I'm currently working on a very challenging dataset (sandstone with "streak" spots), after find-orientation with selected hkls. We got some difficulties for fit-grains step.
The diffraction spots are as follows:
We managed to trial and error with HPC by tweaking with threshold, filter radius, misorientation, etc. (all the parameters I can think of) Here is an example of the test based on 98 percentile background sub. (I tried 50pct 75pct 98pct....)
Based on the highlighted pairs, we performed the fit-grains step. Due to the overlapping reason, we always ended up with most of the grains clustering in the central region (within 0.60.60.6) as shown below.
This should have been about 4.54.50.6 mm^3 (The actual volume size based on CT).
Hi Joel, @joelvbernier
I'm currently working on a very challenging dataset (sandstone with "streak" spots), after find-orientation with selected hkls. We got some difficulties for fit-grains step.
The diffraction spots are as follows:
We managed to trial and error with HPC by tweaking with threshold, filter radius, misorientation, etc. (all the parameters I can think of) Here is an example of the test based on 98 percentile background sub. (I tried 50pct 75pct 98pct....)
Based on the highlighted pairs, we performed the fit-grains step. Due to the overlapping reason, we always ended up with most of the grains clustering in the central region (within 0.60.60.6) as shown below.
This should have been about 4.54.50.6 mm^3 (The actual volume size based on CT).
Do you have suggestions or comments on this?
Thanks a lot, Tian