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This thesis reports original research on a novel internal combustion (IC) engine charge air system concept called Turbo-Discharging. Turbo-Discharging depressurises the IC engine exhaust system so that the engine gas exchange pumping work is reduced, thereby reducing fuel consumption and CO2 emissions. There is growing concern regarding the human impact on the climate, part of which is attributable to motor vehicles and transport. Recent legislation has led manufacturers to improve the fuel economy and thus reduce the quantity of CO2 generated by their vehicles. As this legislation becomes more stringent manufacturers are looking to new and developing technologies to help further improve the fuel conversion efficiency of their vehicles. Turbo-Discharging is such a technology which benefits from the fact it uses commonly available engine components in a novel system arrangement. Thermodynamic and one-dimensional gas dynamics models and experimental testing on a 1.4 litre four cylinder four-stroke spark ignition gasoline passenger car engine have shown Turbo-Discharging to be an engine fuel conversion efficiency and performance enhancing technology. This is due to the reduction in pumping work through decreased exhaust system pressure, and the improved gas exchange process resulting in reduced residual gas fraction. Due to these benefits, engine fuel conversion efficiency improvements of up to 4% have been measured and increased fuel conversion efficiency can be realised over the majority of the engine operating speed and load map. This investigation also identified a measured improvement in engine torque over the whole engine speed range with a peak increase of 12%. Modelling studies identified that both fuel conversion efficiency and torque can be improved further by optimisation of the Turbo-Discharging system hardware beyond the limitations of the experimental engine test. The model predicted brake specific fuel consumption improvements of up to 16% at peak engine load compared to the engine in naturally aspirated form, and this increased to up to 24% when constraints imposed on the experimental engine test were removed.

Training simulators are used in a variety of industries that require the skill of handling complex or sophisticated technologies and having knowledge of advanced controls. Training simulators have a long history; a number of studies have already been done to make the training simulators more flexible. Jet engine testing operators have to follow a proper methodology to carry out the procedures of safe engine testing. While performing the tests, the operators have to deal with various emergency conditions and should have proper information on how to deal with those situations. This thesis presents the design and development of a training simulator for aviation engine testing operators. Engine simulation software, GasTurb, is used to develop the jet engine model files and to get the output variables from the simulator. These model files are made accessible in Simulink (MATLAB) with the help of second order S-function. The S-function accesses the Dynamic Link Library (DLL) of GasTurb, to read the model files and to provide real time output on the basis of inputs from external hardware. The user interface to display these output values is developed in Unity game engine. Five different emergency scenarios have been designed and evaluated using the developed simulator. Related variables for these emergency scenarios are plotted to compare the reaction of the operators. The feedback is also taken from the operators regarding the effectiveness of training simulator. The result shows that training simulator would promote and develop their understanding of process. It would help to enhance the ability of operator to identify parameters causing the emergency scenarios and enable them to overcome such situations. / October 2016

The performance requirements of turbofan engines demands a stability and transient capability beyond that associated with the past generations of gas turbine engines. The axial flow fan unit is most vulnerable to loading limitations due to the primary problems associated with the compression process, its sensitivity to inlet distortion and the difficulty to design for an overall optimum blade duty in a machine of wide radial blade loading distribution. The development of mathematical models with some capability of predicting the stable operating range of an axial flow fan has to overcome the difficulties associated with the modelling of the radially distinct flow regions and their dynamic interaction. ' The current investigation combined the available knowledge of one-dimensional models (based on the principles of conservation of mass, linear momentum and energy) with the assumptions of the parallel compressor theory, in order to develop a linearized system of equations for stability analysis (surge prediction). The stability conditions which emerged from this approach were applied on the experimentally derived characteristics of a low hub to tip ratio split flow fan in a manner which involved the modelling of the dynamic interaction of the inner and outer flow region of the fan. The development of the governing equations was achieved by applying one-dimensional flow analysis to the inner and outer section of the fan. Their interaction was modelled on the experimentally obtained radial movement of the splitter streamline and the discharge ,static pressure 'radial distribution. The inner and outer region were treated as a lumped volume element search operating on a local masflow averaged total pressure rise characteristic and alternatively acting in conjunction with a common nozzle and separate nozzles. The experimental investigation was carried out on a low hub totipratio two-stage split flow fan(with the facility of independent bypass and core throttles)in order to examine the localised and overall performance of such a fan(and the staling processes involved)and to enable the application of the stability analysis. The influence of reducing the distance between the fan flow spliter and the last bladerowasal so investigated, «The mathematical mode1s predicted the point of dynamic instability within 4.52 of the experimental observed mas flow rate and pressure is value.

