Effect of Maximum Camber Location on Aerodynamics Performance of Transonic Compressor Blades

Chen, N. X.; Zhang, H. W.; Du, Hai; Xu, Yu; Huang, Wenhao

doi:10.1115/gt2005-68541

Cited by 12 publications

(8 citation statements)

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“…Fan blade was optimized by Idahosa et al [12] through an automated optimization procedure. Effect of maximum camber location on a transonic compressor blade was reported by Chen et al [13]. They studied numerically and suggested that efficiency can be increased changing the airfoil shape.…”

Section: Introductionmentioning

confidence: 91%

Design optimization of low-speed axial flow fan blade with three-dimensional RANS analysis

2008

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This work presents a numerical optimization procedure for a low-speed axial flow fan blade with polynomial response surface approximation model. Reynolds-averaged Navier-Stokes equations with SST turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. The blade profile as well as stacking line is modified to enhance blade total efficiency, i.e., the objective function. The design variables of blade lean, maximum thickness and location of maximum thickness are selected, and a design of experiments technique produces design points where flow analyses are performed to obtain values of the objective function. A gradient-based search algorithm is used to find the optimal design in the design space from the constructed response surface model for the objective function. As a main result, the efficiency is increased effectively by the present optimization procedure. And, it is also shown that the modification of blade lean is more effective to improve the efficiency rather than modifying blade profile.

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Section: Introductionmentioning

confidence: 91%

Design optimization of low-speed axial flow fan blade with three-dimensional RANS analysis

2008

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“…Several other studies on shape optimization of turbomachinery blades have been undertaken, with specific emphases on maximum camber [7], camber line [8][9], airfoil thickness [10], thickness location [11], trailing edge (TE) radius [12], and others.…”

Section: Introductionmentioning

confidence: 99%

Performance enhancement of axial fan blade through multi-objective optimization techniques

et al. 2010

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This paper presents an axial fan blade design optimization method incorporating a hybrid multi-objective evolutionary algorithm (hybrid MOEA). In flow analyses, Reynolds-averaged Navier-Stokes (RANS) equations were solved using the shear stress transport turbulence model. The numerical results for the axial and tangential velocities were validated by comparing them with experimental data. Six design variables relating to the blade lean angle and the blade profile were selected through Latin hypercube sampling of design of experiments (DOE) to generate design points within the selected design space. Two objective functions, namely, total efficiency and torque, were employed, and multi-objective optimization was carried out, to enhance the performance. A surrogate model, Response Surface Approximation (RSA), was constructed for each objective function based on the numerical solutions obtained at the specified design points. The Non-dominated Sorting of Genetic Algorithm (NSGA-II) with local search was used for multi-objective optimization. The Pareto-optimal solutions were obtained, and a trade-off analysis was performed between the two conflicting objectives in view of the design and flow constraints. It was observed that, by the process of multi-objective optimization, the total efficiency was enhanced and the torque reduced. The mechanisms of these performance improvements were elucidated by analysis of the Pareto-optimal solutions.

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“…Oyama et al [63] reported blade profile modification with the help of B-spline curve of NASA rotor 67 to increase adiabatic efficiency by 2%. Chen et al [69] optimized camber line, thickness distribution and stacking line by polynomial curve to define compressor blade and gained 1.73% improvement of adiabatic efficiency. Maximum camber location effect was studied by Chen et al [69].…”

Section: Applications Of Surrogate Based Optimization Methodsmentioning

confidence: 99%

“…Chen et al [69] optimized camber line, thickness distribution and stacking line by polynomial curve to define compressor blade and gained 1.73% improvement of adiabatic efficiency. Maximum camber location effect was studied by Chen et al [69]. Benini [53] defined blade section profiles by Bezier curve using multi-objective optimization considering total pressure ratio and adiabatic efficiency as objectives for design of a compressor blade.…”

Section: Applications Of Surrogate Based Optimization Methodsmentioning

confidence: 99%

Surrogate Based Optimization Techniques for Aerodynamic Design of Turbomachinery

Samad¹,

Kim²

2009

International Journal of Fluid Machinery and Systems

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Recent development of high speed computers and use of optimization techniques have given a big momentum of turbomachinery design replacing expensive experimental cost as well as trial and error approaches. The surrogate based optimization techniques being used for aerodynamic turbomachinery designs coupled with Reynolds-averaged NavierStokes equations analysis involve single-and multi-objective optimization methods. The objectives commonly tried to improve were adiabatic efficiency, pressure ratio, weight etc. Presently coupling the fluid flow and structural analysis is being tried to find better design in terms of weight, flutter and vibration, and turbine life. The present article reviews the surrogate based optimization techniques used recently in turbomachinery shape optimizations.

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Effect of Maximum Camber Location on Aerodynamics Performance of Transonic Compressor Blades

Cited by 12 publications

References 0 publications

Design optimization of low-speed axial flow fan blade with three-dimensional RANS analysis

Design optimization of low-speed axial flow fan blade with three-dimensional RANS analysis

Performance enhancement of axial fan blade through multi-objective optimization techniques

Surrogate Based Optimization Techniques for Aerodynamic Design of Turbomachinery

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