The majority of grid points in the fluid domain generally belong to background Cartesian grids which do not move during a simulation.
The main interest of this fictitious domain method is to use simple structured meshes, possibly uniform Cartesian nested grids, which do not generally fit the interface but define an approximate one.
Using this methodology, we introduce a semi-static adaptive grid method, which does not involve an iterative procedure for grid redistribution, as in the IGR method.
Nevertheless, a grid resolution, which does not compromise the accuracy, reliability and robustness of the optimisation in an upscaled model must be carefully determined.
Numerical examples are given to demonstrate that this procedure overcomes the Runge phenomenon when interpolation at equidistant nodes on [−1,1] is constructed, and also provides a respectable approximation for bivariate grid data, which does not become dense on the whole domain.
The method employs a novel, fully-curvilinear staggered grid discretization approach, which does not require either the explicit evaluation of the Christoffel symbols or the discretization of all three momentum equations at cell interfaces as done in previous formulations.
(mathcal {G}) consists of sub-GCM-grid-scale variability, which does not get resolved in GCM simulations, but gets resolved in DS simulations.
The detector stands out due to its simple concept, which does not include a Frisch grid.
The tool also offers a nonaffine transformation in the form of a first- and second-degree transformation which does not preserve the original voxel coordinate grid.
In normal circumstances, Germany would be a terrible place to install solar panels: it is not very sunny and has a good distribution grid, which solar does not require.
