Neural networks based subgrid scale modeling in large eddy simulations
β Scribed by F. Sarghini; G. de Felice; S. Santini
- Book ID
- 108391181
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 403 KB
- Volume
- 32
- Category
- Article
- ISSN
- 0045-7930
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract Large eddy simulation (LES) is based on separation of variable of interest into two partsβresolved and subgrid. The resolved part is obtained numerically using modified transport equation while the effect of the subgrid part is modelled using subgridβscale (SGS) models. In this paper we
Recently, the e-expansion and recursive renormalization group (RNG) theories as well as approximate inertial manitblds (AIM) have been exploited as means of systematically modeling subgrid scales in large-eddy simulations (LES). Although these theoretical approaches are rather complicated mathematic