Section: New Results

Highlights of the Year

Stochastic fluid flow dynamics under uncertainty

We have proposed the basis of a formalism allowing to built large scale stochastic representation of fluid flows dynamics [17] . This formalism relies on a location uncertainty principle which separates the flow in terms of a resolved large scale component and a highly oscillating random component. The dynamics is built in a similar way as in the deterministic case through a stochastic representation of the Reynolds transport theorem. This principle paves a new way for the construction of subgrid models from the uncertainties we have on the flow. The associated subgrid tensor provides a clear interaction between small scale data and large scale resolved quantities. This characteristic opens new directions for the devising of methods for the nulmerical simulation of large scale components of the flow. It allows also deriving large-scale models that takes into account explicitly the inherent errors to a particular geophysical dynamics representation.