Dear experts,
I have installed the latest versions of FLUKA 4.5 and FLAIR 3.4 and intend to use the AUTOIMBS card to calculate the dose distribution for thick shielding, thereby avoiding the layering of the thick shield. However, I found that this card seems to have no effect on the results and does not reduce the variance.
Below is my input card, could you please help me identify any issues? Thank you very much!
autoimbs.inp (5.8 KB)
Dear @lichen
When using AUTOIMBS, particles are biased so that they can reach the ROI. Once a particle is inside the ROI, no further biasing is applied to it, unless it exits the ROI and then is again subject to biasing. In your case, you have defined the shielding as ROI. Therefore, when the particle is inside the shielding, no biasing is applied to it, which I guess is not what you wanted.
To correct the situation, you should select rvacume as your ROI. And provide as spatial limits an RPP somewhat larger than your shielding, so that its inner volume overlaps meaningfully with your ROI and the AUTOIMBS algorithm knows towards where to promote particles.
Hope this helps,
Fran
Dear @fogallar
Thank you for your thorough response. I’m not sure if I understood your point correctly. I added an RPP slightly larger than the shielding body and modified the AUTOIMBS card, but I encountered an error during the run.
autoimbs.inp (5.9 KB)
I modified the ROI, and it works. Thank you! @fogallar Wishing you all the best!
Happy to hear that, @lichen
I’ll briefly explain what’s happening because it might be useful for other users.
When AUTOIMBS is used, the volume inside the Spatial limits RPP is voxelized.
Then, the algorithm detects which of those voxels (specifically, their centers) lie inside the ROIs.
Next, it constructs the necessary biasing map using this information to promote particles towards the voxels inside the ROI.
Therefore, for the ROI to be seen by the algorithm, it must sufficiently overlap with the Spatial limits. For example, in your case, you have a shielded room and you want to promote particles outside that room in every direction. To achieve this, there must be an overlap between the Spatial limits and the ROI such as there is a layer at least one voxel thick all around your room (i.e., inside your ROI). This way, the algorithm can effectively detect that the ROI fully surrounds your room.
This is also why users are advised to visualize the biasing map (.bnn file) created after initialization, to ensure that the gradient properly leads towards the intended ROI.
As mentioned in the manual, if you don’t specify the voxel size, a default will be calculated so that there are approximately half a million voxels inside the Spatial limits. Specific details about the number and size of the voxels are provided in the .out file.
Hope this helps.
Kind regards,
Fran