Multidisciplinary design optimization of a commercial aircraft wing - An exploratory study

1994 ◽  
2000 ◽  
Vol 122 (1) ◽  
pp. 70-76 ◽  
Author(s):  
Marc A. Stelmack ◽  
Stephen M. Batill ◽  
Bryan C. Beck

A multidisciplinary design optimization (MDO) framework has been used to design an aircraft brake assembly. This was done using a user-interactive implementation of the framework in which design information was obtained from analysis software used in industry but not developed for an MDO application. The design included a number of performance requirements associated with a brake that has been produced for a commercial aircraft. Design improvement was achieved using a practical number of system realizations and the interaction between the optimization algorithm and the design engineers was maintained throughout the process. [S1050-0472(00)00201-4]


Author(s):  
Xuan-Binh Lam

Multidisciplinary Design Optimization (MDO) has received a considerable attention in aerospace industry. The article develops a novel framework for Multidisciplinary Design Optimization of aircraft wing. Practically, the study implements a high-fidelity fluid/structure analyses and accurate optimization codes to obtain the wing with best performance. The Computational Fluid Dynamics (CFD) grid is automatically generated using Gridgen (Pointwise) and Catia. The fluid flow analysis is carried out with Ansys Fluent. The Computational Structural Mechanics (CSM) mesh is automatically created by Patran Command Language. The structural analysis is done by Nastran. Aerodynamic pressure is transferred to finite element analysis model using Volume Spline Interpolation. In terms of optimization algorithms, Response Surface Method, Genetic Algorithm, and Simulated Annealing are utilized to get global optimum. The optimization objective functions are minimizing weight and maximizing lift/drag. The design variables are aspect ratio, tapper ratio, sweepback angle. The optimization results demonstrate successful and desiable construction of MDO framework. Keywords: Multidisciplinary Design Optimization; fluid/structure analyses; global optimum; Genetic Algorithm; Response Surface Method.


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