RII Track-4: Finding Order in Chaos: a Systematic Approach to Turbulence Control for Drag Reduction

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Nontechnical DescriptionTurbulent flows play a crucial role in nature and engineering across a range of important areas, from climate to aviation to cardiovascular disease. In particular, turbulence is one of the most important phenomena in engineering because turbulent flows are significantly responsible for flow resistance in various designed systems such as in the automotive and aerospace industries. However, despite the critical implications of turbulent flows and decades of research focused on controlling these flows for energy savings, turbulence control is still scientifically challenging due to the chaotic nature of turbulence. This project will probe the chaotic nature of turbulence, on the premise that prevailing theories based on statistical randomness are conceptual barriers to future breakthroughs. To this end, the PI's mathematical and computational methods will be integrated with experimental techniques using state-of-art facilities at the University of Minnesota. This systematic collaborative approach will be employed to transform understanding of turbulent flows, opening up the possibility of substantial energy savings. This project will establish a long-term collaboration between the PI's home institution of the University of Nebraska-Lincoln and the University of Minnesota to advance the fundamental understanding of turbulent flows.Technical DescriptionUbiquitous in nature, turbulence is regarded as the greatest unsolved problem in classical physics and mathematics. In addition, turbulence is one of the most important phenomena in engineering because turbulent flows are significantly responsible for drag, which is directly related to energy consumption. However, controlling turbulence has thus far been an insurmountable challenge due to the random characteristic nature of turbulent flows. The goal of this research is to advance a first-principles systematic framework for discovering and predicting highly organized turbulent dynamics, with a longer-term goal of exploiting this framework for improved turbulence control and increased energy efficiency in many flow processes. The objective is to build on recent advances in the dynamical understanding of turbulent flows to find and exploit a predictive model for rigorous flow control. The research takes a systematic approach to transform our understanding of turbulence. The PI will use a computational and mathematical framework to characterize organized turbulent dynamics between the ordered flow structures, working in collaboration with a team at the University of Minnesota whose facilities provide an excellent research environment for experimental validations of the ordered flow structures and the predictive model. The PI will utilize, refine, and further develop a systematic approach to discover a predictive model of turbulent flows, identifying evidence of organized turbulent dynamics. Ultimately, the PI will utilize knowledge gained during the fellowship to improve and develop facilities at the University of Nebraska-Lincoln to sustain a long-term research effort.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.