Randomized trial demonstrates effective mesh generation in 3D wing configurations, suggesting a breakthrough in CFD efficiency.
Structured mesh generation is critical for high-fidelity Computational Fluid Dynamics (CFD) simulations; however, the automatic generation of multi-block structured meshes for complex three-dimensional (3D) wings remains a long-standing challenge. Traditional methods heavily rely on manual multi-block topology decomposition, while recent intelligent methods suffer from limited generalizability, reliance on labeled training data, and inadequate boundary-layer controllability. This paper proposes a fully automatic structured mesh generation method for arbitrary 3D wing configurations based on adaptive parametric multi-block topology. First, a geometric parameterization framework for 3D wings is established using the Gordon surface method. Then, the multi-block topology is adaptively generated analytically via parametric construction of control vertices and edges. Finally, a four-level assembly process is employed to generate the final mesh. Systematic tests on wings with various aspect ratios, sweep angles, and deformations demonstrate that the method exhibits excellent robustness. Generating a one-million-cell mesh requires only 0.391 s (single-threaded), which is approximately six times faster than existing intelligent methods. CFD results of benchmark wings show good agreement with available reference data, while the static aeroelastic characteristics of the custom flying-wing model conform to physical principles. This study provides a generalizable, interpretable, and fully automatic solution for structured mesh generation of 3D wings.
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Jiang et al. (2026) studied this question.
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