LES

Autonomic Closure for Turbulent Flows Using Approximate Bayesian Computation

Autonomic closure is a new technique for achieving physically accurate adaptive closure of coarse-grained turbulent flow governing equations, such as those solved in large eddy simulations (LES). Although autonomic closure has been shown in recent a priori tests to more accurately represent unclosed terms than do dynamic versions of traditional LES models, the optimization step used in the approach introduces large matrices that must be inverted, resulting in high memory usage.

Using ABC for turbulence model calibration

Turbulence model development using Approximate Bayesian Computation.