Naixing Chen
Chinese Academy of Sciences
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Featured researches published by Naixing Chen.
ASME Turbo Expo 2005: Power for Land, Sea, and Air | 2005
Naixing Chen; Hao Zhang; H. Du; Yanji Xu; Wei-Yuan Huang
It is well known that to increase rotational velocity is one of the effective measures to increase total pressure ratio. With increasing velocity, under the condition of transonic flow, the obvious effect of maximum camber location on aerodynamics performance of compressor blades especially in the supersonics zone can be found. In order to reduce the blade losses and to improve the blade design methodology it is necessary to study this complex flow mechanism. This paper describes only the influence of relative maximum camber location on aerodynamics performance, mainly adiabatic efficiency. As an example an axial fan was designed and calculated by the methodologies developed at the Institute of Engineering Thermophysics, Chinese Academy of Sciences.Copyright
ASME Turbo Expo 2009: Power for Land, Sea, and Air | 2009
Naixing Chen; Hao Zhang; Q. Xu; Wei-Yuan Huang
A 3D blade optimization strategy for improving turbomachinery performance is proposed mainly based on simple gradient-based method and multi-section blade parameterization technique (MS-BPT) in the present paper. The blade rebuilding method (BRM), the 3D grid generation method (RAPID3DGRID) and the N. S. solver are also used. By using the blade rebuilding method the coordinates of arbitrary blade profile (2D) of each section can be transformed into a set of blade design parameters. For all sections (i.e. in the 3D case) the number of the total design parameters to be searched is increased. But, it can be reduced by designers’ experiences. Since these design parameters, which are obtained by the present blade parameterization method, are independent each from other, this feature allows us to use a simple gradient-based method (SGBM) to search the optimum of the cost function, i.e. with changing any one of the parameters and using grid generator and N. S. solver the optimal design parameters can be obtained in each single optimal parameter searching. And then, instead the old one the new obtained parameter joins the other parameter optimum-searching process in an iteration turn. By repeating the iteration process the convergence of whole optimization process can be reached. The NASA single rotor compressor served as a computation example. The adiabatic efficiency was increased nearly by three percentages. The converged results can be obtained only by a few iterations turns. It is shown that the present method is efficient and can be applied as one of the optimization tools to the design optimization of turbomachinery blades.Copyright
ASME Turbo Expo 2006: Power for Land, Sea, and Air | 2006
Naixing Chen; Hongwu Zhang; Fangfei Ning; Yanji Xu; Weiguang Huang
This paper describes a procedure for a rapid and accurate 3D aerodynamic optimization of high performance turbine blades. This procedure has been developed to account for the complicated geometrical aspects and the complex nature of the associated fluid flow, while remaining simple, practical and demanding less computing power. The focus has been placed on the blade geometrical representation using a set of simple algebraic equations (blade parameterization) and on the aerodynamic optimization methodology based on the numerical computations by a N.S. solver. The turbine blade, including thickness distribution and camber line for each section of the blade span and radial stacking line, has been defined by polynomials, allowing investigation of the influence of any single-parameter change on blade performance. An improved response surface method, by incorporating a simulated annealing algorithm (RS-SAM), has been found to improve the accuracy and to strengthen the optimum-searching ability. A multi-objective response surface method (MORSM) has also been included for testing. One example is given here to demonstrate the effectiveness of the procedure.Copyright
Journal of Thermal Science | 2007
Naixing Chen; Hongwu Zhang; Yanji Xu; Weiguang Huang
Journal of Thermal Science | 2005
Naixing Chen; Hongwu Zhang; Weiguang Huang; Yanji Xu
Journal of Thermal Science | 2004
Naixing Chen; Hongwu Zhang; Yanji Xu; Weiguang Huang
Journal of Thermal Science | 2000
Naixing Chen; Yanji Xu; Weiguang Huang
Journal of Thermal Science | 2012
Shaojuan Geng; Naixing Chen; Hongwu Zhang; Weiguang Huang
Journal of Thermal Science | 2010
Naixing Chen; Huan Zhang; Weiguang Huang
Journal of Thermal Science | 2003
Naixing Chen; Hongwu Zhang; Yanji Xu; Weiguang Huang