Session: Rising Stars of Mechanical Engineering Celebration & Showcase

Paper Number: 149671

149671 - Unraveling Predictive and Multiscale Dynamics in Turbulence for Flow Control 

Ubiquitous in nature, turbulence is regarded as the greatest unsolved problem in classical physics and mathematics. Turbulent flow also plays a crucial role in nature and engineering across a range of important issues, from climate to aviation and cardiovascular disease. As such, a better understanding of turbulence is central to human health and the sustainability of natural resources. The most essential features of turbulence are its chaotic and multiscale natures, posing both challenges and opportunities. In particular, turbulence closely ties into research and development in energy science. For example, in aviation, turbulent drag forces can consume half or more of the energy in many important flow processes, such as flows over the airfoil, rotor blade, and fuselage, thus decreasing efficiency and increasing operational costs. Further, if drag could be reduced by 1% in passenger airplanes, it would save approximately more than $2 billion dollars per year. Therefore, flow control to reduce turbulent drag is a pivotal step towards substantial energy savings. However, turbulence control is still scientifically challenging due to its chaotic and multiscale characteristics. To address this challenge, the goal of this project is to apply recent advances in the dynamical systems viewpoint of turbulence to solve the problem of the chaotic and multiscale nature embedded in turbulence for rigorous flow control. The key idea is to uncover the predictability and multiscale interactions in turbulence using so-called exact coherent solutions (ECSs) to the governing Navier-Stokes equations. The use of these ECSs will provide a more deterministic and controlled way to unravel both predictable and multiscale characteristics in turbulence. Since finding a deterministic solution to turbulence is regarded as one of the greatest unsolved problems in classical physics and mathematics (even in engineering), gaining a new understanding of the predictability of turbulence would represent a significant intellectual advance.  Ultimately, this research will provide the fundamental knowledge necessary to advance flow control strategies to reduce energy consumption in many engineering systems. The new knowledge obtained will be exploited for cost-effective turbulence control. The discovery that predictive and multiscale dynamics exist will lead to a more rigorous control strategy that can steer turbulence toward desirable states, whereby targeted larger scales are controlled by controlling smaller ones. As energy losses in various industrial flow systems are largely associated with turbulent drag, this project has far-reaching implications in effectively improving the energy efficiency of the systems by taking full advantage of the predictive and multiscale dynamics in turbulence.

Presenting Author: Jae Sung Park University of Nebraska-Lincoln

Presenting Author Biography: Dr. Jae Sung Park is an Associate Professor in the Department of Mechanical and Materials Engineering at the University of Nebraska-Lincoln (UNL). He received his B.S. from Hanyang University and his M.S. and Ph.D. from the University of Illinois at Urbana-Champaign. All degrees are in Mechanical Engineering. Prior to coming to UNL in 2017, Dr. Park was a postdoctoral researcher in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. His research encompasses a wide range of fluid mechanics from low to high Reynolds number flows, involving complex fluids, rheology, transition-to-turbulence, and turbulence. Dr. Park has been awarded the NSF CAREER Award, UNL University-wide Teaching Award, UNL College of Engineering Excellence in Research Award, and UNL College of Engineering New Faculty Teaching Award.

Authors:

Jae Sung Park University of Nebraska-Lincoln