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改进的模拟退火算法在翼型设计中的应用 被引量:3

The Application of an Improved Simulated Annealing Algorithm to Airfoil Design
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摘要 通过研究模拟退火算法的机理和应用,对标准模拟退火算法进行了改进,并应用到翼型气动优化中。改进算法与标准算法相比,在耗费机时基本一致的情况下,优化了初始翼型NACA0012,使其设计点的阻力分别减小了30.16%和32.95%。由此可见,模拟退火算法在翼型气动优化设计中具有实用性和有效性,并且改进算法的优化效果更理想。 Comparing with traditional deterministic methods, the simulated annealing algorithm is a stochastic global search algorithm. It has been proven to be a good tool for complex nonlinear optimization problems and applied to a variety of engineering problems. In this paper, the standard simulated annealing algorithm is improved and it is applied to aerodynamic optimization design for airfoil shape. The original airfoil NACA0012 is optimized respectively by the standard algorithm and the improved one. The drag of the design point decreases respectively as 30. 16% and 32. 95% while the CPU time is about the same. It shows that the simulated annealing algorithm is applicable and effective for airfoil design. Furthermore, the improved algorithm may obtain much better result.
出处 《飞行力学》 CSCD 北大核心 2008年第1期71-74,共4页 Flight Dynamics
基金 国家自然科学基金资助项目(10502043) 航空科学基金资助项目(05A53003)
关键词 模拟退火算法 改进的模拟退火算法 翼型设计 simulated annealing algorithm improved simulated annealing algorithm airfoil design
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参考文献3

  • 1Allen Gardner B, Michael S Selig. Airfoil Design Using a Genetic Algorithm and an Inverse Method [ R ]. AIAA 2003-0043,2003.
  • 2Klein M,Sobieczky H. Sensitivity of Aerodynamic Optimization to Parameterized Target Functions [ R ]. Proceedings of the International Symposium on Inverse Problems in Engineering Mechanics ( ISIP 2001 ) ,2001.
  • 3Ng K Y,Tan C M,Ray T,et al. Single and Muhiobjective Wing Planform and Airfoil Shape Optimization Using a Swarm Algorithm[ R]. AIAA 200343045,2003.

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