Thursday, November 16, 2017
Dr. Joseph Zhu
University of Virginia
2:00 - 3:00pm
SEH, B1220
Abstract
Fish swimming outperforms traditional human-made autonomous underwater vehicles (AUVs) in many ways, such as speed, efficiency, maneuverability, and stealth. This can be attributed to their unique body shape, flexible fins, meticulously designed muscle and bone structures, and multiple sensory feedback system. Additionally, it is hypothesized that fish optimize their swimming locomotion in different situations, for example exploring and inhabiting various environments or surviving predator-prey encounters.
Very few studies, however, have investigated each contributory factors mentioned above individually to understand how they influence overall performance. In biology, it is incredibly challenging, if not impossible, to alter one parameter without affecting the others. A bio-inspired platform which mimics its biological counterpart provides opportunities to study underlying physics of fish swimming without following restricted conditions. In this talk, I will present our recent development of two platforms to study the influence of some key characteristics in fish locomotion.
The first platform is the MantaBot, which was inspired by biological design criteria in batoid fish: flattened rigid body and flexible actuators. The MantaBot body was rendered from a computer tomographic scanning image of a cownose ray. The flexible fins were made of elastomer in an airfoil cross-section shape. The fins were driven by active tensegrity structures. An additional rigid fin was attached to the rear of the body for pitch control. The vehicle was powered by a Li-ion battery pack and controlled by an Arduino microcontroller. A pressure sensor and a MEMS gyroscope/accelerometer device were equipped in the system for depth feedback control and navigation. Experiments were conducted in a water tank where the Mantabot was attached to a rail for rectilinear swimming. Optimal operation conditions (fin flapping amplitude and frequency) were determined for fastest swimming by surveying a wide range of parameters. Free swimming tests were done in a swimming pool. Our results show, under optimal condition, the MantaBot can swim faster than one body length per second and cruise about 7 km per charge.
The second platform mimics key characteristics of thunniform swimming. This platform has been designed to allow us to study the underlying physics of individual part as well as the entire system. Previous studies have shown that tuna fish are highly efficient swimmers stemming from their fusiform body shape, stiff crescent-shaped caudal fin, narrowed peduncle, and thunniform swimming mode. Our foci on the tuna swimming platform are the peduncle structure and the flexibility of caudal fin. Initial studies of biological peduncles showed that flexibility had a dramatic result on the economy of swimming. We designed an artificial peduncle based on a biological counterpart. We compared the swimming performance of the artificial peduncle with a rigid caudal fin to the biological one on the same platform. Our results showed that the artificial peduncle with a rigid caudal fin swam at speed about 80% of those with a biological one. Further study showed that the flexibility of the caudal fin might contribute more than 20% of the overall speed performance. We also designed 2D flexible panel structures inspired by fin-rays to study effects of isolated chordwise/spanwise flexibility on swimming performance. By 3D printing panels with uneven thickness, we can achieve anisotropic flexural stiffness in artificial fin design. Our results showed that a purely pitching rectangular panel with only chordwise flexibility has higher efficiency, while one with only spanwise flexibility loses both thrust and efficiency. The 2D skeleton-enhanced structure makes it feasible to fine-tune flexibility of an artificial fin and make it perform better than biology under certain circumstances.
Biography
Dr. Joseph Zhu is currently a research scientist at the department of Mechanical and Aerospace Engineering of the University of Virginia. He received his PhD degree in 1997 from Changsha Institute of Technology, China. He was a visiting scholar at Georgia Technology Institute in 2000 and later a postdoctoral associate at University of Pennsylvania in 2001.
Dr. Zhu’s research interests include autonomous underwater vehicles (AUVs), functional nano-porous materials, MEMS sensors and applications, and experimental microfluidic.