Numerical and Experimental Study on Aerodynamic Approximation Methods for Inclined Honeycomb Grid Fins

Wind tunnel experiment serves as a primary method for characterizing grid fin aerodynamics, yet a fundamental conflict arises between facility size constraints and the structural vulnerability of excessively thinned grid fins from aggressive scaling, which might prevent viable experiments from being conducted. This study addresses this limitation by proposing two aerodynamic approximation methods, namely the unconstrained cell chord ratio method and the unconstrained external frame dimensions method, which generate aerodynamically equivalent configurations by strategically reducing the number of cells within the external frame to increase structural thickness. Through combined computational fluid dynamics (CFD) simulations and wind tunnel experiments analyzing full-scale isolated grid fins, full-scale launch vehicles equipped with grid fins, and their 1:25 scaled counterparts, both methods demonstrably outperform the published supersonic linearization approximation method. Critically, once the cell number is not excessively reduced, the unconstrained frame method maintains identical variation trends in aerodynamic forces, moments, and rudder control effectiveness compared to the baseline configuration, with maximum deviations constrained within 3% across tested conditions. This precision validates the exceptional suitability of the method for aerodynamic approximation of scale-down grid-fin-equipped launch vehicles in wind tunnel experiments, resolving the critical trade-off between test feasibility and structural strength.

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Publication Details

Journal
Energies
Published
2025-09-15
DOI
https://doi.org/10.3390/en18184893
Primary Topic
Aerodynamics and Fluid Dynamics Research
Type
article
Field-Weighted Citation Impact
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article

Numerical and Experimental Study on Aerodynamic Approximation Methods for Inclined Honeycomb Grid Fins

Xiaojun Wu, Hongyin Jia, Huan Li, Pengcheng Cui et al.
Energies
Aerodynamics and Fluid Dynamics Research
article

Numerical and Experimental Study on Aerodynamic Approximation Methods for Inclined Honeycomb Grid Fins

Xiaojun Wu, Hongyin Jia, Huan Li, Pengcheng Cui, Lei Luo, Longfei Li, Guiyu Zhou
article en

Abstract

Wind tunnel experiment serves as a primary method for characterizing grid fin aerodynamics, yet a fundamental conflict arises between facility size constraints and the structural vulnerability of excessively thinned grid fins from aggressive scaling, which might prevent viable experiments from being conducted. This study addresses this limitation by proposing two aerodynamic approximation methods, namely the unconstrained cell chord ratio method and the unconstrained external frame dimensions method, which generate aerodynamically equivalent configurations by strategically reducing the number of cells within the external frame to increase structural thickness. Through combined computational fluid dynamics (CFD) simulations and wind tunnel experiments analyzing full-scale isolated grid fins, full-scale launch vehicles equipped with grid fins, and their 1:25 scaled counterparts, both methods demonstrably outperform the published supersonic linearization approximation method. Critically, once the cell number is not excessively reduced, the unconstrained frame method maintains identical variation trends in aerodynamic forces, moments, and rudder control effectiveness compared to the baseline configuration, with maximum deviations constrained within 3% across tested conditions. This precision validates the exceptional suitability of the method for aerodynamic approximation of scale-down grid-fin-equipped launch vehicles in wind tunnel experiments, resolving the critical trade-off between test feasibility and structural strength.

EnergiesVol. 18(18)
China Aerodynamics Research and Development Center (CN)
Openalex Percentile: Top 67%
Aerodynamics and Fluid Dynamics Research
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Numerical and Experimental Study on Aerodynamic Approximation Methods for Inclined Honeycomb Grid Fins — Xiaojun Wu, Hongyin Jia, et al. · Energies (2025) | TGRS Research Map | TGRS