基于多岛遗传算法的二维翼型吸气减阻优化

针对吸气减阻技术吸气质量较大的缺点,采用多岛遗传算法与计算流体力学(CFD)相结合的方法,对吸气减阻技术进行了优化.数值计算采用E387二维翼型,将吸气开口位置和吸气质量通量作为优化参数,通过寻找上翼面最佳的吸气开口位置,使翼型阻力和吸气质量最小.结果表明:多岛遗传算法能够有效地优化吸气开口位置和吸气质量;当吸气开口位于最佳位置时,吸气质量达到了寻优区间下限,而翼型减阻效果可达8.3%;吸气没有延缓流动转捩的发生,翼型阻力减小的原因主要是由于压差阻力的减小.

Optimization of drag-reduction by suction using multi-island genetic algorithm

To overcome the drawback of large suction mass requirement, the suction control for drag reduction was optimized. Computational fluid dynamics (CFD) in conjunction with multi-island genetic algorithm was employed as the tool to achieve the optimization. E387 airfoil was employed as the physical model. The suction location and mass flux of slot were set as the design optimization variables. The goal was to minimize both the airfoil drag and suction mass requirement by identifying the optimal suction location on the upper airfoil surface. The results show that the suction location and the suction mass requirement could be optimized by multi-island genetic algorithm. When the suction location is optimal, the mass flux of slot reaches the lower limit of the optimization interval with the airfoil drag reduced up to 8.3%. The occurrence of transition is not delayed by suction control so that friction drag is not reduced and the airfoil drag reduction is mainly due to the reduction in pressure drag.