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SUMMARY:MEchanics GAthering -MEGA- Seminar: Fluid physics driven bio-inspi
 red robots
DTSTART:20211118T161500
DTEND:20211118T173000
DTSTAMP:20260414T181552Z
UID:037f5a049000bc20bec41a923e994be9cb8172f43a1d5ff19e2adacf
CATEGORIES:Conferences - Seminars
DESCRIPTION:Qiang Zhong (Fluid Systems Lab\, University of Virginia)\nAbst
 ract Exploring\, monitoring\, and using oceans in a smart and sustainable
  way is an extreme challenge to current marine technologies. One of the so
 lutions could lie in autonomous marine robotic systems. Successful autonom
 ous robots must operate in complex and unstructured offshore environments\
 , so they should be ‘intelligent’- to accomplish missions autonomously
  and efficiently. Bio-inspired engineering is a popular way to endow auton
 omous robots with high-performance\, which requires three areas of experti
 se: flow physics\, robot design\, and control. However\, one of the critic
 al challenges could be the difficulties of transferring knowledge between 
 the three classic research areas\, therefore limiting the bio-inspired stu
 dies. In this talk\, we will present our recent effort that combines these
  three approaches to uncover one of the secrets of high-performance swimmi
 ng: what is the ‘best’ stiffness of a swimming fish-like robot? We fir
 st gained inspiration from real tuna tails by measuring tail stiffness res
 ponses\, then developed a reduced-order theoretical tuna model coupled wit
 h an aerodynamic model to explore the role of stiffness from a reduced-ord
 er modeling aspect. Furthermore\, our understanding of biomechanics\, flui
 d dynamics\, and elastic theory helped us design a bio-inspired robot tuna
 . Coupled with our cyber-physical water tunnel rig\, we explored the role 
 of stiffness in real free-swimming conditions. Comparing results from expe
 riments and modeling\, we found that the ‘best’ stiffness should scale
  with swimming speed squared to maintain maximum swimming performance. The
  proposed tunable stiffness strategy was proven effective on the robotic f
 ish with significant efficiency enhancement in real swimming missions\, wh
 ich overcame the long-existing performance bottleneck of soft-structured b
 io-inspired fish robots and provided deeper insights into fish swimming.\n
 \nBio Qiang Zhong is currently a Postdoctoral Researcher at the Departmen
 t of Mechanical and Aerospace Engineering\, University of Virginia\, USA. 
 He received his Ph.D. in Mechanical Engineering from the University of Vir
 ginia in 2021\, his master's degree in Mechanical Engineering from the Uni
 versity of Pittsburgh in 2016\, and his bachelor’s degree in Biosystem E
 ngineering from Zhejiang University in 2014. His research interests includ
 e developing physically intelligent robots with a combination of fluid mec
 hanics\, robot design\, and control for ocean explorations. He has publish
 ed a series of high-quality journals\, including Science Robotics\, Journa
 l of Fluid Mechanics\, etc. He is the co-founder of the Intelligent and Bi
 o-inspired Mechanics Seminar (IBiM) series.\n 
LOCATION:MED 0 1418 https://plan.epfl.ch/?room==MED%200%201418 https://epf
 l.zoom.us/j/67873367071?pwd=b0NEeWY2MFJqNGUzUitJV256YSt6QT09
STATUS:CONFIRMED
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