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Open Access

Automatic Multiblock Mesh Generation for 3D-Wing Aerodynamic Analysis

the School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
the School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China, the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China, and also with the Zhongguancun Laboratory, Beijing 100191, China
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Abstract

In aerodynamic design, high-quality multiblock mesh generation serves as the cornerstone for accurate lift-drag analysis of wings. However, conventional computational fluid dynamics (CFD) workflows offered by industrial software reveals critical limitations in labor-intensive manual operations. While automatic meshing in 2D wing cross-section is well-established, its extension to 3D wing meshing faces unresolved challenges, including excessive block generation, complex feature alignment, and incomplete simulation-ready pipelines. This paper presents an automatic multiblock mesh generation framework specifically targeting these commercial software shortcomings for 3D wing analysis. Our methodology addresses three persistent challenges: (1) a parameterization-based tip surface meshing method with optimized cell quality, (2) an extrusion-based wing body meshing approach ensuring precise feature alignment at joints and leading edges, and (3) an end-to-end pipeline from geometric pre-processing to CFD-ready multiblock mesh generation. Experiments demonstrate the framework’s ability to produce high-quality meshes with minimal manual intervention, streamlining the workflow for aerodynamic simulations.

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Complex System Modeling and Simulation
Pages 151-163

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Cite this article:
Yu Y, Li N, Gong G. Automatic Multiblock Mesh Generation for 3D-Wing Aerodynamic Analysis. Complex System Modeling and Simulation, 2026, 6(2): 151-163. https://doi.org/10.23919/CSMS.2025.0017

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Received: 21 May 2025
Revised: 01 June 2025
Accepted: 13 June 2025
Published: 01 June 2026
© The author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).