Problems in generating the von Mises stresses from single stress components

Hi all,

based on the previous post (Stresses from ANSYS .rst are displayed as NaN - #2 by Kenneth_Moreland) I have noticed the following problem.

With pymapdl_reader only the individual components of the stress tensor are extracted. And that in the nodes. ParaView links these stress components under Magnitude, but the program apparently uses the L2 norm:
What I actually need for my analysis is the von Mises stress instead L2 norm:
I have tried to generate this equivalent stress with a calculator:

("Nodal stresses 0_XX"^2 + "Nodal stresses 0_YY"^2 + "Nodal stresses 0_ZZ"^2 -
"Nodal stresses 0_XX"*"Nodal stresses 0_YY" - "Nodal stresses 0_XX"*"Nodal stresses 0_ZZ" - "Nodal stresses 0_YY"*"Nodal stresses 0_ZZ" +
3 * ("Nodal stresses 0_XY"^2+"Nodal stresses 0_YZ"^2+"Nodal stresses 0_XZ"^2))^0.5

However, I get a completely incorrect distribution of stress in the body:

It should be mentioned at this point that the numerical values in the scale are correct. So the calculator has probably calculated the stresses correctly, but it is likely to be the visualization that is failing.

I am using ParaView 5.12.0-RC2. A .vtu file with the stresses and nodes can be found in this post:

I need please help with the visualization of the stresses with a Calculator.

Many thanks in advance

The problem is the same as your last post. Your cells are still quadratic hexahedra, and it still has invalid values for all but the 8 values used for linear interpolation. When you applied the Calculator, you created a new object, and the Nonlinear Subdivision Level parameter got reset to 1. Set it back to 0, and you will probably get what you expected.

The reason why the output looks different than before (that is, not all NaNs) is that the default behavior of the Calculator is to replace invalid values (i.e. NaNs) with a specific value (defaulted to 0). So you get interpolations with 0 instead of NaN. If you turn on advanced properties and unselect Replace Invalid Results, you will find you will get the NaNs in the output. (You will also get some warnings from the Calculator filter because it will assume that the NaNs came from a problem with its expression rather than NaNs in the input.

*facepalm *
Thank you very much, I had no idea that I should set the value to 0 even with a calculator.

Best regards,