I don't believe it exists "the best" method to detect vortex...

I can suggest using the lambda-2 criterion but, while it is theroretical nice, its application in confined flows using the value lambda2=0 leads to a confused pattern of vortices and I often found that a small negative value is better.

As post-processing, Tecplot has its option based on the lambda2 criterion

You could use "vorticity" function using different iso-values to mark the vortex boundary.  Larger iso-value of vorticity would mark the vortex of higher strength.

There are other criteria which can be utilized to mark the vortex boundary/structure such as - Q, discriminant and lambda-2 method.

All of these parameters can either be used as a custom field function or user defined function to store in user defined memory. Not sure whether these parameters are available as it is in CFD post.

In all, these criteria indicate relative dominance of rotational component (asymmetric part of the velocity gradient tensor) over shear component (symmetric part of the velocity gradient tensor) in a flow field.

All of these criteria usually perform well and detect vortex as a rotating flow structure with a negative pressure core. So, again different iso-values can be used to distinguish the higher strength vortex from the lower one.

I am not sure if you mean "bigger" by strength or length scale. If it is length scale that you interested in, discrete wavelet transformation is a method to extract different length scales of rotating flow structures from velocity field data.

Hope it helps,

SM

Swirl Number is best parameter can also be used, by making custom field function as per your requirement or swirl no available in Fluent also but need to check correctness of fluent swirl number.

If your vortices are in strong shear layers (in a boundary layer in your case?), the residual vorticity (Kolář, "Vortex identification: New requirements and limitations", 2011) could be useful as it is capable of separating the vorticity caused by the shear layer and the vorticity bounded to your vortices.

Regarding the filtering of "smaller" vortices,  in addition to the answer of Subhasish Mitra, some kind of data-driven modal decomposition (like POD) filtering could allow you to keep only the most energetic structures of your flow before applying your criterion.

look at :

1- (http://arxiv.org/pdf/1404.3109.pdf)

2- (https://en.wikipedia.org/wiki/Curl_(mathematics))

I don't believe it exists "the best" method to detect vortex...

I can suggest using the lambda-2 criterion but, while it is theroretical nice, its application in confined flows using the value lambda2=0 leads to a confused pattern of vortices and I often found that a small negative value is better.

As post-processing, Tecplot has its option based on the lambda2 criterion

Dear colleague good day and thank you for your replies ,

According to what I understood it is better to use Q criterion or lambda-2 directly by CFD-post or by custum field function in Fluent  ,,, 

Yadav  please can you give me more details about calculating Swirl Number in Fluent ?

Subhasish Mitra and Gaby Launay for smaller vortices you suggested respectivly to use DWT and POD ,,, is there any posibility to use one of these methods in Fluent or CFD-post ?

Best regards 

B D 

Once the velocity data are available from CFD model, you can use MATLAB to write a script for POD and DWT analysis.

Swirl Number

In swirling pipe flow, it is important to have knowledge concerning the swirl decay rate along the length of pipe so that, the degree of swirl for a swirling flow can be defined by the swirl number Sw [14], which is defined as a ratio of the axial flux of angular momentum to the axial flux of axial momentum as given as

Please, see this publication for somewhat faster than usual PIV-based methods to detect vortices.

https://arxiv.org/abs/1612.05826