Wall shear-stress extraction by an optical flow algorithm with a sub-grid formulation

In this study,we developed a novel optical-flow algorithm for determining the wall shear-stress on the surface of objects.The algorithm solves the thin-oil-film equation using a numerical scheme that recovers local features neglected by smoothing filters.A variational formulation with a smoothness constraint was applied to extract the global shear-stress fields.The algorithm was then applied to scalar images generated using direct numerical simulation(DNS)method,which revealed that the errors were smaller than those of conventional methods.The application of the proposed algorithm to recover the wall shear-stress on a low-aspect-ratio wing and on an axisymmetric boattail model taken as examples in this study showed a strong potential for analysing shear-stress fields.Compared to the methods used in previous studies,proposed method reveals more local features of separation line and singular points on object surface.

Study of vertically ascending flight of a hawkmoth model

This paper provides insight into the wing kinematics,the power requirement and the dynamic stability characteristics of a hawkmoth model in vertically ascending flight.The wing kinematics of the hawkmoth model is obtained based on the minimum required power assumption.The optimization process is conducted using genetic and simplex algorithms that are coupled with an artificial neural network to rapidly predict the aerodynamic force and required power.The training data for the neural network are generated from an unsteady vortex-lattice method.Compared to hover,the results in this study show the larger flapping frequency and the smaller rotation amplitude of the hawkmoth wing kinematics in ascending flight.Additionally,more power is required when the ascending speed increases.While conducting a dynamic modal analysis based on a cycle-average approach,the certain effect of the ascending speed on the modal structures of the hawkmoth model was observed.