High-order gas-kinetic schemes for turbulence modeling and simulation

The essence and shortcoming of turbulence modeling and simulation of atmospheric boundary/surface layers are discussed. The present approach rests on the extensively tested and widely used two-equation k-ε model to predict such flows. All features and constants of the standard version of the k-ε model as it is used for shear flows are retained here. This eliminates the requirement of rigorous experimental validation. However, the model with its set of boundary conditions features compatibility and realizability with the commonly reported stable, unstable and neutral atmospheric boundary/surface layer data. The paper presents also a comparison with experimental data and other models and the need for future research in this direction.

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Computing for Reactive Turbulence Modeling and Simulation

Mechanics Research Communications ◽

10.1016/j.mechrescom.2021.103759 ◽

2021 ◽

pp. 103759

Author(s):

Peyman Givi

Keyword(s):

Modeling And Simulation ◽

Turbulence Modeling

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A family of high-order gas-kinetic schemes and its comparison with Riemann solver based high-order methods

Journal of Computational Physics ◽

10.1016/j.jcp.2017.11.036 ◽

2018 ◽

Vol 356 ◽

pp. 150-173 ◽

Cited By ~ 16

Author(s):

Xing Ji ◽

Fengxiang Zhao ◽

Wei Shyy ◽

Kun Xu

Keyword(s):

High Order ◽

Riemann Solver ◽

High Order Methods ◽

Kinetic Schemes

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HIGH ACCURACY METHOD FOR TURBULENT FLOW PROBLEMS

Mathematical Models and Methods in Applied Sciences ◽

10.1142/s0218202512500054 ◽

2012 ◽

Vol 22 (06) ◽

pp. 1250005 ◽

Cited By ~ 6

Author(s):

M. GUNZBURGER ◽

A. LABOVSKY

Keyword(s):

Turbulent Flows ◽

Turbulence Modeling ◽

High Order ◽

Step Method ◽

Flow Problems ◽

Temporal Variables ◽

The Family ◽

Approximate Deconvolution ◽

High Reynolds ◽

Stability And Accuracy

We present a method of high-order temporal and spatial accuracy for flow problems with high Reynolds number. The method presented is stable, computationally cheap and gives an accurate approximation to the quantities sought. The direct numerical simulation of turbulent flows is computationally expensive or not even feasible. Hence, the method employs turbulence modeling. The two key ingredients are the temporal deferred correction, combined with the family of Approximate Deconvolution models, which allows for arbitrarily high order of accuracy in both spatial and temporal variables. We prove stability and accuracy for the two-step method; the method is shown to be second order accurate in time and in the filtering width.

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