Dynamic subgrid-scale model constant-value estimation refined by vector-level identity in an atmospheric flow field

Dynamic subgrid-scale model constant-value estimation refined by vector-level identity in an atmospheric flow field

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This study investigates the accuracy of dynamic models in predicting model constants within inviscid flow fields, such as those used in puffy spa headband wind farm flow analysis, from the perspectives of identity and turbulent energy conservation accuracy.Specifically, results are compared between tensor-level and vector-level identities, the latter of which includes the calculation of model constants taking into account the errors of differential approximation.The subgrid-scale models employed include the Smagorinsky model and the coherent structure model.The analysis focuses on inviscid flow fields within a three-dimensional periodic domain.Fourth- or second-order spatial accuracy was applied to a coarse computational grid.

The results yielded values of a model constant that compensated the resulting energy conservation errors to zero.The statistics of the velocity fluctuation derivatives in the flow fields where the energy conservation errors were compensated were examined.Dynamic model predictions for both identities were then computed for the Smagorinsky and coherent ctructure models and compared with the correct values.The results show that the dynamic model predictions are largely independent of the energy conservation errors, and that the predictions based on the tensor-level identity deviate significantly more from bostik mvp the correct values than those based on the vector-level identity.