A hybrid multilevel approach for aeroelastic optimization of composite wing-box

The quest for finding optimum solutions to engineering problems has been existing for a long time. In the last decade several optimization techniques have been applied to the structural design of composite wing structures. Generally many of these proposed procedures have dealt with different discipl...

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Bibliographic Details
Published in:Structural and multidisciplinary optimization 2009-12, Vol.39 (6), p.607-624
Main Authors: Gasbarri, Paolo, Chiwiacowsky, Leonardo D., de Campos Velho, Haroldo F.
Format: Article
Language:English
Subjects:
Aerodynamics
Aeroelasticity
Aeronautics
Aerospace industry
Aircraft design
Composite wings
Computational Mathematics and Numerical Analysis
Couplings
Design optimization
Engineering
Engineering Design
Flight mechanics
Genetic algorithms
Industrial Application
Optimization techniques
Quadratic programming
Structural design
Theoretical and Applied Mechanics
Wing boxes
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Summary:The quest for finding optimum solutions to engineering problems has been existing for a long time. In the last decade several optimization techniques have been applied to the structural design of composite wing structures. Generally many of these proposed procedures have dealt with different disciplines such as aerodynamics, structures, or dynamics separately. However an aeronautical design process is multidisciplinary since it involves strong couplings and interactions among, for instance, aerodynamics, dynamics, flight mechanics and structures. The main problem in a multidisciplinary aircraft design is usually the development of an efficient method to integrate structures or structural properties, which can be considered both as “global” and “local” design variables. This paper describes an integrated aerodynamic / dynamic / structural optimization procedure for a composite wing-box design. The procedure combines an aeroelastic optimization of a composite wing based on a general purpose optimizer such as the Sequential Quadratic Programming (SQP) and a composite optimization using Genetic Algorithm (GA). Both the optimizations are implemented through a hybrid multilevel decomposition technique.
ISSN:1615-147X
1615-1488
DOI:10.1007/s00158-009-0429-6