Abstract
Aim: The introduction of the full paper discusses relevant matters and then proposes developing what we believe to be a better optimal design, which is explained in sections 1 through 4. The core of section 1 is that, with the particle swarm optimization and simulated annealing algorithm, the moving grid method and the improved Hicks-Henne function deformation technology, we parameterize the 18 design variables of the tip of a wing and its root respectively. Section 2 briefs the sampling method with the loose type of surrogate model. To train the samples, sections 3 and 4 use the Latin Hypercube method to evaluate the prediction ability of the Kriging agent model, whose prediction precision is shown in Fig.4. The core of section 4 is that we use the agent model to perform the optimal design of the subsonic wing of a certain typical aircraft; the optimal design results, given in Figs. 5 through 8, and their analysis show preliminarily that our design method is effective for improving the aerodynamic characteristics of subsonic wing.
Original language | English |
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Pages (from-to) | 515-519 |
Number of pages | 5 |
Journal | Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University |
Volume | 29 |
Issue number | 4 |
State | Published - Aug 2011 |
Keywords
- Agent model
- Moving grid method
- Navier-Stokes equations
- Particle swarm optimization
- Simulated annealing algorithm