Browsing by Author "Wang, Jian"

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    Aircraft hydraulic power system diagnostic, prognostics and health management
    (Cranfield University, 2012-01) Wang, Jian; Lawson, C. P.
    This Individual Research Project (IRP) is the extension research to the group design project (GDP) work which the author has participated in his Msc programme. The GDP objective is to complete the conceptual design of a 200-seat, flying wing civil airliner—FW-11. The next generation aircraft design demands higher reliability, safety and maintainability. With the development of the vehicle hydraulic system technology, the equipment and systems become more and more complex, their reliability and maintenance become more difficult for designers, manufacturers and customers. To improve the mission reliability and reduce life cycle cost, there is strong demand for the application of health management technology into airframe system design. In this research, the author introduced diagnostic, prognostic and health management (DPHM) concept into the aircraft hydraulic power system development. As a brand new technology, it is a challenge to apply the DPHM techniques to on-board system. Firstly, an assumed hydraulic power system was designed for FW-11 by the author and used as the case in his IRP research. Then the crucial components and key parameters needed to be monitored were obtained based on Function Hazard Analysis and Failure Modes Effects Analysis of this system. The writer compared a few diagnostic and prognostic methods in detail, and then selected suitable ones for a hydraulic power system. A diagnostic process was applied to the hydraulic power system using a Case-based reasoning (CBR) approach, whilst a hybrid prognostic method was suggested for the system. After that, a diagnostic, prognostic and health management (DPHM) architecture of the hydraulic power system was designed at system level based on the diagnostic and prognostic research. The whole research work provided a general and practical instruction for hydraulic system design by means of DPHM application.
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    Embedded large eddy simulation of transitional flow over NACA0012 aerofoil
    (Sage, 2020-07-06) Lin, Yujing; Wang, Jian; Savill, Mark
    An accurate computation of near-field unsteady turbulent flow around aerofoil is of outstanding importance for aerofoil trailing edge noise source prediction, which is a representative of main contributor to airframe noise and fan noise in modern commercial aircraft. In this study, an embedded large eddy simulation (ELES) is fully implemented in a separation-induced transitional flow over NACA0012 aerofoil at a moderate Reynolds number. It aims to evaluate the performance of the ELES method in aerodynamics simulation for wall-bounded aerospace flow in terms of accuracy, computational cost and complexity of implementation. Some good practice is presented including the special treatments at RANS-LES interface to provide more realistic turbulence generation in LES inflow. A comprehensive validation of the ELES results is performed by comparing with the experimental data and the wall-resolved large eddy simulation results. It is concluded that the ELES method could provide sufficient accuracy in the transitional flow simulations around aerofoil. It is proved to be a promising alternative to the pure LES for industrial flow applications involving wall boundary layer due to its significant computational efficiency
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    Geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation
    (IEEE, 2020-10-30) Zhang, Jiayu; Zhang, Tao; Shin, Hyosang; Wang, Jian; Zhang, Chen
    Extensive research results have shown that animals like pigeons and turtles can use geomagnetic information for long-distance migration and homing. This article studies the bionic navigation method inspired by magnetotaxis behavior without prior knowledge. The problem of bionic geomagnetic navigation is generalized as an autonomous search of navigation path under the excitation of geomagnetic environment. The geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation is proposed. In order to optimize the navigation path, the heading angle predicted by the geomagnetic gradient is used to constrain the sample space in the evolutionary algorithm. Then, according to the principle of multiparameter simultaneous convergence, the evaluation function is improved to enhance the reliability and accuracy of the navigation path. Simulations of the algorithm before and after improvement are carried out based on the data retrieved from the enhanced magnetic model (EMM). The performance of the improved method is evaluated and verified in the case of the area with normal geomagnetic field (GF), geomagnetic anomaly area, and multiple destinations. The simulation results show that the search efficiency and the straightness of the navigation path are greatly improved. The reason is that the constraint of sample space reduces the randomness in the process of navigation path search, and the improved evaluation function can evaluate the quality of samples more accurately. The improved algorithm also has good performance in the geomagnetic anomaly area, which indicates the potential application in the future.