Effective collaboration is essential for engineers at geographically dispersed locations to accomplish good design with less iteration. Over the last several years, more and more efforts have been put into such research as many industries have distributed their product development to locations with knowledge force. This paper presents a collaborative engine to facilitate collaborations among distributed mechanical designs. Using component-based software technology, collaboration functionality is developed into a set of groupware that makes the collaborative engine applicable to develop new collaborative applications or integrate legacy applications into collaborative environments. An XML-based information representation is developed to streamline the information transmission within the distributed environment. A case study is carried out to show how this engine facilitates designers to collaboratively create a 3D solid model of a same part in real time. / Singapore-MIT Alliance (SMA)

In a document retrieval system where data is stored and compared with a specific query and then compared with other documents, we need to find the document that is most similar to the query. The most similar document will have the weight higher than other documents. When more than one document are proposed to the user, these documents have to be sorted according to their weights. Once the result is presented to the user by a recommender system, the user may check any document of interest. If there are two different documents' lists, as two proposed results presented by different recommender systems, then, there is a need to find which list is more efficient. To do so, the measuring tool "Search Engine Ranking Efficiency Evaluation Tool [SEREET]" came to existence. This tool assesses the efficiency of each documents list and assigns a numerical value to the list. The value will be closer to 100% if the ranking list efficiency is high which means more relevance documents exist in the list and documents are sorted according to their relevance to the user. The value will be closer to 0% when the ranking list efficiency is poor and all of the presented documents are uninteresting documents to the user. A model to evaluate ranking efficiency is proposed in the dissertation, then it is proved it mathematically. Many mechanisms of search engine have been proposed in order to assess the relevance of a web page. They have focused on keyword frequency, page usage, link analysis and various combinations of them. These methods have been tested and used to provide the user with the most interesting web pages, according to his or her preferences. The collaborative filtering is a new approach, which was developed in this dissertation to retrieve the most interesting documents to the user according to his or her interests. Building a user profile is a very important issue in finding the user interest and categorizes each user in a suitable category. This is a requirement in collaborative filtering implementation. The inference tools such as time spent in a web page, mouse movement, page scrolling, mouse clicks and other tools were investigated. Then the dissertation shows that the most efficient and sufficient tool is the time a user spent on a web page. To eliminate errors, the system introduces a low threshold and high threshold for each user. Once the time spent on a web page breaks this threshold, an error is reported. SEREET tool is one of the contributions to the scientific society, which measures the efficiency of a search engine ranking list. Considerable work were carried, then the conclusion was that the amount of time spent on a web page is the most important factor in determining a user interest of a web page and also it is a sufficient tool which does not require collaborations from other tools such as mouse movements or a page scrolling. The results show that implicit rating is a satisfactory measure and can replace explicit rating. New filtering technique was introduced to design a fully functional recommender system. The linear vector algorithm which was introduced improves the vector space algorithm (VSA) in time complexity and efficiency. The use of machine learning enhances the retrieved list efficiency. Machine learning algorithm uses positive and negative examples for the training, these examples are mandatory to improve the error rate of the system. The result shows that the amount of these examples increases proportionally with the error rate of the system.