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About Us

Our mission is to inspire new technology at the boundary between Fluid Mechanics and Cyber-Physical Systems (CPS). Think autonomous swimming robots or implantable body flow sensors. We are part of the Mechanical & Aerospace Engineering Department, the Electrical & Computer Engineering Department, and the Link Lab at the University of Virginia. Our current research is focused on 1) fish-like robots, 2) microscale quadrotors, and 3) body flow sensors. We’re working on ways that fluid modeling can improve the effectiveness of these devices and better integrate them into a smart and connected world. Scroll down to learn more about us and our research.

Meet

Our Team

Dan Quinn
Principal Investigator
Darius Carter
Expertise: MAV Stability
Lucy Fitzgerald
Expertise: Self-Powered Sensing
Qiang Zhong
Expertise: UUV Maneuvers
Lauren Bouchard
Expertise: MAV Rotor Wakes
Maria Contreras
Expertise: Self-Powered Sensing
Megan Mazzatenta
Expertise: MAV sensing
Arianna Asquini
Expertise: Tidal Heat Flux
Leo Liu
Expertise: Dynamic Ground Effect
Chris Fitzpatrick
Expertise: Piezoelectric Harvesters
See Our

Recent Publications

How dorsal fins make fish faster and more efficient

The dorsal and anal fins of fish interact with the tail fins to produce higher thrust and efficiency. We focused on thin elongated dorsal fins, like those of jackfish. We discovered that dorsal fins can act like the wing strakes of fighter jets, promoting flow attachment on a main lifting surface (wing/tail) by inducing spanwise flow and reducing the effective angle of attack. Beyond a critical sharpness, the effect is more costly than beneficial, meaning dorsal fins may be optimal when they are slightly blunted rather than razor sharp. See a video of the results here. (This work was done in collaboration with the Flow Simulation Research Group at the University of Virginia.)

Modeling lateral station-keeping in fish

Fish flap their tails asymmetrically to maneuver around obstacles. In contrast, classic fish tail models assume symmetric motions in a uniform flow. We tested how well these classic models work for maneuvering tails. In some cases, the models work well: even 2D wakeless models were able to predict the phase of high frequency lateral displacements. As for predicting overshoot and settling time, only a semi-empirical model was accurate to within 10%.

Stable equilibria exist for near-surface swimmers and fliers

Fish and birds experience different forces when they swim/fly near a flat surface (e.g. seabed, solid ground, still lake). We discovered that the vertical forces they feel switch from negative (downward) to positive (upward) at a particular distance from the surface. In other words, there’s a stable equilibrium altitude where they are neither pushed down nor up. Animals and bio-inspired robots should factor this altitude into their control schemes; ignoring it could lead to high energy costs when swimming/flying near a flat surface. (This work was done in collaboration with the Biofluids Research Lab at Lehigh University.)

How lovebirds maneuver through crosswinds in the dark

Pilots need complex instruments and training to safely fly through gusts when their vision is deprived. In contrast, birds fly reliably over open water and at night, despite being more susceptible to gusts due to their much lower flight speeds. We found that even inexperienced lovebirds can navigate through strong opposing gusts in the dark. Their ability is surprising, because it was previously thought that diurnal animals needed a visual horizon and image features moving over their retina to maneuver. (This work was the culmination of a multi-year project that started when PI Quinn was in the Lentink Lab at Stanford University.)

How Micro Aerial Vehicles could exploit ground and ceiling effects

Micro Aerial Vehicles (MAVs) have the potential to revolutionize search-and-rescue, product delivery, aerial mapping, and weather sensing. Current models for how MAVs interact with solid boundaries are based on helicopters, which operate at different length and speed scales. Here we compare existing and updated models with experimental thrust and flow field measurements, and we demonstrate how better near-ceiling and near-ground models could improve MAV efficiency and situational awareness. (This work was done in collaboration with the Bezzo Lab at the University of Virginia.)

All Publications

Contact Us

  • Let us know if you’re interested in joining our team! We are always looking for new exceptional lab members. Every year we can accept a few new undergraduate students, graduate students, and postdocs. Our team is strengthened by physical, intellectual, and cultural diversity; all persons of all backgrounds are encouraged to apply.
  • Let us know if you have questions/comments/ideas, and we’ll get back to you as soon as possible.


Where to find us:

MEC 104
122 Engineer's Way
Charlottesville, VA 22904