[fluka-discuss]: RE: Cartesian vs Cylindrical grid

From: Joachim Vollaire <joachim.vollaire_at_cern.ch>
Date: Thu, 26 May 2016 07:49:25 +0000

Dear Roman
The difference can be explained by geometrical considerations. In one case, you have bins with lateral extensions a disk of radius 3.7 cm (cylindrical binning) while on the other case you have a square with lateral extensions of 20 cm (Cartesian).

With the cylindrical binning, you only include the inner part of the target so most likely the peak deposited energy while on the other case you are averaging over a larger volume. The difference is lower in the back of the target most likely due to the lateral extension of the particle shower and a more homogeneous deposited energy distribution (which you could visually check with a 2D binning).

Concerning the comparison with OLTARIS, you should use the same binning which was used to compare with FLUKA to prevent including the geometrical effect described above

From: owner-fluka-discuss_at_mi.infn.it [mailto:owner-fluka-discuss_at_mi.infn.it] On Behalf Of Roman Savinov
Sent: 26 May 2016 07:40
To: fluka-discuss_at_fluka.org
Subject: [fluka-discuss]: Cartesian vs Cylindrical grid

Dear FLUKA experts,

I noticed that USRBIN (dose) gives slightly different result depending on the grid chosen: Cartesian or Cylindrical.
the target is a cylinder (r=10, l=30 cm) inside a vacuum void.
I do understand that when I choose Cartesian grid, some of the void region in the corners gets included and affects the result but it doesn't explain why deviation is large near the front and decreases with a depth of the target:
and more importantly, why it is cartesian grid that yields better fit with OLTARIS result?

I am trying to compare FLUKA output with result from this paper:
specifically fig.9 (bottom right)

here are my scoring cards:
USRBIN 0.0 3.7 1. 1. 300. &
USRBIN 10. DOSE -32. 10. 10. 35.CARTESIAN
USRBIN -10. -10. 3.7 1. 1. 300. &

3.7 is a thickness of aluminum shield.

thank you,


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Received on Thu May 26 2016 - 11:20:07 CEST

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