Compressor blade design influences aero-engine performance mainly through its total pressure ratio and efficiency. As a volume-based geometric parameterization, Free-form Deformation (FFD) brings three-dimensionality that is essential to blade design. However, the manipulation of control points with respect to simple numeric parametric perturbation renders the use of design space low-efficient. Therefore, an improved FFD with ‘wiser’ control point lay-out is expected to identify those more important design variables. This paper proposes novel design variables that are assigned to grouping of control points’ displacement in FFD lay-out. In short, the approach is realized as: (i) establish a library of sufficient blade shape samples; (ii) filter the database with geometric constraints; (iii) extract dominant modes via (POD) Proper Orthogonal Decomposition; (iv) construct new design variables and apply them in optimization. With geometric constraint filtering, problem-oriented information is injected. With POD, the dominance of new selected geometric parameters in problem description is assured. Perfunctory details of displacement data of each control point in the lay-out can be replaced by grouped data as new design variable candidates. As a proof-of-concept study of the new approach, compressor blade Rotor 37 is selected to be the good platform of testing the feasibility of POD-aided FFD as a global and flexible yet economic geometric parameterization. Result demonstrates the feasibility of proposed POD-aided FFD approach that helps conduct an optimization involving displacement of 6 × 4 × 3 control points with as few as five new design variables, while still being capable of bringing optimization effect in three test cases.

An approach of Proper Orthogonal Decomposition-aided Free-form Deformation with application in compressor blade design

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Computational Analysis of Axial Compressor Stages Characteristics

The most critical step in designing a turbomachine is to design the blades. In this study, an axial turbine blade is designed using an inverse design method called Ball-Spine Algorithm. In some cases, the target pressure distribution is not specified in the inverse design process, and it has to be determined arbitrarily by the designer. This study is conducted in order to compute the optimal target pressure distribution by maximizing the cascade blade efficiency. Optimization is carried out using the Genetic Algorithm. Two commercial software packages, ANSYS and MATLAB, are used in this research. Since inverse design is an iterative process, these software packages are linked together to execute the whole procedure automatically. Validation of the approach is accomplished by redesigning an existing blade. Then the optimization method is applied, and the desired blade is inversely designed. Results show that the cascade blade efficiency increases by about 9% on average for this blade.

Optimization of the target pressure distribution and inverse design of an axial turbine blade

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Methodology and Experience of Primary Design of a Transonic Axial Compressor

Developing a mathematical model and a computer program for a preliminary design of a transonic axial compressor

A novel three-dimensional inverse method based on the time-accurate solution of Navier–Stokes equations for axial compressor design is proposed in this work. The main novelty lies in the derivation of an inverse design boundary condition established on the conservation of Riemann invariant in order to directly design the blade surface. Specifically, a dynamic mesh technique is employed to update the grids and reduce the computational costs. In addition, some restrictions are imposed on the blade surface movement in order to avoid unrealistic airfoil profiles and guarantee computational robustness. Two redesign procedures are presented, including shock wave strength restrain for the NASA Rotor 37 stage and integrated controlled diffusion airfoil concept design for the Stage 35. Results indicate that this novel inverse method is effective for detailed axial compressor design.

Hu Wu

Papers

A Novel Three-Dimensional Inverse Method for Axial Compressor Blade Surface Design