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

Abstract

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.

arXiv commentPublished in Journal of Fluid Mechanics, Volume 895 (Received 19 October 2019; revised 4 April 2020; accepted 8 April 2020)

References in corpus (22)

• Dynamic first-order phase transition in kinetically constrained models of glasses
• Direct evaluation of large-deviation functions
• Elaborating Transition Interface Sampling Methods
• Computation of extreme heat waves in climate models using a large deviation algorithm
• Simulating rare events in dynamical processes
• Introduction to the Diffusion Monte Carlo Method
• Probing rare physical trajectories with Lyapunov weighted dynamics
• Rogue Waves and Large Deviations in Deep Sea
• A review of Monte Carlo simulations of polymers with PERM
• Go with the Winners: a General Monte Carlo Strategy
• A rare event algorithm links transitions in turbulent flows with activated nucleations
• Finite-Size Scaling of a First-Order Dynamical Phase Transition: Adaptive Population Dynamics and an Effective Model
• Experimental Evidence of Hydrodynamic Instantons: The Universal Route to Rogue Waves
• Computing transition rates for the 1-D stochastic Ginzburg--Landau--Allen--Cahn equation for finite-amplitude noise with a rare event algorithm
• Computing return times or return periods with rare event algorithms
• Langevin dynamics, large deviations and instantons for the quasi-geostrophic model and two-dimensional Euler equations
• Vortex-density fluctuations, energy spectra and vortical regions in superfluid turbulence
• Are extreme dissipation events predictable in turbulent fluid flows?
• Statistical behavior of adaptive multilevel splitting algorithms in simple models
• Efficient characterisation of large deviations using population dynamics
• Monte Carlo simulations of the randomly forced Burgers equation
• Anomalous scaling in the random-force-driven Burgers equation: A Monte Carlo study

Cited by in corpus (11)

• Rare event algorithm study of extreme warm summers and heat waves over Europe
• Bayesian Optimization with Output-Weighted Optimal Sampling
• Applications of large deviation theory in geophysical fluid dynamics and climate science
• Extreme events in transitional turbulence
• Multistability and rare spontaneous transitions in barotropic $\beta$-plane turbulence
• Spontaneous Symmetry Breaking for Extreme Vorticity and Strain in the 3D Navier-Stokes Equations
• Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain
• Collapse of transitional wall turbulence captured using a rare events algorithm
• Limit theorems for cloning algorithms
• Rare event sampling for moving targets: extremes of temperature and daily precipitation in a general circulation model
• Rare-event detection in a backward-facing-step flow using live optical-flow velocimetry: observation of an upstream jet burst