Wing kinematics measurement and aerodynamics of hovering mosquitoes <i>Aedes togoi</i>

The aerodynamic mechanisms underlying mosquito flight have long intrigued researchers but are still insufficiently understood. In this study, we measured for the first time the wing kinematics and morphological data of hovering mosquitoes Aedes togoi, a species with a larger body size and lower wingbeat frequency compared to previous studies, using high-speed camera techniques. The aerodynamic forces and flows generated by the wing were numerically simulated. Our findings indicate that the mosquito produces a small lift peak at the beginning and end of each half-stroke, with a larger lift peak in the middle phase. The kinematic-fluid-aerodynamic link is established, and the aerodynamic force production mechanisms of mosquitoes Aedes togoi different from other mosquito species are revealed. The difference lies in the middle stroke phase, where the aerodynamic forces are generated by the delayed stall mechanism in conjunction with the fast pitch-up mechanism. Furthermore, the power consumption of these mosquitoes is dominated by aerodynamic power, with a mass-specific power of approximately 28.9 W/kg, comparable to that of other mosquito species. These insights deepen our understanding of mosquito flight mechanics and behavior, while also offering valuable guidance for the design of bio-inspired flapping-wing vehicles with small stroke amplitudes.

Authors

Institutions

Publication Details

Journal
Physics of Fluids
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0257527
Primary Topic
Biomimetic flight and propulsion mechanisms
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Wing kinematics measurement and aerodynamics of hovering mosquitoes Aedes togoi

Xueguang Meng, Zengshuang Chen, Kexin Li, Gang Chen
Physics of Fluids
Biomimetic flight and propulsion mechanisms
article

Wing kinematics measurement and aerodynamics of hovering mosquitoes Aedes togoi

Xueguang Meng, Zengshuang Chen, Kexin Li, Gang Chen
article en

Abstract

The aerodynamic mechanisms underlying mosquito flight have long intrigued researchers but are still insufficiently understood. In this study, we measured for the first time the wing kinematics and morphological data of hovering mosquitoes Aedes togoi, a species with a larger body size and lower wingbeat frequency compared to previous studies, using high-speed camera techniques. The aerodynamic forces and flows generated by the wing were numerically simulated. Our findings indicate that the mosquito produces a small lift peak at the beginning and end of each half-stroke, with a larger lift peak in the middle phase. The kinematic-fluid-aerodynamic link is established, and the aerodynamic force production mechanisms of mosquitoes Aedes togoi different from other mosquito species are revealed. The difference lies in the middle stroke phase, where the aerodynamic forces are generated by the delayed stall mechanism in conjunction with the fast pitch-up mechanism. Furthermore, the power consumption of these mosquitoes is dominated by aerodynamic power, with a mass-specific power of approximately 28.9 W/kg, comparable to that of other mosquito species. These insights deepen our understanding of mosquito flight mechanics and behavior, while also offering valuable guidance for the design of bio-inspired flapping-wing vehicles with small stroke amplitudes.

Physics of FluidsVol. 37(3)
Xi'an Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 94%
Biomimetic flight and propulsion mechanisms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.