Stochastic Modeling of Flows behind a Square Cylinder with uncertain Reynolds numbers
In this thesis, we explore the use of stochastic Navier-Stokes equations through the
Dynamically Orthogonal (DO) methodology developed at MIT in the Multidisciplinary
Simulation, Estimation, and Assimilation Systems Group. Specifically, we examine the
effects of the Reynolds number on stochastic fluid flows behind a square cylinder and
evaluate computational schemes to do so. We review existing literature, examine our
simulation results and validate the numerical solution. The thesis uses a novel open
boundary condition formulation for DO stochastic Navier-Stokes equations, which allows
the modeling of a wide range of random inlet boundary conditions with a single DO
simulation of low stochastic dimensions, reducing computational costs by orders of
magnitude. We first test the numerical convergence and validating the numerics. We then
study the sensitivity of the results to several parameters, focusing for the dynamics on the
sensitivity to the Reynolds number. For the method, we focus on the sensitivity to the:
resolution of in the stochastic subspace, resolution in the physical space and number of
open boundary conditions DO modes. Finally, we evaluate and study how key dynamical
characteristics of the flow such as the recirculation length and the vortex shedding period
vary with the Reynolds number.