论文标题
灵活的Calliphora机翼的实验数据驱动的质量弹力模型
An experimental data-driven mass-spring model of flexible Calliphora wings
论文作者
论文摘要
由于惯性,弹性和空气动力,昆虫的翅膀在拍打运动过程中会发生明显的变形。形状的变化然后改变空气动力,从而导致完全耦合的流体结构相互作用(FSI)问题。在这里,我们介绍了在拍打飞行中详细的三维FSI模拟(Calliphora vomitoria)机翼。使用多参数质量弹簧方法提出了机翼模型,该方法是为其实施简单和计算效率而选择的。我们通过使用具有协方差矩阵适应(CMA-ES)的遗传算法来优化其参数来训练模型来重现静态弹性测量。然后,训练有实验数据的机翼模型与在大量平行的超级计算机上运行的高性能流求解器耦合。讨论了建模方法的不同特征和弹性特性的内物种变异性。我们发现,具有不同机翼刚度的个体具有相似的空气动力特性,其特征是在相同的雷诺数下具有无量纲的力和功率。我们通过比较柔性翅膀及其刚性对应物之间的比较进一步研究机翼柔韧性的影响。在刚性和柔性机翼的相等规定的运动条件下,机翼柔韧性提高了提升与拖拉的比率以及升力比率,并减少了在机翼旋转过程中观察到的峰值力。
Insect wings can undergo significant deformation during flapping motion owing to inertial, elastic and aerodynamic forces. Changes in shape then alter aerodynamic forces, resulting in a fully coupled Fluid-Structure Interaction (FSI) problem. Here, we present detailed three-dimensional FSI simulations of deformable blowfly (Calliphora vomitoria) wings in flapping flight. A wing model is proposed using a multi-parameter mass-spring approach, chosen for its implementation simplicity and computational efficiency. We train the model to reproduce static elasticity measurements by optimizing its parameters using a genetic algorithm with covariance matrix adaptation (CMA-ES). Wing models trained with experimental data are then coupled to a high-performance flow solver run on massively parallel supercomputers. Different features of the modeling approach and the intra-species variability of elastic properties are discussed. We found that individuals with different wing stiffness exhibit similar aerodynamic properties characterized by dimensionless forces and power at the same Reynolds number. We further study the influence of wing flexibility by comparing between the flexible wings and their rigid counterparts. Under equal prescribed kinematic conditions for rigid and flexible wings, wing flexibility improves lift-to-drag ratio as well as lift-to-power ratio and reduces peak force observed during wing rotation.