, with messages containing additional semantic annotation such that the emphasis for appropriate handling lies with the consumer. Concerning what is exchanged, we consider knowledge and understanding in terms of Situational Awareness levels as a means of allowing components to communicate at an appropriate level and prevent communication overload due to exchanging the wrong kind and the wrong volume of data. We present scenarios that have been constructed to illustrate problematic aspects in the domain that are reflections of the wider challenges faced by artificial socio-cognitive systems, and show how these can be tackled or mitigated with the help of a range of framework components. An intelligence layer contains autonomous agents which are responsible for controlling vehicles, but we assist these agents through the use of an external governance structure, capable of issuing guidance to the intelligent agents for situations where they do not know what to do, and/or to issue appropriate obligations to ensure the wider society goals are met. We see such external regulation as an intrinsic feature of social systems, whether implied (convention) or explicit (regulation/law), and replicate this structure through the use of institutions to provide a reference when the agent's knowledge is incomplete. In conclusion, our focus is on agent understanding from a Situational Awareness perspective, and consideration of what communication at which level is appropriate; from this we find that agents are better suited to higher level communication than to dealing with the processing of high volumes of low level perceptions. We couple the intelligent agents to an external governance structure, to mimic existing structures of regulation allowing agents to be provided with additional guidance as required. This approach is demonstrated in a number of scenarios which show the framework resolving issues where an individual agent would otherwise show undesirable behaviour as it: i) lacked knowledge of social convention, ii) would choose to pursue its own benefit over the collectives, or iii) lacked appropriate jurisdiction over other agents to bring about a solution. Having demonstrated how these issues can be alleviated by our approach in particular scenarios, we argue for some generalisations to problems broadly faced by (artificial) socio-cognitive systems, which we believe have sufficiently similar characteristics that our approach to the concretisation of SA for ASCS can be applied.

In this work, experimental data of ignition delay times of n-butanol, gasoline, toluene reference fuel (TRF), a gasoline/n-butanol blend and a TRF/n-butanol blend were obtained using the Leeds University Rapid Compression Machine (RCM) while autoignition (knock) onsets and knock intensities of gasoline, TRF, gasoline/n-butanol and TRF/n-butanol blends were measured using the Leeds University Optical Engine (LUPOE). The work showed that within the RCM, the 3-component TRF surrogate captures the trend of gasoline data well across the temperature range. However, based on results obtained in the engine, it appears that the chosen TRF may not be an excellent representation of gasoline under engine conditions as the knock boundary of TRF as well as the measured knock onsets are significantly lower than those of gasoline. The ignition delay times measured in the RCM for the blend, lay between those of gasoline and n-butanol under stoichiometric conditions across the temperature range studied and at lower temperatures, n-butanol acts as an octane enhancer over and above what might be expected from a simple linear blending law. In the engine, the measured knock onsets for the blend were higher than those of gasoline at the more retarded spark timing of 6 CA bTDC but the effect disappears at higher spark advances. Future studies exploring the blending effect of n-butanol across a range of blending ratios is required since it is difficult to conclude on the overall effect of n-butanol blending on gasoline based on the single blend that has been considered in this study. The chemical kinetic modelling of the fuels investigated has also been evaluated by comparing results from simulations employing the relevant reaction mechanisms with the experimental data sourced from either the open literature or measured in-house. Local as well as global uncertainty/sensitivity methods accounting for the impact of uncertainties in the input parameters, were also employed within the framework of ignition delay time modelling in an RCM and species concentration prediction in a JSR, for analysis of the chemical kinetic modelling of DME, n-butanol, TRF and TRF/n-butanol oxidation in order to advance the understanding of the key reactions rates that are crucial for the accurate prediction of the combustion of alternative fuels in internal combustion engines. The results showed that uncertainties in predicting key target quantities for the various fuels studied are currently large but driven by few reactions. Further studies of the key reaction channels identified in this work at the P-T conditions of relevance to combustion applications could help to improve current mechanisms. Moreover, the chemical kinetic modelling of the autoignition and species concentration of TRF, TRF/n-butanol and n-butanol fuels was carried out using the adopted TRF/n-butanol mechanism as input in the engine simulations of a recently developed commercial engine software known as LOGEengine. Similar to the results obtained in the RCM modelling work, the knock onsets predicted for TRF and TRF/n-butanol blend under engine conditions were consistently higher than the measured data. Overall, the work demonstrated that accurate representation of the low temperature chemistry in current chemical kinetic models of alternative fuels is very crucial for the accurate description of the chemical processes and autoignition of the end gas in the engine.