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The purpose of this research is to construct the competency of engine manufacturing engineer of Aero engine industry. Base on the result, it is expected to provide the principles for the Aero engine industry for personnel recruitment, education and training, and effectively enhance the working effciency. At first, this research figures out the research items of related competency analysis base on the different literatures. And then through deep discussion with senior engineers, management staffs and experts, to determine the key purpose of engine manufacturing engineers of Aero engine industry, i.e. to execute feasibility evaluation, process design, engineering integration, tool design and problem solving, etc. From those key purposes, it developped 6 major functions, 24 minor functions and 94 function units. For further study of the function tree of those competency, this research also conduct the weighing questionaire from some experts, to evaluate the weighing value of different functions on the tree diagram, to decide the degree of different functions. Among the 6 major functions, the weight of process integration capability is the highest, engineering capability get the second one, both of these two capabilities occupied 59% of the total weight. Besides these two important capabilities, it is followed by general process capability, special process capability, common capability, and operating of CAD. As a result, process integration capability and engineering competency are the most important capabilities for engine manufacturing engineers. This result could be the reference for personnel cultivation of aviation industry and also to provide the indications for self-assessment and self-growth of engine manufacturing engineers. The ultimate purpose is to expect the promotion of engine manufacturing of national Aero engine industry.

Aero-engine intakes play a critical role in the performance of modern high-bypass turbofan engines. It is their function to provide uniformly distributed, steady air flow to the engine fan face under a variety of flow conditions. However, during situations of high incidence, high curvature of the intake lip can accelerate flow to supersonic speeds, terminating with a shock wave. This produces undesirable shock wave boundary layer interactions (SWBLIs). Reynolds-Averaged Navier Stokes (RANS) turbulence models have been shown to be insensitive to the effects of boundary layer relaminarisation present in these highly-accelerated flows. Further, downstream of the SWBLI, RANS methods fail to capture the distorted flow that propagates towards the engine fan face. The present work describes simulations of a novel experimental intake rig model that replicates the key physics found in a real intake- namely acceleration, shock and SWBLI. The model is a simple geometric configuration resembling a lower intake lip at incidence. Simulations are carried out at two angles of attack, $\alpha=23^{\circ}$ and $\alpha=25^{\circ}$, with the more aggressive $\alpha=25^{\circ}$ possessing a high degree of shock oscillation. RANS, Large Eddy Simulations (LES) and hybrid RANS-LES are carried out in this work. Modifications to the one-equation Spalart-Allmaras (SA) RANS turbulence model are proposed to account for the effects of re-laminarisation and curvature. The simulation methods are validated against two canonical test cases. The first is a subsonic hump model where RANS modifications give a noticeable improvement in surface pressure predictions, even for this mild acceleration case. However, RANS is shown to over-predict the separation size. LES performs much better here, as long as the Smagorinsky-Lilly SGS model is not used. The $\sigma$-SGS model is found to perform best, and is used to run a hybrid RANS-LES that predicts a separation bubble size within $4\%$ of LES. The second canonical test case is a transonic hump that features a normal shockwave and SWBLI. RANS performs well here, predicting shock location, surface pressure and separation with good agreement with experimental measurements. Hybrid RANS-LES also performs well, but predicts a shock downstream of that measured by experiment. The use of an improved shock sensor here is able to maintain solution accuracy. Simulations of the intake rig are then run. RANS modifications provide a significant improvement in prediction of the shock location and lip surface pressure compared to the standard SA model. However, RANS models fail to reproduce the post shock interaction flow well, giving incorrect shape of the flow distortion. Further, RANS is inherently unable to capture the unsteady shock oscillations and related flow features. LES and hybrid RANS-LES predict the shock location and SWBLI well, with the downstream flow distortion also in very good agreement with experimental measurements. LES and hybrid RANS-LES are able to reproduce the time averaged smearing of the shock which RANS cannot. However, shock oscillations in the $\alpha=25^{\circ}$ case present a particular challenge for costly LES, requiring long simulation time to obtain time averaged flow statistics. Hybrid RANS-LES offers a significant saving in computational expense, costing approximately $20\%$ of LES. The work proposes recommendations for simulation strategy for intakes at incidence based on computational cost and performance of simulation methods.

This thesis sets out to examine the proposal that, by using tomography and gas sensing techniques to detect and image gas concentration in fast moving flows, engineers can improve the combustion diagnostics and emissions performance of gas turbines, enabling a better understanding of combustion and design optimisation of greener engines. The key factor is the combination of tomography with Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensing technology, implemented simultaneously along many beams, to image the gas concentration distribution in the exhaust plume of a gas turbine, in a plane perpendicular to the plume flow direction. The target gas species is carbon dioxide, CO2, and the absorption feature chosen is at a wavelength of 1997.2 nm. The narrow spectral absorption properties of such small molecules present a considerable challenge for a multi-beam tomographic implementation. Moreover, the design, oriented to harsh and industrial environments, presents key challenges for the design of robust optics and electronics for the collection of reliable data. The development of a 126-beam tomography system required the investigation of recently developed TDLAS techniques and their compatibility with data acquisition (DAQ) system firmware strategies to be implemented by custom DAQ electronics. A novel FPGA-based single channel TDLAS CO2 detection system has been designed and built to demonstrate the feasibility for the replication of 126-channels in the full system. Further proof-of-concept experiments carried out at full scale have produced tomographic images of phantom CO2 distributions that demonstrate the utility of the CST technique.

This study ventures into the intricate realm of aero engine mount systems, delving into the design and optimization of these crucial components. Our research utilizes mathematical modeling, computational algorithms, and a well-coordinated integration of Python scripting with Computer-Aided Design (CAD) tools to explore the design space of engine mounts, aiming to optimize their performance. Specifically, the study targets the optimization of certain design variables - L1, θ1, θ2, θ3, and R - that characterize the physical properties and performance of the engine mount system. The Python script computes the optimal values for these variables, which are then inputted into a CAD program, enabling the visualization and analysis of the optimized design. One of the fundamental objectives of this study was to minimize the forces experienced within the links of the engine mount system. The optimization procedure focused on the balance and distribution of forces across the links, ensuring that no single link was subjected to an undue portion of the load. The successful achievement of this objective not only improved the structural integrity of the engine mount system, but also underscored the potential of targeted optimization strategies in enhancing the performance of these critical components. By reducing the forces within the links, the study was able to contribute to the overarching goal of improving the overall distribution of loads in the separate links of the aero engine mount structure. The optimization objectives of this study also include minimizing the overall weight of the engine mount system, reducing backbone bending, and minimizing deflections through the reduction of the radial component. The results demonstrate the successful accomplishment of these objectives within the set boundaries, paving the way for enhancements in the structural rigidity and reliability of the engine mount system. Lastly, the study underscores the potential of leveraging computational optimization tools, such as the Python scripting and the L-BFGS-B algorithm. The outcomes of this study offer essential insights that could guide future design and optimization processes of engine mounts, laying a robust groundwork for further exploration in this field. Future work may include extending this methodology to larger engines with different behaviors and scales.  For those intrigued by the computational aspect of this investigation and keen to delve deeper into the intricacies of the code employed, Appendix A provides a comprehensive view. The Python script utilized in this study, integral to the optimization process, is included in its entirety in this section.