Large eddy simulations of wall jets with coflow for the study of turbulent Prandtl number variations and data-driven modeling

2020 ◽  
Vol 5 (6) ◽  
Author(s):  
Ali Haghiri ◽  
Richard D. Sandberg
Keyword(s):  
Prandtl Number ◽  
Large Eddy Simulations ◽  
Data Driven ◽  
Turbulent Prandtl Number ◽  
Wall Jets ◽  
Large Eddy ◽  
Data Driven Modeling

Data-Driven Modeling of Large-Eddy Simulations for Fuel Injector Design

2021 ◽  
Author(s):  
Petro Junior Milan ◽  
Sudeepta Mondal ◽  
Roberto Torelli ◽  
Bethany Lusch ◽  
Romit Maulik ◽  
...  
Keyword(s):  
Large Eddy Simulations ◽  
Data Driven ◽  
Fuel Injector ◽  
Large Eddy ◽  
Data Driven Modeling ◽  
Injector Design

Large eddy simulations of turbulent circular wall jets

2015 ◽  
Vol 80 ◽  
pp. 72-84 ◽  
Author(s):  
Shuai Zhang ◽  
Adrian Wing-Keung Law ◽  
Bing Zhao
Keyword(s):  
Large Eddy Simulations ◽  
Wall Jets ◽  
Large Eddy

Subgrid-Scale Diffusivity: Wall Behavior and Dynamic Methods

2004 ◽  
Vol 73 (3) ◽  
pp. 360-367 ◽  
Author(s):  
Guillaume Brillant ◽  
Sabine Husson ◽  
Françoise Bataille
Keyword(s):  
Prandtl Number ◽  
Boundary Conditions ◽  
Turbulent Channel Flow ◽  
Constant Heat Flux ◽  
Large Eddy Simulations ◽  
Subgrid Scale ◽  
Adiabatic Wall ◽  
Thermal Boundary Conditions ◽  
Dynamic Methods ◽  
Large Eddy

This study concerns the near-wall behavior of the subgrid-scale diffusivity. This is shown to depend on the thermal boundary conditions. Therefore, the constant subgrid-scale Prandtl number hypothesis is questionable and a direct modeling of the subgrid-scale diffusivity is considered instead. Large-eddy simulations are carried out using the Trio U code in a turbulent channel flow configuration with the three classical thermal boundary conditions (constant temperature, constant heat flux, and adiabatic wall). Different dynamic methods are used to model the subgrid-scale diffusivity and results are compared with constant subgrid-scale Prandtl number large-eddy simulations and with direct numerical simulations.

scholarly journals Data-driven deconvolution for large eddy simulations of Kraichnan turbulence

2018 ◽  
Vol 30 (12) ◽  
pp. 125109 ◽  
Author(s):  
R. Maulik ◽  
O. San ◽  
A. Rasheed ◽  
P. Vedula
Keyword(s):  
Large Eddy Simulations ◽  
Data Driven ◽  
Large Eddy
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