Abstract
Flapping or oscillating foils are commonly investigated as bio-inspired propulsors, mimicking the efficient and agile acceleration of fish and marine mammals. When flapped at lower frequencies and higher amplitudes oscillating foils generate drag (not thrust) and power is generated from the resulting lift force. The objectives of this research are to predict the power generation abilities that is dominated by nonlinear leading-edge vortex (LEV) formation, the resulting wake formation, and the resulting vortex-foil interactions that occur for systems of oscillating foils.
Our results have shown there exists a wide kinematic range of heave/pitch amplitudes and oscillation frequencies for optimal power generation that occur through different mechanisms classified by the (LEV) formation. We present an image based convolutional autoencoder that can dimensionally reduce the data such that it can be clustered with an unsupervised algorithm, and predict efficiency based on a wake image snapshot. A model is then developed to predict the unsteady power generation of downstream foils in an array configuration.
About the Speaker
Jennifer Franck is an Associate Professor of Mechanical Engineering at the University of Wisconsin-Madison. Her research utilizes computational fluid dynamics to explore the flow physics of unsteady and turbulent flows with current projects funded by AFOSR, NSF and ARPA-E. She has an BS in Aerospace Engineering from University of Virginia, followed by a M.S. and Ph.D. from California Institute of Technology. She spent 9 years on the faculty at Brown University before moving to Wisconsin.
Host: Professor Leonardo Chamorro
