Gradient-Based Internal–External Flow Coupling Optimization for Embedded-Inlet Aircraft

As aerodynamic configurations become increasingly integrated with propulsion systems, internal–external flow coupling has become a key issue in airframe–engine integration. For embedded-inlet configurations, however, the airframe and inlet/exhaust system have different geometric shaping requirements, making their design variables difficult to represent within a unified gradient-based optimization framework. This study develops a continuous parameterization method for embedded inlets that simultaneously controls cross-sectional profiles, area distribution, and centerline under large cross-sectional rotation angles. The method combines B-spline curves, shape blending functions, quaternion-based transformations, and free-form deformation (FFD) to establish a hybrid parameterization framework for coupled internal–external flow optimization. Analytical geometric sensitivities of the inlet surface mesh with respect to profile, area-distribution, and centerline variables are derived through the complete parameterization chain and coupled with discrete-adjoint flow sensitivities, enabling gradient evaluation for both external aerodynamic-shape and internal inlet-geometry variables. The framework is applied to full-configuration multipoint optimization of an aircraft with an embedded inlet. Aerodynamic drag is reduced by 2.82% and 2.36% at the two design points, while inlet drag decreases by 4.44 and 4.63 counts (1 count = 0.0001). Under distortion-coefficient and mass-flow-rate constraints, the inlet-exit total pressure recovery coefficient increases by 0.54% and 0.41%, respectively. These results demonstrate the effectiveness of the proposed method for integrated internal–external flow optimization and its potential for airframe–engine integrated design.

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Publication Details

Journal
Aerospace
Published
2026-09-13
DOI
https://doi.org/10.3390/aerospace13090835
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
article
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article

Gradient-Based Internal–External Flow Coupling Optimization for Embedded-Inlet Aircraft

Yayun Shi, Tihao Yang, Yiwen Wang, Libo Wang et al.
Aerospace
Computational Fluid Dynamics and Aerodynamics
article

Gradient-Based Internal–External Flow Coupling Optimization for Embedded-Inlet Aircraft

Yayun Shi, Tihao Yang, Yiwen Wang, Libo Wang, Yuning Liu
article en

Abstract

As aerodynamic configurations become increasingly integrated with propulsion systems, internal–external flow coupling has become a key issue in airframe–engine integration. For embedded-inlet configurations, however, the airframe and inlet/exhaust system have different geometric shaping requirements, making their design variables difficult to represent within a unified gradient-based optimization framework. This study develops a continuous parameterization method for embedded inlets that simultaneously controls cross-sectional profiles, area distribution, and centerline under large cross-sectional rotation angles. The method combines B-spline curves, shape blending functions, quaternion-based transformations, and free-form deformation (FFD) to establish a hybrid parameterization framework for coupled internal–external flow optimization. Analytical geometric sensitivities of the inlet surface mesh with respect to profile, area-distribution, and centerline variables are derived through the complete parameterization chain and coupled with discrete-adjoint flow sensitivities, enabling gradient evaluation for both external aerodynamic-shape and internal inlet-geometry variables. The framework is applied to full-configuration multipoint optimization of an aircraft with an embedded inlet. Aerodynamic drag is reduced by 2.82% and 2.36% at the two design points, while inlet drag decreases by 4.44 and 4.63 counts (1 count = 0.0001). Under distortion-coefficient and mass-flow-rate constraints, the inlet-exit total pressure recovery coefficient increases by 0.54% and 0.41%, respectively. These results demonstrate the effectiveness of the proposed method for integrated internal–external flow optimization and its potential for airframe–engine integrated design.

AerospaceVol. 13(9)
Northwestern Polytechnical University (CN), Carolina Unmanned Vehicles (United States) (US), Xi'an Jiaotong University (CN)
Affordable and clean energy
Openalex Percentile: Top 13%
Computational Fluid Dynamics and Aerodynamics
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