Collaborative Research: Targeting Turbulence Using Smart Particles

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Approximately 29 percent of all energy consumed in the U.S. is used to transport goods and people. Most of this energy is used to overcome drag forces produced by the turbulent flow of gases and liquids; only a modest reduction in drag would result in large fuel savings. Drag is associated with turbulent flow creating regions of concentrated vorticity near walls. Previous methods for reducing the drag forces, such as introducing substances (such as polymers) into the flow, did not exploit the known structure of the turbulence in a targeted way. When polymers are injected or bled into the near-wall turbulent boundary layer, they become distributed randomly, making it impractical in most cases to use these additives to reduce drag. This work seeks to answer: Can micro-particles containing a suitable additive and having specific physical properties be introduced into turbulent flow to achieve much greater drag reduction than traditional methods? The success of the present approach in reducing drag is expected to motivate the emergence of technologies focused on the development of micro-particles that can detect the nature of their own flow environment and respond by modifying that environment. For example, particles which segregate themselves into turbulent structures based on their density and subsequently dissolve will be examined first, but future smart particles might sense local flow properties, such as flow stain rates, and subsequently direct themselves to regions of the flow where their effects may be most impactful. It is easy to imagine how reducing drag on ships, cars, trains, and airplanes would have a broad impact on society.The proposed work aims to specifically target these structures by allowing particles, smaller than the smallest turbulent length scale and of the appropriate shape or density, to carry and release drag reducing agents as they collect in a natural way within or around such structures. Ideally, as one such structure is disrupted, remaining particles will migrate to the next in a disruptive cascade. Particle properties (especially particle sizes, densities, polymer properties, polymer release mechanisms, particle injection locations, and injection rates) and smart injection techniques that are most effective in reducing drag will be determined. It is proposed to study this concept using direct numerical simulation of the Navier-Stokes equations (which describe fluid motion) for the transitional case of turbulent spot evolution and for the fully turbulent flat plate boundary layer and channel flow cases. These situations cover the canonical transitional and turbulence internal and external flow regimes relevant to flow about ships as well as within pipelines.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.