subgridmodelling

Subgrid modelling is a technique used in computational fluid dynamics (CFD) and other fields of computational science to account for the effects of small-scale phenomena that cannot be directly resolved by the computational grid. This is particularly relevant in simulations involving turbulent flows, multiphase flows, and other complex systems where the smallest relevant scales are much smaller than the largest scales of interest.

In subgrid modelling, the large-scale flow is resolved on a coarse grid, while the effects of the unresolved small-scale phenomena are modelled using mathematical or empirical relationships. This approach allows for more efficient simulations, as it reduces the computational cost associated with resolving all scales of motion. However, it also introduces uncertainties and approximations, which must be carefully managed to ensure the accuracy and reliability of the results.

Common subgrid models include the Smagorinsky model, the dynamic Smagorinsky model, and the large eddy simulation (LES) model. These models vary in their complexity and the level of detail they provide for the unresolved scales. The choice of subgrid model depends on the specific application, the computational resources available, and the desired accuracy of the simulation.

Subgrid modelling is an active area of research, with ongoing efforts to develop more accurate and efficient models for a wide range of applications. As computational power continues to increase, the importance of subgrid modelling in enabling large-scale simulations of complex systems is expected to grow.