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Open image in new window Fig. 6 1/4 of five spot pattern streamline model with grids constructed using a geometric gridding coefficient of 1.2 in the x and y directions and variable layers' sizes in the z direction.
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Fig. 14 RMSE as a function of SNR in the off-grid model with different grid interval.
In the model experiments, two different sets of meteorological input data were used: (1) surface observation data from station measurements and from weather radar, and (2) forecast data from five different high-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km.
Due to recent advances in supercomputing and GCMs, fine-resolution models with grid spacing less than 25 km have been used to investigate future change in TC activities (Murakami et al. 2012; Manganello et al. 2014; Knutson et al. 2015; Roberts et al. 2015; Wehner et al. 2015).
The performance of the model with different grid nesting configurations, turbulence closures, and grid resolutions is investigated through comparisons with observation data.
To see whether the size of the grid would influence the model outputs, we carried out a sensitivity analysis by running the final model with a grid size of 40 km.
Heat exchange areas for the possible heat exchangers are found by solving a nonlinear optimization model with a grid search algorithm.
To address this issue, a transient computational fluid dynamics (CFD) model with moving grid technique has been presented in this work.
Non-Hydrostatic Model with a grid interval of 350 m.
Figure 16 Flows' throughput in the IEEE model with a grid topology.
Figure 15 Flows' throughput in our model with a grid topology.
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