Collaborative Research: Bird flight in turbulence

This integrative project fills a significant knowledge gap in understanding bird flight by quantifying flight under the more challenging but realistic conditions of turbulence. Significant progress had been made in recent years characterizing and modeling bird flight in ideal, quiescent environments and in clean (laminar) flows. However, turbulent air flow environments are more common in nature and much less is known about flight in these non-ideal, unsteady environments. A series of experiments carried out in the specialized animal flight wind tunnel at Brown University will characterize changes in the kinematics, energetics, and group flight behavior of birds as they adjust to different levels of atmospheric turbulence. The results will not only inform the ecology and evolution of small birds and enhance understanding of the natural world, but will also advance the state of the art in the aerodynamics in unsteady flows, with applications in biotechnology and the design and engineering of bio-inspired aerial vehicles. Pursuing this project requires an interdisciplinary combination of biology and engineering represented by the three collaborators, and trainees will benefit from working across disciplines. In addition to training PhD students and postdoctoral fellows in the respective labs of the three universities participating in the project, a Research Experience for Undergraduates program will be offered during each project year. Undergraduates from around the nation will apply for a summer research fellowship to work on the project, and students with activities or coursework that indicate an interest in interdisciplinary work will be encouraged to participate. One student with a background in biology and another with a background in engineering or physical sciences will be selected to participate each year. The project will therefore contribute to interdisciplinary training and workforce development in AI-ML and bioinspired design. The research team will fly cockatiels in a wind tunnel and measure the changes due to turbulence in (i) metabolic activity using a labeled sodium bicarbonate technique, (ii) detailed wing and body kinematics using motion capture and high-speed videography, (iii) group flight behavior, and (iv) wake velocity signatures using particle image velocimetry. These experiments will be carried out with birds flying solo in the wind tunnel, birds flying together in small groups, and birds flying behind a robotic ornithopter mounted in the wind tunnel and operating with a prescribed flapping behavior. Lightweight body-mounted accelerometers will be used to measure flapping frequency and intensity, and to assess synchronization between different birds flying together in the wind tunnel or between the robot and bird, under the varying flow conditions. Machine learning and AI techniques will be developed to process and synthesize the multiple data streams (video, PIV, accelerometry, metabolic activity). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.