Using genetic algorithm in airfoil design

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. Anahtar Kelimeler: Titreşimli genetik algoritma, kanat profili dizaynı.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.  Keywords: Vibrational genetic algorithm, airfoil design

Reducing the Computational Effort Associated with Evolutionary Optimisation in Single Component Design

The dissertation presents innovative Evolutionary Search (ES) methods for the reduction in computational expense associated with the optimisation of highly dimensional design spaces. The objective is to develop a semi-automated system which successfully negotiates complex search spaces. Such a system would be highly desirable to a human designer by providing optimised design solutions in realistic time. The design domain represents a real-world industrial problem concerning the optimal material distribution on the underside of a flat roof tile with varying load and support conditions. The designs utilise a large number of design variables (circa 400). Due to the high computational expense associated with analysis such as finite element for detailed evaluation, in order to produce "good" design solutions within an acceptable period of time, the number of calls to the evaluation model must be kept to a minimum. The objective therefore is to minimise the number of calls required to the analysis tool whilst also achieving an optimal design solution. To minimise the number of model evaluations for detailed shape optimisation several evolutionary algorithms are investigated. The better performing algorithms are combined with multi-level search techniques which have been developed to further reduce the number of evaluations and improve quality of design solutions. Multi-level techniques utilise a number of levels of design representation. The solutions of the coarse representations are injected into the more detailed designs for fine grained refinement. The techniques developed include Dynamic Shape Refinement (DSR), Modified Injection Island Genetic Algorithm (MiiGA) and Dynamic Injection Island Genetic Algorithm (DiiGA). The multi-level techniques are able to handle large numbers of design variables (i.e. > 100). Based on the performance characteristics of the individual algorithms and multi-level search techniques, distributed search techniques are proposed. These techniques utilise different evolutionary strategies in a multi-level environment and were developed as a way of further reducing computational expense and improve design solutions. The results indicate a considerable potential for a significant reduction in the number of evaluation calls during evolutionary search. In general this allows a more efficient integration with computationally intensive analytical techniques during detailed design and contribute significantly to those preliminary stages of the design process where a greater degree of analysis is required to validate results from more simplistic preliminary design models

Three Dimensional Shape Optimization Of Bodies Subjected To Air Flow By Heuristic Algorithms

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2006Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2006Bu çalışmada titreşimli genetik algoritma yöntemi, dinamik ağ ve bir Euler akış çözücüsü ile birleştirilmiş ve üç boyutlu kanat modellerinin (Onera M6 kanadı) optimize edilmiştir. Onera M6 kanadı özellikle iki parametresi, kanat kesiti ve sivrilik oranı üzerinde, evrimsel algoritmalar ve paralel hesaplama yöntemleri kullanılarak iyileştirilmiştir. Akış alanlarını çözmek için ACER3D isimli Euler denklemlerini çözen program kullanılmıştır. Optimizasyon işlemleri sırasında elde edilen üç boyutlu modeller için yeni ağ yapıları dinamik ağ yöntemi kullanılarak bulunmuştur. Taşıma ve sürükleme gibi aerodinamik kuvvetler bir sonlu eleman yöntemiyle hesaplanmaktadır. Sonuçlar analiz edildiğinde, optimizasyon işleminin beklendiği şekilde geliştiği gözlemlenmektedir. Sürükleme kuvvetine yaklaşık yüzde 25 azaldığı görülmüştür. Ayrıca bu yapılırken taşıma kuvvetinin ve kalınlık oranının başta belirlenmiş dizayn taşıma kuvveti ve orijinal kalınlık oranına yakın kalması sağlanmıştır. Bu işlem uygunluk fonksiyonu ile ayarlanmaktadır. Program sürükleme kuvvetini minimize etmeye çalışırken sivrilik oranının azaldığı gözlemlenmiştir. Ancak bu azalma çok düşük seviyelere inememekte, belli bir aşamadan sonra hemen hemen sabit kalmaktadır, çünkü programın amacı sadece sürüklemeyi azaltmak değil aynı zamanda taşıma kuvvetini sabit tutmaktadır.In this study, evolutionary algorithms and dynamic mesh techniques have been combined for the design and optimization of a transonic wing by two parameters, the wing section and the taper ratio by using parallel computing. The Euler flow solver ACER3D has been used to obtain the flow parameters for each member. The unstructured tetrahedral mesh is modified according to the change in wing section and taper ratio by using dynamic mesh technique. Aerodynamic force, lift and drag, calculations have been done by using a finite element method. From the results, it is observed that the optimization process is working as expected. The drag coefficient has been reduced by about 25 percent. While this has been done, its lift coefficient and thickness ratio are tried to be close to the design values determined at the beginning. This is done by arranging the fitness function. The taper ratio is getting smaller while the code is trying to minimize the drag force. But it cannot be reduced to very small values and is kept almost the same at later steps, because the program should not only reduce the drag force but also keep the lift force close to the design value.DoktoraPh

A Framework for Hyper-Heuristic Optimisation of Conceptual Aircraft Structural Designs

Conceptual aircraft structural design concerns the generation of an airframe that will provide sufficient strength under the loads encountered during the operation of the aircraft. In providing such strength, the airframe greatly contributes to the mass of the vehicle, where an excessively heavy design can penalise the performance and cost of the aircraft. Structural mass optimisation aims to minimise the airframe weight whilst maintaining adequate resistance to load. The traditional approach to such optimisation applies a single optimisation technique within a static process, which prevents adaptation of the optimisation process to react to changes in the problem. Hyper-heuristic optimisation is an evolving field of research wherein the optimisation process is evaluated and modified in an attempt to improve its performance, and thus the quality of solutions generated. Due to its relative infancy, hyper-heuristics have not been applied to the problem of aircraft structural design optimisation. It is the thesis of this research that hyper-heuristics can be employed within a framework to improve the quality of airframe designs generated without incurring additional computational cost. A framework has been developed to perform hyper-heuristic structural optimisation of a conceptual aircraft design. Four aspects of hyper-heuristics are included within the framework to promote improved process performance and subsequent solution quality. These aspects select multiple optimisation techniques to apply to the problem, analyse the solution space neighbouring good designs and adapt the process based on its performance. The framework has been evaluated through its implementation as a purpose-built computational tool called AStrO. The results of this evaluation have shown that significantly lighter airframe designs can be generated using hyper-heuristics than are obtainable by traditional optimisation approaches. Moreover, this is possible without penalising airframe strength or necessarily increasing computational costs. Furthermore, improvements are possible over the existing aircraft designs currently in production and operation

Advances in Evolutionary Algorithms

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

Design optimization of small-scale unmanned air vehicles

Ph.DDOCTOR OF PHILOSOPH