Optimization of Blade Sweep in a Transonic Axial Compressor Rotor

Jang, Choon‐Man; Li, Ping; Kim, Kwang‐Yong

doi:10.1299/jsmeb.48.793

Cited by 20 publications

(13 citation statements)

References 16 publications

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“…This is one of the simplest surrogate model, which utilizes information collected from various sources and by different tool. Thus, this method is effective for both of single-and multi-disciplinary optimization problems [40][41][42][43][44].…”

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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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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“…More recently, optimization strategies that automate geometry creation with CFD simulation have been developed. Benini [10] and Jang et al [11] researched the aerodynamic optimization design techniques based on the NASA Rotor 37 rotor. Three-dimensional viscous flow effects were taken into account through the 3D CFD approach.…”

Section: Introductionmentioning

confidence: 99%

Flow Diagnosis and Optimization Based on Vorticity Dynamics for Transonic Compressor/Fan Rotor

Chen¹,

Turner²,

Siddappaji³

et al. 2017

OJFD

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This paper presents two optimized rotors. The first rotor is as part of a 3-blade row optimization (IGV-rotor-stator) of a high-pressure compressor. It is based on modifying blade angles and advanced control of curvature of the airfoil camber line. The effects of these advanced blade techniques on the performance of the transonic 1.5-stage compressor were calculated using a 3D Navier-Stokes solver combined with a vortex/vorticity dynamics diagnosis method. The first optimized rotor produces a 3-blade row efficiency improvement over the baseline of 1.45% while also improving stall margin. The throttling range of the compressor is expanded largely because the shock in the rotor tip area is further downstream than that in the baseline case at the operating point. Additionally, optimizing the 3-blade row block while only adjusting the rotor geometry ensures good matching of flow angles allowing the compressor to have more range. The flow diagnostics of the rotor blade based on vortex/vorticity dynamics indicate that the boundary-layer separation behind the shock is verified by on-wall signatures of vorticity and skinfriction vector lines. In addition, azimuthal vorticity and boundary vorticity flux (BVF) are shown to be two vital flow parameters of compressor aerodynamic performance that directly relate to the improved performance of the optimized transonic compressor blade. A second rotor-only optimization is also presented for a 2.9 pressure ratio transonic fan. The objective function is the axial moment based on the BVF. An 88.5% efficiency rotor is produced.

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“…However, with the rapidly increased computing capacity and advances in numerical methods, Computational Fluid Dynamics (CFD) coupled with advanced optimization algorithms provides a costeffective way to improve the design of turbomachinery as compared to classical methods based on manual iteration. Many design optimization approaches such as response surface methodology [1][2][3][4], genetic algorithms [5][6][7] and finite difference methods [8] were applied in design development and most of them are widely used nowadays.…”

Section: Introductionmentioning

confidence: 99%

“…Then the shear stress can be updated following Eqn. (1). The generalization of the wall function introduced above is reflected by the calculation of the eddy viscosity which is independent of any turbulence model, i.e.…”

Section: A Introduction Of the Wall Functionmentioning

confidence: 99%

Optimization of Endwall Contours of a Turbine Blade Row Using an Adjoint Method

Luo

McBean

Liu

2011

Volume 7: Turbomachinery, Parts A, B, and C

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This paper presents the application of a viscous adjoint method in the optimization of a low-aspect-ratio turbine blade through spanwise restaggering and endwall contouring. A generalized wall-function method is implemented in a Navier-Stokes flow solver coupled with Menter's SST k-ω Coordinates in the computational domain INTRODUCTIONAt present, it is difficult to further improve the performance of turbomachinery through traditional design procedures because significant efficiency gains have already been obtained. However, with the rapidly increased computing capacity and advances in numerical methods, Computational Fluid Dynamics (CFD) coupled with advanced optimization algorithms provides a costeffective way to improve the design of turbomachinery as compared to classical methods based on manual iteration. Many design optimization approaches such as response surface methodology [1-4], genetic algorithms [5][6][7] and finite difference methods [8] were applied in design development and most of them are widely used nowadays.In the optimization of designs based on CFD analysis, the flow solver which plays an important role in the optimization system is required to provide physically accurate flow solutions. However, not all turbulence models can sufficiently model complex flows. Wilcox gave an overview of the turbulence models [9] and demonstrated that models based on the ω-equation can support satisfactory solutions for most of the flows. In the present study, the flow solutions come from a turbomachinery flow code Turbo90, in which Menter's SST k-ω turbulence model [10] is adopted coupled with a third-order Roe scheme for the convective terms.For the designs of complex geometries, meshes with millions of cells are required to resolve the flow. The problem of reducing the computer time without loss in numerical accuracy is of particular importance for the optimization of designs. In the past several decades, research has been done to improve the efficiency of flow solvers. An effective method for reducing computational effort is to reduce the computational grid without loss of accuracy. Hereby for the improved modeling of boundary layer regions with limited grid resolution, the wall function methods were developed originally through flat-plate flows with zero streamwise pressure gradient. Most of the earliest wall functions were developed from the "law of the wall" [11,12], which accounts for the flow structure in the logarithmic layer. However, the entire boundary region in a fully-turbulent flow can be subdivided into three parts, a viscous sublayer, a buffer layer and a logarithmic layer. By using the earliest wall function methods, the first grid point away from the solid wall should locate in the logarithmic layer and obviously it is a severe constraint, which is inevitably to be violated in complex flows. In order to overcome such drawbacks, wall functions that account for the entire boundary layer are needed. Kalitzin [13] proposed a general-

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Optimization of Blade Sweep in a Transonic Axial Compressor Rotor

Cited by 20 publications

References 16 publications

Surrogate Based Optimization Techniques for Aerodynamic Design of Turbomachinery

Surrogate Based Optimization Techniques for Aerodynamic Design of Turbomachinery

Flow Diagnosis and Optimization Based on Vorticity Dynamics for Transonic Compressor/Fan Rotor

Optimization of Endwall Contours of a Turbine Blade Row Using an Adjoint Method

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