Optimal control of microswimmers in turbulent flows

Finding efficient navigation strategies in turbulent flows is necessary for the development of artificial microswimmers, with many paramount applications including drug delivery and hazard cleanup.

It also allows better understanding of plankton, which is essential for predicting and preventing catastrophes in the aquatic life or the global climate.Microswimmers have limited information and maneuverability in a chaotically fluctuating environment.

To find the best navigation strategy is therefore an astonishingly difficult task, because they must use indirect measurements to exploit intricate non-linear and time-delayed relations between the flow and their swimming dynamics.

The aim of this proposal is to solve this task in a stochastic model, using an analytical method that I have developed and successfully used to understand mechanisms of small passive microswimmers and particles in turbulence.

The solution will identify mechanisms and the most important signals for efficient navigation strategies, and how these depend on the parameters of the swimmer.I will work on this four-year project together with a PhD student funded by this application.

My international and national collaborators can help me compare the findings in my model to more realistic models using direct numerical simulations of turbulence and to experiments of plankton.