For example, if the microscope pixel size is 66 × 66 nm, then an appropriate "fine grid" bin size may be 22 × 22 nm, so that nine "fine grid" elements can then be summed to correspond to the experimental pixel size.
Pressure at cell centers and flux across grid faces can then be solved using a TPFA approach.
This fuzzy set of grid spacings can then be defuzzified in a more or less conservative way to define a sampling scheme.
Given the reference coordinates of the LLRR and ALSEP sites, the derived topographies, which are the heights referenced to their respective radii re-sampled on a 0.0625° × 0.0625° grid size, can then be externally assessed through bilinear interpolation.
For this second concept, the only layer that needs to be patterned is the silver grid electrode and the grid pattern design can then be readily tuned.
The combined information from different grid cells layers can then identify our unique location.
The grid adaptability test can then be performed.
In the offline stage, we construct a small number of reduced basis functions within each coarse grid block, which can then be used to approximate the multiscale finite element basis functions.
To establish a relation between our results and a real bat, it is necessary to specify the actual values of the temporal and spatial parameters of our model, to obtain a time scale for the development of the grids that we can then compare with experimental findings.
We can then impose various grid disturbances on the high-voltage side of the wind turbine transformer using the grid simulator.
