Abstract:

In future aircraft design, the desired performance indexes are not only more rigorous, but also more numerous. Therefore, aerodynamic design should achieve high definition shape design and satisfy the multiple design requirements. It is consequently necessary to establish a multivariable optimization model in aerodynamic design. In this paper, a test example is provided to show the advantage and disadvantage of the multivariable model in aerodynamic optimization. While the optimized results are significantly heightened, searching difficulty also increases for the optimization algorithm. Meanwhile, because of the coupling disturbance among different design parameters, it is difficult to achieve global optimized results. So in this paper a sampling mean-response sensitivity analysis is carried out to measure the importance of design parameters, which are then grouped based on their importance level. Subsequently the multilevel collaborative optimization design method based on system decomposition is used to reduce the system complicacy. It ensures the precision of the multivariable optimization model and resolves the searching difficulty of the optimization algorithm. An example for a wing-body optimization is carried out using the above method and the result shows its feasibility and advantage as compared with the traditional aerodynamic optimization method.

Key words: multivariable system, aerodynamic design, sensitivity analysis, system decomposition, multilevel collaborative optimization