MSGID: 1:317/3 642f9c6f   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    Model simulates variable flap stiffness for the best lift    
      
     Date:   
         April 6, 2023   
     Source:   
         University of Illinois Grainger College of Engineering   
     Summary:   
         There is extensive research on how a fixed-position flap affects   
         lift in the realm of fluid-structure interaction. So, researchers   
         conducted a bio-inspired study with a novel twist -- variable   
         stiffness over time much like a bird can tense, or stiffen, the   
         musculature and tendons connected to covert feathers -- to learn   
         more about how it affects lift.   
      
         The results showed a 136 percent benefit.   
      
      
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   FULL STORY   
   ==========================================================================   
   There is extensive research on how a fixed-position flap affects   
   lift in the realm of fluid-structure interaction. However, taking the   
   conversation in a new direction, researchers at the University of Illinois   
   Urbana-Champaign conducted a bio-inspired study with a novel twist --   
   variable stiffness -- to learn more about how it affects lift.   
      
      
   ==========================================================================   
   The researchers wondered if they could model a flap on an airfoil, or   
   wing, with varying stiffnesses over time much like a bird can tense,   
   or stiffen, the musculature and tendons connected to covert feathers.   
      
   "We know from previous studies that having a flap with some stiffness   
   could help increase lift in the stall regime," said Andres Goza,   
   a professor in the Department of Aerospace Engineering at UIUC. "So,   
   that begged the question: What if you could tune the stiffness? How   
   much benefit would there be?"  The results of the study showed a big   
   benefit. "Our flap with a variable stiffness was better than having no   
   flap by 136 percent and 85 percent better than the best possible single   
   stiffness flap from an earlier study we conducted."  Goza and his student   
   Nirmal Nair modeled a variable stiffness actuator on a flap hinged to   
   an airfoil via a torsional spring to create a hybrid controller that   
   changes the stiffness over time. The flap itself cannot flop or bend   
   in any way. The stiffness refers to how tightly the torsional spring is   
   holding onto the flap.   
      
   "In the simulation, we trained a controller that determined a specific   
   value on the spectrum from very stiff to very loose. The controller was   
   built using reinforcement learning, and trained to select a stiffness   
   to improve lift on the airfoil," Goza said.   
      
   "Using the variable stiffness actuators, we obtain the changes in   
   stiffness values of the spring. The spring is a simplified model. In   
   practice, this functionality can be implemented using variable stiffness   
   actuators, though this is a non-trivial step that would require a new   
   research effort, beyond the scope of what we looked at. The results   
   of our tuneable stiffness paradigm were compared to the best possible   
   single stiffness case, obtained by building a performance map for several   
   different simulations corresponding to a single stiffness value each."   
   Goza said the lift improvements are achieved due to large-amplitude flap   
   oscillations as the stiffness varies over four orders of magnitude.   
      
   "For the first nine time units, the controller tried different stiffnesses   
   and learned what happened," Goza said. "Then we turned it loose for the   
   remainder of the simulation: at a given instance in time, it decides   
   to change the stiffness and actively adapt over time based on what the   
   flow is doing to get a boost in lift."  Goza said it is complicated to   
   develop a control strategy like this one.   
      
   "As the stiffness changes, the flap moves. Then the flap motion changes   
   the airflow around it, so there is a complex coupling going on," Goza   
   said. "Now the flap will respond differently to the change of the flow   
   field around it and as the flow field changes, the response of the flap   
   will change again.   
      
   Simulating this two-way coupling is a source of complexity.   
      
   "A strength of our work is that we model all of that. We fully account for   
   the two-way coupling between the structural motion and the response. And   
   that's key to developing an accurate controller. We need to be able to   
   say, when I change the stiffness, here's the interplay that will happen   
   and harness that to give it a better lift."  Goza said most often when   
   people think about control, it's about feedback. We receive information   
   about a system, then use that information to make a decision. There are   
   consequences, and you keep auto-correcting.   
      
   "This hybrid controller tunes the stiffness, but we call it hybrid   
   because we don't directly control the flap motion. We're just saying   
   the flap has a specific stiffness, and I am going to actuate that and   
   change the stiffness.   
      
   Everything that happens next is based on the physics of that   
   stiffness. The flap will feel what's happening in the flow and start   
   deploying of its own accord. And it's going to start inducing these other   
   dynamics."  Goza said the most natural application for this research is   
   unoccupied vehicles that have onboard computers.   
      
   "For these smaller aircraft, gusts can have a much larger impact,"   
   Goza said.   
      
   "They need to be more maneuverable, for example in natural disasters there   
   may be a need to reach a location where humans can't easily travel."  He   
   added that computation has utility "because you can allow the controller   
   to vary the stiffness across 4 orders of magnitude, and whatever   
   the resulting number is just gets used in the simulation. You're not   
   constrained by physical limitations. That lets us explore parameter spaces   
   that we wouldn't otherwise know about, and use that as a springboard to   
   motivate clever experimentalists to realize these parameter ranges.   
      
   "At this point in the research, the structural designs that undergo the   
   required stiffness changes don't exist. So, in this way computation can   
   inspire material scientists to develop new materials/structural design   
   paradigms that can do it," Goza said.   
      
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   ==========================================================================   
   Story Source: Materials provided by   
   University_of_Illinois_Grainger_College_of_Engineering.   
      
   Original written by Debra Levey Larson. Note: Content may be edited for   
   style and length.   
      
      
   ==========================================================================   
   Journal Reference:   
      1. Nirmal J. Nair, Andres Goza. Bio-inspired variable-stiffness   
      flaps for   
         hybrid flow control, tuned via reinforcement learning. Journal of   
         Fluid Mechanics, 2023; 956 DOI: 10.1017/jfm.2023.28   
   ==========================================================================   
      
   Link to news story:   
   https://www.sciencedaily.com/releases/2023/04/230406152642.htm   
      
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