Experimental and numerical investigation of wing–wing interaction and its effect on aerodynamic force of a robotic dragonfly during hovering and forward flight

Swain, Prafulla Kumar; Dora, Siva Prasad

doi:10.1007/s00419-020-01868-z

Cited by 11 publications

(2 citation statements)

References 37 publications

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“…There are many reports on the study of forewing and hindwing interactions in dragonflies. It was proven that dragonflies can produce additional aerodynamic forces from forewing and hindwing interactions [33]. At present, the wing deformation and flow phenomenon around the gap have not been further analyzed due to the limitations of our experimental platform.…”

Section: Discussionmentioning

confidence: 99%

Lift enhancement of a butterfly-like flapping wing vehicle by reinforcement learning algorithm

et al. 2023

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In order to enhance the take-off lift of a butterfly-like flapping wing vehicle, we implemented an integrated experimental platform and applied a reinforcement learning algorithm. The vehicle, which has a wingspan of 81cm and is mounted on a stand with a force sensor, is driven by two servos that are powered and controlled wirelessly. To achieve the goal of enhancing take-off lift, we used a model-free, on-policy actor-critic PPO algorithm. After 300 learning steps, the average aerodynamic lift force increased significantly from 0.044 N to 0.861 N. This enhanced lift force was sufficient to meet the take-off requirements of the vehicle without the need for any additional aids or airflow. Additionally, we observed a strong lift peak in the upstroke after analyzing the learning results. Further experiments showed that this lift peak is directly related to the elastic release of the wing twist and the opening and closing of the gap between the forewing and hindwing in the early stage of the upstroke. These findings were not easily predicted or discovered using traditional aerodynamic methods. This work provides valuable reinforcement learning experience for the future development of flapping-wing vehicles.

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Section: Discussionmentioning

confidence: 99%

Lift enhancement of a butterfly-like flapping wing vehicle by reinforcement learning algorithm

et al. 2023

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“…The higher the St, the higher the number of dipoles formed. A dipole formation at shorter distances leads to stronger synergy among vortices according to the Biot-Savart vortex induction law (Zheng & Wei [32]). Hence, at a higher value of St, the thrust and propulsive efficiency are higher compared to a lower value of St.…”

Section: The Vortex Flow Induced By a Single Foilmentioning

confidence: 99%

Thrust enhancement mechanism of a single and tandem flapping foil following an elliptical flapping trajectory

medna,

Kumar,

swain

et al. 2023

Preprint

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Flapping foil devices have drawn considerable attention as a new means of thrust generation devices. The present study investigates the hydrodynamic performance mechanism of a single and tandem flapping foil undergoing different flapping trajectories with two different phase angles, 0° and 180°. The hydrodynamic efficiency, such as propulsive efficiency and wake structure of the single and tandem hydrofoil, are examined using computational methods. The effect of Strouhal number (St) and stream-wise gap (Gx) was also discussed along with the flapping trajectory. The results show that by implementing the new flapping trajectory, the induced thrust of the trailing foil can be enhanced up to 45% compared to the simple flapping. This study shed new light on improving biomimetic propulsion devices, as it aims to enhance the elicited thrust of the hydrofoil.

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Effect of wing flexibility on the aerodynamic performance of a robotic dragonfly

et al. 2022

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Experimental and numerical investigation of wing–wing interaction and its effect on aerodynamic force of a robotic dragonfly during hovering and forward flight

Cited by 11 publications

References 37 publications

Lift enhancement of a butterfly-like flapping wing vehicle by reinforcement learning algorithm

Lift enhancement of a butterfly-like flapping wing vehicle by reinforcement learning algorithm

Thrust enhancement mechanism of a single and tandem flapping foil following an elliptical flapping trajectory

Effect of wing flexibility on the aerodynamic performance of a robotic dragonfly

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