Gridconvergencetutkimuksilla

Gridconvergence refers to a phenomenon observed in computational fluid dynamics and other simulation-based fields where the solution obtained from a numerical simulation converges to a stable and accurate result as the computational grid, or mesh, is refined. A finer grid means more discrete points or cells are used to represent the physical domain, allowing for a more detailed and precise representation of the underlying physical phenomena.

When a simulation is run with increasingly finer grids, the output, such as velocity, pressure, or temperature distributions, should ideally approach a consistent and unchanging solution. This consistency indicates that the numerical discretization of the governing equations is sufficiently fine to capture the essential physics of the problem without significant error introduced by the grid's resolution. The process of grid convergence is crucial for validating the accuracy of a simulation.

To demonstrate grid convergence, researchers typically perform simulations on a series of grids with progressively smaller cell sizes. They then monitor key output parameters and observe how these parameters change with grid refinement. If the parameters stabilize and show only minor variations as the grid becomes finer, it suggests that grid convergence has been achieved. This iterative process is essential for ensuring that the simulation results are reliable and not artifacts of an insufficient grid resolution. Achieving grid convergence provides confidence that the simulation is a good approximation of the real-world system being modeled.