Multivariable aerodynamic design based on multilevel collaborative optimization

Jiaozan Li, Zhenghong Gao

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish
Pages (from-to)58-65
Number of pages8
JournalHangkong Xuebao/Acta Aeronautica et Astronautica Sinica
Volume34
Issue number1
DOIs
StatePublished - Jan 2013

Keywords

  • Aerodynamic design
  • Multilevel collaborative optimization
  • Multivariable system
  • Sensitivity analysis
  • System decomposition

Fingerprint

Dive into the research topics of 'Multivariable aerodynamic design based on multilevel collaborative optimization'. Together they form a unique fingerprint.

Cite this