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Turbulence models in CFD
CFD stands for computational fluid dynamics. A vast field of numerical analysis in the field of fluid s flow phenomena is represented by this topic. Primarily CFD deals with understanding and solving ordinary and partial differential equations and much more than that. turbulence when present in a flow dominates all other flow phenomena.The modeling of turbulence thus greatly improves the quality of numerical simulations.
The main steps in solving a CFD problem is
- geometry and grid generation
-setting-up a physical model
-solving it
-post-processing the computed data

Complexity of the turbulence model
The Complexity in most of the turbulence models is due to the nature of Navier-Stokes equation which is inherently nonlinear, time-dependent, three-dimensional PDE. turbulence is also a random process in time. vortex structures move along the flow with very much varying lifetimes.

Classification of turbulent models:
The models based on Reynolds-Averaged Navier-Stokes(RANS) are:
-Eddy-viscosity models (EVM):
Here it is assumed that turbulent stress is proportional to the mean rate of strain

-Differential stress models (DSM):
Reynolds-stress transport models (RSTM) or second-order closure models (SOC) are part of this.

- Non-linear eddy-viscosity models (NLEVM):
In these kind of models, Turbulent stress is modelled as a non-linear function of mean velocity gradients

The ones based on the Computation of fluctuating quantities are:

-Large-eddy simulation (LES):
The time-varying flow is computed but the sub-grid-scale motions is modeled.

-Direct numerical simulation (DNS):
No modelling what so ever is applied here.

For full details, refer this pdf:
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INTRODUCTION
The abbreviation CFD stands for computational fluid dynamics. It represents a vast area of numerical analysis in the field of fluid s flow phenomena. Headway in the field of CFD simulations is strongly dependent on the development of computer-related technologies and on the advancement of our understanding and solving ordinary and partial differential equations (ODE and PDE). However CFD is much more than just computer and numerical science. Since direct numerical solving of complex flows in real-like conditions requires an overwhelming amount of computational power success in solving such problems is very much dependent on the physical models applied. These can only be derived by having a comprehensive understanding of physical phenomena that are dominant in certain conditions. [1], [8] Why turbulence? Whenever turbulence is present in a certain flow it appears to be the dominant over all other flow phenomena. That is why successful modeling of turbulence greatly increases the quality of numerical simulations. All analytical and semi-analytical solutions to simple flow cases were already known by the end of 1940s. On the other hand there are still many open questions on modeling turbulence and properties of turbulence it-self. No universal turbulence model exists yet. Further more the price tag for our ignorance is immense. That makes the area of CFD modeling also extremely economically attractive.


Presented By;
Jurij SODJA
Mentor: prof. Rudolf PODGORNIK

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http://ww-f1.ijs.si/ rudi/sola/Turbulence-models-in-CFD.pdf