Complex simulator-based models usually have intractable likelihood functions, rendering
the likelihood-based inference methods inapplicable. Approximate Bayesian Computation …

Approximate Bayesian computation (ABC) is a data-driven technique that uses many low-
cost numerical simulations to estimate unknown physical or model parameters (eg …

Approximate Bayesian computation (ABC) is a likelihood-free inference method that has
been employed in various applications. However, ABC can be sensitive to outliers if a data …

Approximate Bayesian computation is a popular methodology for simulation-based
parameter inference in scenarios where the likelihood function is either analytically …

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 …

Approximate Bayesian computation (ABC) is used in this study to estimate unknown model
parameter values, as well as uncertainties, in a nonequilibrium anisotropy closure for …

Turbulent flows are present in a wide variety of real-world engineering problems, often by
design due to their favorable mixing characteristics. At the same time, however, these flows …

A major challenge in computational fluid dynamics (CFD) simulations of real-world flows is
the accurate assignment of boundary, initial, and geometric conditions, as well as fluid and …