Cha Chong Song,
Ryu Tong Hwi,
Kim Yong,
Han Yong Gil,
Ho Myong Su,
Kim Un Il,
- Professor, Department of Mechanical Science and Technology, Kim Chaek University of Technology, Pyongyang, North Korea
- Professor, Department of Mechanical Science and Technology, Kim Chaek University of Technology, Pyongyang, North Korea
- Professor, Department of Mechanical Science and Technology, Kim Chaek University of Technology, Pyongyang, North Korea
- Professor, Department of Mechanical Science and Technology, Kim Chaek University of Technology, Pyongyang, North Korea
- Professor, Department of Mechanical Science and Technology, Kim Chaek University of Technology, Pyongyang, North Korea
- Professor, Department of Mechanical Science and Technology, Kim Chaek University of Technology, Pyongyang, North Korea
Abstract
It is well known that aerodynamic performance of a UAV is very sensitive to the wing shape and flight conditions, and inevitable uncertainties such as wing manufacturing errors and wind variations may lead to drastic deterioration in its aerodynamic performance. In the UAV wing design, therefore, it is required not to use the conventional design optimization approach considering only optimality of performance at the design point, but to use the robust design optimization approach considering both optimality and robustness of performance against any uncertainties. The study describes a Multi- Objective Six Sigma Design of the subsonic airfoil with the purpose function of both the expected value and the dispersion of the lift-to-drag ratio of the airfoil with respect to the Mach number and the attack angle. First, it shows that the optimal control points of the cubic B-spline are obtained by means of the Integer Quadratic Programming for the initial airfoil. Finally, the robust design of airfoil was carried out with the aid of Isight 2017, regarding the obtained control points as the design variables and under consideration of the uncertainty of Mach number and attack angle. Here, the Multi-Objective Six Sigma Design of the airfoil was done in combination of six sigma analysis based on Monte-Carlo method with Multi-Objective Particle Swarm method to improve the optimization and robustness of the lift-to-drag ratio. A new optimization approach for robust design, Multi-Objective Six Sigma Design, has been developed and applied to robust aerodynamic airfoil design for subsonic UAV. The present robust aerodynamic airfoil design optimization using this approach successfully showed robustness improvement in aerodynamic performance. The obtained result indicated that an airfoil with a smaller maximum camber improves robustness of lift to drag ratio against the variation of flight Mach number and attack angle.
Keywords: Airfoil, robust design, multi-objective six sigma analysis, lift to drag ratio, spline approximation
[This article belongs to Journal of Aerospace Engineering & Technology ]
Cha Chong Song, Ryu Tong Hwi, Kim Yong, Han Yong Gil, Ho Myong Su, Kim Un Il. Robust Design of Subsonic Airfoil by Multi-Objective Six Sigma Approach. Journal of Aerospace Engineering & Technology. 2025; 15(03):14-23.
Cha Chong Song, Ryu Tong Hwi, Kim Yong, Han Yong Gil, Ho Myong Su, Kim Un Il. Robust Design of Subsonic Airfoil by Multi-Objective Six Sigma Approach. Journal of Aerospace Engineering & Technology. 2025; 15(03):14-23. Available from: https://journals.stmjournals.com/joaet/article=2025/view=228115
References
- Elouardi S, El Maani R, Radi B. Probabilistic study of the aerodynamic around a 3D wing. Adv Theor Appl Mech. 2018; 11(1): 49–59.
- Hollom J. Optimization of natural laminar flow aerofoils and wings for robustness to critical transition amplification factor. Thesis. Sheffield: The University of Sheffield; 2018; 13–162. 0.1 0.0 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 0 100 110 120 130 140 150 160 L. Bound: 0 -6.226 sigma Quality: 8 sigma Mean: 122.8 7 Std. Dev.: 5.283
- Zhang Y, Fang X, Chen H, Fu S, Duan Z, Zhang Y. Supercritical natural laminar flow airfoil optimization for regional aircraft wing design. Aerosp Sci Technol. 2017; 70: 568–577.
- Tao J, Sun G, Si J, Wang Z. A robust design for a winglet based on NURBS-FFD method and PSO algorithm. Aerosp Sci Technol. 2015; 43: 152–164.
- Engineous Software, Inc. Isight component guide. Version 2017.1. 2016; 134–193.
- DeGennaro AM, Rowley CW, Martinelli L. Uncertainty quantification for airfoil icing using. J Aircraft. 2015; 52(5): 1404–1411.
- Coder JG, Maughmer MD. Comparisons of theoretical methods for predicting airfoil aerodynamic characteristics. J Aircraft. 2014; 51(1): 183–191.
- Li J, Gao Z, Huang J, Zhao K. Robust design of NLF airfoils. Chin J Aeronaut. 2013; 26(2): 309–318.
- Ghadimi P, Rostami AB, Jafarkazemi F. Aerodynamic analysis of the boundary layer region of symmetric airfoils at ground proximity. Aerosp Sci Technol. 2012; 17: 7–20.
- Papoutsis-Kiachagias EM, Papadimitriou DI, Giannakoglou KC. Discrete and continuous adjoint methods in aerodynamic robust design problems. In: Proceedings of an ECCOMAS Thematic Conference; Antalya, Turkey. 2011 May; 61–64.
- Ma R, Liu P. Numerical simulation of low-Reynolds-number and high-lift airfoil S1223. In: Proceedings of the World Congress on Engineering, 2009 Jul 1–3; London, UK. 2009; II: 1–6.
- Koch PN, Wujek B, Golovidov O, Simpson TW. Facilitating probabilistic multidisciplinary design optimization using Kriging approximation models. AIAA Paper 2002–5415; 2002 Sep.
- Deb K. Multi-objective optimization using evolutionary algorithms. Chichester: John Wiley & Sons; 2001.
- Fonseca CM, Fleming PJ. Genetic algorithms for multi-objective optimization: formulation, discussion and generalization. In: Proceedings of the 5th International Conference on Genetic Algorithms; San Mateo, CA, USA. 1993; 416–423.
- Drela M, Giles MB. Viscous-inviscid analysis of transonic and low Reynolds number airfoils. AIAA J. 1987; 25(10): 1347–1355.

Journal of Aerospace Engineering & Technology
| Volume | 15 |
| Issue | 03 |
| Received | 30/06/2025 |
| Accepted | 18/09/2025 |
| Published | 25/09/2025 |
| Publication Time | 87 Days |
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