  This study investigates, by means of numerical simulations, extreme
mechanical force exerted by a turbulent flow impinging on a bluff body, and
examines the relevance of two distinct rare-event algorithms to efficiently
sample these events. The drag experienced by a square obstacle placed in a
turbulent channel flow (in two dimensions) is taken as a representative case
study. Direct sampling shows that extreme fluctuations are closely related to
the presence of a strong vortex blocked in the near wake of the obstacle. This
vortex is responsible for a significant pressure drop between the forebody and
the base of the obstacle, thus yielding a very high value of the drag. Two
algorithms are then considered to speed up the sampling of such flow scenarii,
namely the AMS and the GKTL algorithms. The general idea behind these
algorithms is to replace a long simulation by a set of much shorter ones,
running in parallel, with dynamics that are replicated or pruned, according to
some specific rules designed to sample large-amplitude events more frequently.
These algorithms have been shown to be relevant for a wide range of problems in
statistical physics, computer science, biochemistry. The present study is the
first application to a fluid-structure interaction problem. Practical evidence
is given that the fast sweeping time of turbulent fluid structures past the
obstacle has a strong influence on the efficiency of the rare-event algorithm.
While the AMS algorithm does not yield significant run-time savings as compared
to direct sampling, the GKTL algorithm appears to be effective to sample very
efficiently extreme fluctuations of the time-averaged drag and estimate related
statistics such as return times.

Computational Physics;Fluid Dynamics