Interaction of an organism with its environment is largely mediated by fluids. Molecules travel through fluids both within and outside of an organism to elicit biological response. Organisms move through fluids to seek food, to find their mate or to escape danger. Microscopic propagules are carried by fluids to explore novel environments. Fluids transmit sound and interact with light. The physics of fluids thus shapes the evolution of living organisms.
A major part of our research activity is dedicated to model and simulate the fluid dynamics of living systems. We currently focus on:
(1) the hydrodynamics of swimming
(2) the statistical properties of turbulent odor plumes emitted by a concentrated source
(3) *the statistical properties of atmospheric transport•
Swimming organisms leave inevitable footprints like smell and currents in the surrounding fluids: these signals are then broadcast in space and time by the fluid itself. Like a footprint on land, these signals are sensed by fish to locate the swimmer, predict their position and even their shape. But sensors also distort the flow and the signals they are trying to measure: how does a fish parse the wake of a swimming prey from its own perturbation of the flow? How far does the footprint extend behind a moving target? and how long before it becomes indistinguishable from the surrounding turbulence? We start from classical multipolar expansions and use high resolution direct numerical simulations to bridge the gap to fully turbulent conditions.
When an odorant is emitted by a localized source in a turbulent flow, the dynamics first produces a continuous filament of odor that meanders and fluctuates until it finally breaks into discrete pockets of odor enriched fluid (whiffs), separated by long stretches of fresh fluid (blanks). This dramatic intermittency, i.e. the alternation between whiffs and blanks, is the major challenge of turbulent navigation. To quantitatively model odor intermittent statistics, we combine accurate direct numerical simulations of odor transport with asymptotic models that leverage the Lagrangian approach for turbulent transport.
The problem of particle transport in the lower atmosphere plays a pivotal role for a variety of disciplines including biology, meteorology, urban planning and climate modeling. Microscopic particles are easily transported by the wind and carried even long distances before they sediment mainly due to gravitational settling and rainfall. Extremely large Reynolds numbers characterize atmospheric transport, where the non-linearity of the Navier-Stokes equations dominates the dynamics and no analytic solutions are available. We combine simplified stochastic models with numerical simulations of atmospheric transport with real weather data.
Andrea Mazzino - UNIGE