Optimization and Design of General Aviation Aircrafts Wing Using Non-Dominated Sorting Genetic Algorithms II

Pazooki, Farshad; Zibafar, Amirreza; Rahmati Lish, Mostafa

doi:10.22034/joae.2021.303370.1055

Optimization and Design of General Aviation Aircrafts Wing Using Non-Dominated Sorting Genetic Algorithms II

Document Type : Original Article

Authors

Farshad Pazooki

Amirreza Zibafar

Mostafa Rahmati lish

Department of Aerospace Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

10.22034/joae.2021.303370.1055

Abstract

The main idea of this paper is to Adopt the optimal design of the general aviation aircraft wing to reach the optimal range and weight. For this purpose, the non-dominated sorting genetic algorithm II; has been used as an optimization tool for reducing three significant elements of aircraft design, including decisions that require a trade-off, time, and cost. The cost function of the optimization was the minimization of wing weight and maximization of aircraft range which was constrained by Four penalty functions and limiting decisions variables. The first function constraint was lift coefficient which should be equal to the lift coefficient required for supporting aircraft weight at cruise flight. The second and the third functions were Taper-Ratio, and tip to root maximum thickness ratio must be between one and zero. The fourth function was to constrain the sum of the absolute value of twist with incidence angle that must be greater or equal to the absolute value of wing zero lift. The fifth penalty function does not allow the lift-to-drag ratio to exceed the maximum limit of the lift-to-drag ratio. Design parameters were root chord, tip chord, wingspan, incidence angle, twist angle, airfoil zero-lift angle of attack, maximum thickness to chord ratio tip, and chord. In the end, the optimal wing shape design was proposed and validated with the target aircraft. The results show that compared to the most efficient target aircraft, 6.84% improvement in range but 2.87% increased weight has been achieved in the optimal response to the problem

Keywords

Optimization

General Aviation

Wing Design

Genetic Algorithm

20.1001.1.17359449.1400.23.2.9.4

[1] R. Perez, H. Liu, K. Behdinan, Flight Dynamics and Control Multidisciplinary Integration in Aircraft Conceptual Design Optimization, Proceedings of The 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, New York: AIAA, pp. 1-10, 2004.

[2] S. M. B. Malaek, A. Ghorbani, Aircraft conceptual design based on genetic algorithm, Aerospace Mechanics Journal, Vol. 1, No. 1, pp. 101-114, 2005. (in Persian)

[3] J. Cavalcanti, B. Mattos, P. Paglione, Optimal Conceptual Design of Transport Aircraft, Proceedings of The 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Virginia: AIAA, pp. 1-22, 2006.

[4] L. Cavagna, L. Riccobene, S. Ricci, A. Bérard, A. Rizzi, A fast MDO tool for aeroelastic optimization in aircraft conceptual design, Proceedings of The 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, British Columbia: AIAA, pp. 1-17, 2008.

[5] Alonso, J.J. & LeGresley, P. & Pereyra, V., 2009. "Aircraft design optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(6), pages 1948-1958.

[6] R. Ramanna, M. Kumar, K. Sudhakar, K. Harinarayana, Multidisciplinary Design Optimization of Transport Class Aircraft, Chakrabarti, Amaresh, Prakash, Raghu V (Eds.), ICoRD'13 Global Product Development, pp. 125 135, India: Springer, 2013.

[7] J. Yoon, N.-V. Nguyen, S.-M. Choi, J.-W. Lee, S. Kim, Y.-H. Byun, Multidisciplinary General Aviation Aircraft Design Optimizations Incorporating Airworthiness Constraints, Proceedings of the 10th AIAA aviation technology, integration, and operations (ATIO) conference, Fort Worth: AIAA, pp. 1-12, 2010.

[8] Mi Baigang, Wang Xiangyu, "A New Aerodynamic Optimization Method with the Consideration of Dynamic Stability", International Journal of Aerospace Engineering, vol. 2021, Article ID 5551094, 9 pages, 2021. https://doi.org/10.1155/2021/5551094

[9] Nils Kleemann, Stanislav Karpuk and Ali Elham," Conceptual Design and Optimization of a Solar-Electric Blended Wing Body Aircraft for General Aviation", AIAA 2020-0008,Published Online:5 Jan 2020https://doi.org/10.2514/6.2020-0008

[10] Vedant Singh, Somesh K. Sharma, S. Vaibhav, "Transport Aircraft Conceptual Design Optimization Using Real Coded Genetic Algorithm", International Journal of Aerospace Engineering, vol. 2016, Article ID 2813541, 11 pages, 2016. https://doi.org/10.1155/2016/2813541

[11] A. R. Babaei and S. M. R. Setayandeh, ‘‘Constrained Optimization of a Commercial Aircraft Wing Using Non-Dominated Sorting Genetic Algorithms (NSGA)’’, Advanced Design and Manufacturing Technology, Vol. 8, No. 4, pp. 5, December – 2015

[12] Kalyanmoy Deb, Associate Member, Amrit Pratap, Sameer Agarwal, T. Meyarivan, ''A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II', IEEE Trans. Evolutionary Computation, VOL. 6, NO. 2, APRIL 2002

[13] Mitra, K. Multiobjective optimization of an industrial grinding operation under uncertainty. Chemical Engineering Science, 64, 23 2009), 5043-5056.

[14] Jianling, C. Multi-objective optimization of cutting parameters with improved NSGA-II. City, 2009.

[15] Kodali, S. P., Kudikala, R. and Deb, K. Multi-objective optimization of surface grinding process using NSGA II. City, 2008.

[16] Taylor, John W. R. Jane’s All the World’s Aircraft. Jane’s Yearbooks, 2018.

[17] Roskam, J., “Airplane Design”, part one, three and six, DARCorporation,1997.

[18] Sadraey, M. H., “Aircraft Design: a systems engineering approach”, John Wiley & Sons Publication,2013.

[19] D. P. Raymer, Aircraft Design: A Conceptual Approach, American Institute of Aeronautics

and Astronautics. Inc., Reston, Va, USA, 1999

[20] Snorri Gudmundsson, General Aviation Aircraft Design: Applied Methods and Procedures, Butterworth-Heinemann, 2013

[21] E. Torenbeek, Synthesis of Subsonic Airplane Design, Delft University Press, Delft,The Netherlands, 1982.

[22] M. Gen and R. Cheng, “Survey of penalty techniques in genetic algorithms,” in Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 804–809, IEEE, May 1996.

[23] M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization, vol. 7, JohnWiley,1999