A high-precision T-spline blade modeling method with 2D and 3D knot adaptive refinement

Abstract

The aerodynamic shape of blades in turbo machinery is a key factor that affects blade efficiency, pressure ratio and other performance indicators. To address the lack of global continuity and difficulty in ensuring fairing quality in blade modeling, this paper proposes a novel blade modeling method that uses curvature constraints and a Mid-Closest Criterion to achieve adaptive knot refinement in 2D profile reconstructing and 3D T-mesh establishing process respectively. To begin with, the proposed Curvature-Constrained Periodic Reconstruction (CCPR) is used to reconstruct discrete sampling points of the section profile into a globally fairing periodic curve, and meets minimal error requirement. Additionally, the distribution of control points matches with curvature variation of the curve itself. Next, the Double Curves-guided Mid-Closest T-spline Surface skinning (DCM-TS) is used to construct a T-mesh from the stacked cross-sectional profile curves automatically, and the control vertices of the T-mesh are in a controllable scale and reasonably distributed. Further, the modeling precision is allocated with the curvature information of the ideal blade contour, and based on that, a T-spline skinning surface is obtained through LSPIA method, which updates the model and realizes blade modeling that considers both the design efficiency and accuracy. Eventually the proposed method is verified and compared with several traditional surface skinning methods in practical modeling cases. The result unveils that the presented method is compatible with traditional aerofoil parameterization methods, generates surface with global continuity and high fairing quality, and has sharply reduced and evenly distributed control vertices.