Efficient optimisation of large aircraft fuselage structures

This paper presents an innovative optimisation method for aircraft fuselage structural design. Detailed local finite element analyses of panel buckling are further processed such that they can be applied as failure constraints in the global level optimisation. The high computational costs involved with the finite element analyses are limited by advanced use of surrogate modelling methods. This yields high flexibility and efficiency in the local level optimisation procedure and allows for efficient gradient based search methods as well as more costly direct search optimisations like genetic algorithms (GAs). The method is demonstrated on a composite fuselage barrel design case considering common structural sizing variables like thicknesses and stringer dimensions. Optimised barrel designs are obtained where the constraints that are derived from the panel buckling analyses are active. The total computational cost for the complete local and global level optimisation procedures is in the order of days on common-performance hardware.

[1]  J. Renaud,et al.  Approximation in non-hierarchic system optimization , 1992 .

[2]  Nathalie Bartoli,et al.  Approximation of the critical buckling factor for composite panels , 2012 .

[3]  Jaroslaw Sobieszczanskisobieski,et al.  On the sensitivity of complex, internally coupled systems , 1988 .

[4]  J. Sobieszczanski-Sobieski,et al.  Structural optimization by multilevel decomposition , 1983 .

[5]  J. Renaud,et al.  Approximation in nonhierarchic system optimization , 1994 .

[6]  Jaroslaw Sobieszczanski-Sobieski,et al.  Structural sizing by generalized, multilevel optimization , 1987 .

[7]  Raphael T. Haftka,et al.  Variable-complexity aerodynamic optimization of a high-speed civil transport wing , 1994 .

[8]  Layne T. Watson,et al.  Computational study of a nonhierarchical decomposition algorithm , 1993, Comput. Optim. Appl..

[9]  Christos Kassapoglou,et al.  Design and Analysis of Composite Structures: With Applications to Aerospace Structures , 2010 .

[10]  Timothy W. Simpson,et al.  Metamodels for Computer-based Engineering Design: Survey and recommendations , 2001, Engineering with Computers.

[11]  Afzal Suleman,et al.  Comparison of Surrogate Models in a Multidisciplinary Optimization Framework for Wing Design , 2010 .

[12]  Michael Beers,et al.  A Linearization Method for Multilevel Optimization , 1987 .

[13]  Jaroslaw Sobieszczanski,et al.  A Mixed Optimization Method for Automated Design of Fuselage Structures , 1972 .

[14]  David Bassir,et al.  Numerical Optimization applied to structure sizing at AIRBUS: A multi-step process , 2009 .

[15]  F. Jose,et al.  Convergence of Trust Region Augmented Lagrangian Methods Using Variable Fidelity Approximation Data , 1997 .

[16]  Bernard Grossman,et al.  A Coarse-Grained Parallel Variable-Complexity Multidisciplinary Optimization Paradigm , 1996, Int. J. High Perform. Comput. Appl..