论文标题
用于机翼统计分析的压力分布特征的自适应采样
Adaptive sampling of pressure distribution features for the airfoil statistical analysis
论文作者
论文摘要
在超临界翼设计领域，进行理论和实验分析的学者总结了各种原则，法律和规则。这些规则的适用性通常受到调查的机翼样品的限制。随着计算流体动力学和计算智能的发展，可以更好地在计算机上进行此类工作。本文提出了一种输出空间采样方法，以生成具有指定压力分布或满足某些特殊要求的机翼样品。然后将良好的选择和分布式样品用于统计研究，以获得更可靠或更普遍的空气动力学规则，这些规则可以用作超临界机翼设计过程中的指导。输出空间采样方法在填充空间和探索边界方面的功能也得到了改善。输出空间采样方法用于生成具有不同需求的超临界机翼样品，从而允许冲击波位置与阻力发散马赫数以及拖动蠕变特性之间的关系。
In the area of supercritical wing design, a variety of principles, laws and rules have been summarized by scholars who perform theoretical and experimental analyses. The applicability of these rules is usually restricted by the airfoil samples investigated. With the advance of computational fluid dynamics and computational intelligence, such work can be better conducted on computers. The present paper proposes an output space sampling method to generate airfoil samples that have specified pressure distributions or meet certain special requirements. The well-selected and distributed samples are then utilized for statistical studies to obtain more reliable or more universal aerodynamics rules that can be used as guidance in the process of supercritical airfoil design. The capabilities of the output space sampling method in regard to filling the space and exploring the boundaries are also improved. The output space sampling method is employed to generate supercritical airfoil samples with different requirements, allowing the relationships between the shock wave location and the drag divergence Mach number as well as the drag creep characteristic to be revealed.
