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-   -   error estimation for grid independence (https://www.cfd-online.com/Forums/fluent/28993-error-estimation-grid-independence.html)

 santosh October 14, 2001 05:05

error estimation for grid independence

hi,

I want to know if fluent has any capability to measure the error using the x-y plot which contains two curves say pressure distribution curves. If the answer is no,can anybody tell me if there are any tools/softwares available to do this and also if it is available on the net.

thanks and regards, santosh

 dimitris October 16, 2001 06:11

Re: error estimation for grid independence

No, to my knowledge, Fluent does not have such an error analysis option. What you can do is write (in the "Plot/XY plot" panel, check "write to file" box) the two curves, i.e. get 2 ascii files containing 2 columns each (e.g. distance vs pressure_gradient) and read them in a spreadsheet (e.g. Excel). Then you can do further post-processing in order to calculate the error between the two runs.

 santosh October 16, 2001 07:25

Re: error estimation for grid independence

one more thing,may sound silly,since the grid resolution is different for the two xy files the vector size will be different.How can I calculate the error between two different size vectors?

thanks and regards, santosh

 dimitris October 17, 2001 16:06

Re: error estimation for grid independence

If the geometry is the same in both meshes you will have two curves (in XY plot) starting and ending at the same x values but with different number and distribution of points. Now there are two solutions:

1. You calculate a fit for both of them (e.g. of a polynomial form in Excel or in another data handling program) and from their analytical form calculate the error at certain x values of your choice.

2. For certain x values of your choice interpolate (say a linearly) from the two neighbouring values in order to find the y value at that point for both results. Then find the relative error.

for example you may have these 2 data sets:

set 1 set 2 x y x y 1.1 3.4 0.98 3.6 2.1 4.5 1.3 4.1 3.1 4.4 2.5 4.6

so if you want to find the error in x=2 you interpolate between points 1 & 2 for dataset 1 and between points 2 & 3 of dataset 2. You find the two interpolated values and then find the error in x=2.

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