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Optimization of Full Composite Body of the Scaled Jas39 Fighter Aircraft Model Using Genetic Algorithm

Jafari, Mohammad Amin | 2008

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 39208 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Abedian, Ali
  7. Abstract:
  8. Popular usage of composite materials in aerospace, civil and defense industries in the last decades has been the cause for paying more attention to optimization of composites tailoring. Due to inherent complexity of composite problems, i.e. discrete nature, complex interrelationship of design variables, existence of so many local optimum points, and etc., gradient base methods of optimization are found to be incapable and as a result using other powerful methods seems inevitable. Nowadays Genetic algorithm (GA) as an evolutionary technique is used for tackling composite problems. The success of a genetic algorithm can be quantified by estimating the cost, time required and the quality of final solution obtained. GA requires the specification of a number of parameters for which users usually don’t know how to specify i.e. cross over rate, mutation rate population size and etc. In this research work fuselage of a full composite scaled Jas39 was optimized by genetic algorithm. A previously developed GA code was linked with Ansys commercial FEM software. The FEM geometry model of the fuselage was developed bye use of a Coordinate Measuring Machine (CMM). Then the full geometry model was created by POWERSHAPE software which finally meshed by Hypermesh7 software. As for the loading the X-plane software and the flight pocket of the plane were used. X-plane is a program that simulates maneuver and flight conditions that aircraft located in those. The cost function was considered to be a combination of weight and deflection. Maximum deflection and Tsi-wu strength index were considered as constraints. Maximum deflection must be less than 10 millimeters and Tsi-wu strength index must be less than 0.67 with paying attention to safety factor 1.5. Here, three different numbers of initial populations were considered. The initial population with 15 chromosomes appeared to gain best result; it seems for problem with so many design variables there may exists an optimum number of chromosomes for the initial population. Finally, this initial population provided the best composite layout with 30% weight saving for the fuselage compared to the real model of the fuselage.
  9. Keywords:
  10. Optimization ; Laminated Composite Materials ; Genetic Algorithm ; Rejuvenation Treatment ; Laminate Sequence Design ; Aircraft ; Full Composit Body

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