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

Numerical study of extreme mechanical force exerted by a turbulent flow on a bluff body by direct and rare-event sampling techniques