İbrahim ÖZKOL, Abdurrahman HACIOĞLU

Kanat profili dizaynında genetik algoritma kullanımı

Bu çalışmada, kanat profili dizaynı amacıyla kullanılacak reel kodlu genetik algoritmalar için yeni bir yaklaşım olan titreşim kavramı ve bu kavramının uygulamasıyla ortaya çıkan Titreşimli Mutasyon tekniği açıklanmıştır. Titreşim kavramının arkasında yatan temel fikir, genetik algoritmanın arama/bulma etkinliğinin arttırılması için popülasyonun periyodik olarak çözüm uzayına yayılmasıdır. Bu amaçla kullanılan Titreşimli Mutasyon Tekniği ile popülasyondaki tüm bireyler periyodik olarak mutasyon işleminden geçirilir ve popülasyonda etkin bir çeşitlilik sağlanır. Vizkoz olmayan, sesaltı, sıkıştırılamaz akış şartlarındaki kanat profili dizaynı uygulamaları yöntemin etkinliğini göstermiş ve Hesaplamalı Akışkanlar Dinamiği hesabı sayısı önemli ölçüde azaltılmıştır.

Using genetic algorithm in airfoil design

In this study, new approaches to genetic algorithms used for aerodynamic design and optimization, called Vibration concept and its applications are made. Vibrational Mutation technique resulting from Vibration concept, and the method of Vibrational Genetic Algorithm, which uses this technique, are detailed. Vibration concept is based on the idea that the population is spread out over the design space periodically to make exploration/exploitation of the genetic algorithm more effective. The aim of Vibrational Mutation is to get effective diversity in the population by using mutation operator. Values of the individuals in the population are changed periodically in mutational manner by using Vibrational mutation technique during genetic process. So, the individuals concentrated on some region in the design space, spread out over the design space again. Thus, it is possible to escape local optimums quickly and to explore more fitting individuals. Therefore, genetic process gets faster and solution can be obtained by making less CFD calculation. Application of the method to a test function has given good results; genetic process have become faster about two times for aerodynamic optimization. Applying it to inverse airfoil design for subsonic, inviscid, incompressible flow condition, and the number of Computational Fluid Dynamics calculations are decreased considerably shows effectiveness of this method.

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Baker, J. E., (1987). Reducing Bias and Inefficiency in the Selection Algorithm, Proceedings of the Second International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, 14-21.
Ermiş M., Ülengin, F. ve Hacıoğlu A., (2002). Vibrational Genetic Algorithm (Vga) for Solving Continuous Covering Location Problems, Lecture Notes in Computer Science, 2457, 293-302.
Eshelman, L. J. ve Schaffer, J. D., (1993). Real Coded Genetic Algorithms and Interval Schemata, Foundations of Genetic Algorithms 2, Morgan Kaufmann Publishers, 187-202.
Falco, I. D., Cioppa, A. D., Balio, R. D. ve Tarantino, E., (1996). Breeder Genetic Algorithms for Airfoil Design Optimisation, IEEE International Conference on Evolutionary Computing, Nagoya.
Falco, I. D., Cioppa, A. D., Lazzetta, A. ve Tarantino, E., (1998). Mijn Mutation Operator for Airfoil Design Optimisation, Soft Computing in Engineering Design and Manufacturing, Springer Verlag, 211-220.
Hacıoğlu, A. ve Özkol, İ., (2002). Vibrational Genetic Algorithm as a New Concept in Aerodynamic Design, Aircraft Engineering and Aerospace Technology, 74, 3.
Kuethe, A. M., ve Chow, C-Y, (1998). Foundation of Aerodynamics, John Wiley and Sons, 161-163.
Mühlenbein, H. ve Schlierkamp-Voosen, D., (1993). Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization, Evolutionary Computation, 1, 25-49.
Obayashi, S., Takanashi, S. ve Takeguchi, Y., (1999). Niching and Elitist Model for MOGAs, Paralel Problem Solving from Nature-PPSN V, Lecture Notes in Computer Science, Springer, 260-269.
Tse, D. C. M. ve Chan, L. Y. Y., (1999). Application of Micro Genetic Algorithms and Neural Networks for Airfoil Design Optimization, RTO-MP-035 RTO-MP-035 Aerodynamic Design and Optimisation of Flight Vehicles in a Concurrent Multi-Disciplinary Environment.
Vicini, A. ve Quagliarella, D., (1999). Airfoil and Wing Design Through Hybrid Optimization Strategies, AIAA Journal, 37, 5.