I would like to apply superposition effect on two .vtk files,in order to visualize the resultant Von Mises stresses. The two files differs only on the presence of two additional components. If needed I can share the two files.
I use paraview for Windows. I opened the two .vtk files, then I visualize Von Mises stress. After that I should use a programmable filter, suggested on a previous topic, but it doesnât work.
This is a shot in the dark (because I think we are all still confused about what âmerge the stress tensor componentsâ means), but if you need to combine data from two .vtk files, perhaps the Append Attributes filter will do what you want. See this for more discussion: Difference between 2 Datasets
these are the two .vtk files, as you can see they differ from the bearings. I want to ââsumââ the von mises stresses for every single point(the components of the stress tensor, von mises stress is a scalar value) of the two different analysis, and visualize the result.
Can you elaborate on what happened and what went wrong? Were the results not as expected? What were the results? Did ParaView crash? Was there a rip in the space-time continuum? Did ParaView try to sell you an extended car warranty?
The description so far still sounds like combining the data with resampling. If we donât know what goes wrong and donât have the data there is not much we can do.
What I expected was to visualize at the same time the red internal ring (high stress value) of the first pic and the white portion around the upper hole (considerable stress value) of the second one (the pics are shown in the previous reply).
So, if it ran correctly, I would see ONE assembly with both remarkable values (I took them as an example, the stresses on every point should be the sum). It isnât what I get.
As you can see, after resampling with dataset, I have the body of the second pic (the destination mesh), with the values of the first one (source data arrays), but NOT the stresses shown in the second pic.
It would be a lot easier to help you if you could share your data.
I can think of a couple of ways you might be able to achieve this. One would be to combine the fields with Resample with Dataset as described before and then use the Calculator filter to find the maximum between the two von mises fields.
Yes, combining the fields of the two datasets into one and then taking the max seems to do the trick. (There were a few steps to first rename, then resample, and then append the fields.
As I can see from the pic,it is exactly what I wanted, thank you. I have a few question after opening the file, beacuse itâs the first time I face Paraview:
1- How are applied the different ââAppend attributesââ? I would like to know the steps, especially for the last one, and the difference with the other with an arrow;
2-As I can see, the calculator finds the max value for every point. But can be eventually summed A von mises and B von mises?
Add PassArrays to both A and B inputs and remove all the arrays except for von Mises Stress. This is optional, but made things a little easier later.
Add RenameArrays to both A and B pipelines to rename the fields to A von Mises Stress and B von Mises Stress, respectively. This makes it possible to differentiate the two arrays as we start combining the fields into one mesh.
Add the Resample With Dataset filter. Set the Source Data Arrays input to the A pipeline and the Destination Mesh to the B pipeline. I chose the B pipeline for the destination mesh because there are small parts of the A mesh outside of the B mesh, so the resample worked better to apply to the B mesh.
The result of Resample With Dataset now has A von Mises Stress on the B mesh. To get the B fields back, select both the ResampleWithDataset and the RenameArrays for the B pipeline in the pipeline browser and add the Append Attributes filter. This will combine both fields into a single mesh, which is the whole point of this exercise.
Add the Calculator filter to AppendAttributes. To get the max stress, set the expression to max("A von Mises Stress", "B von Mises Stress"). To get the sum, set the expression to "A von Mises Stress" + "B von Mises Stress".
Hello, again. I am trying to sum every stress component. So, I started with the ââxx stressââ. I did the same steps you suggested, but it ends with an error:
You have the Resample With Dataset filter attached to the wrong inputs. It should be attached to the Rename Arrays filters, but instead it is directly attached to the readers. Because of this, it is not getting the A_xx named array.