Best Point Gamma Source in MCNP simulation?

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SUMMARY

The discussion focuses on optimizing particle histories in MCNP simulations when using a point isotropic gamma source. Users suggest converting the point source to a cone-shaped source or using a parallel beam to increase the number of particle histories reaching the tally region, thereby reducing statistical error. The importance of the distance between the source and detector is highlighted, with recommendations to adjust this distance for improved results. Additionally, a Python library, CardSharpForMCNP, is introduced to simplify the generation of MCNP input decks, particularly for managing source configurations.

PREREQUISITES
  • Understanding of MCNP (Monte Carlo N-Particle Transport Code) simulations
  • Knowledge of radiation flux and its relationship with distance (1/r^2 law)
  • Familiarity with source biasing and restricting techniques in particle simulations
  • Basic proficiency in Python for utilizing the CardSharpForMCNP library
NEXT STEPS
  • Explore MCNP source configurations, specifically cone and parallel beam setups
  • Learn about the impact of distance on radiation detection and measurement accuracy
  • Investigate the use of the CardSharpForMCNP library for generating MCNP input decks
  • Study statistical error reduction techniques in Monte Carlo simulations
USEFUL FOR

Researchers, physicists, and engineers involved in radiation transport simulations, particularly those using MCNP for gamma source modeling and optimization.

Salman Khan
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TL;DR
Point gamma source in mcnp
When I simulate a point isotropic gamma source in mcnp usually number of particle histories to the tally region (let say a detector placed at 30 cm from point source) is much low (few hundreds only) as compared to actually particle histories (1.0E7), Will it be correct if convert isotropic point source to a cone source so that I can increase number of particle histories towards tally region?.
Thanks every one in advance
 
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This is 1/r^2 for radiation, and you will get a flux of around 885 per square cm per 1e7 source particles. (Think surface of a sphere).

A cone shaped beam can work, a parallel beam could also work, set a VEC and DIR=1. The Compton scattering would still be modeled well but it might be worth checking if the background from the rest of the flux affects your result. Can you change what you are modeling to be more efficient or are you replicating a real experiment that has already been done?
 
Alex A said:
This is 1/r^2 for radiation, and you will get a flux of around 885 per square cm per 1e7 source particles. (Think surface of a sphere).

A cone shaped beam can work, a parallel beam could also work, set a VEC and DIR=1. The Compton scattering would still be modeled well but it might be worth checking if the background from the rest of the flux affects your result. Can you change what you are modeling to be more efficient or are you replicating a real experiment that has already been done?
I just want to model my problem more efficiently by entering more possible particles to the tally region to reduce statistical error. As we know mcnp gives answer per particle that is why I want to enter more particle to the region of interest so that I can get more accurate result. M I right ?.if not please suggest thanks
 
Yes, you are right.

But why 30cm? Why not closer?
 
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Alex A said:
Yes, you are right.

But why 30cm? Why not closer?
Yes you are right I can decrease distance to further improve results. But what will I do if distance of source and detector is 30 cm in an experimental setup, here the only choice seem to me is to convert point isotropic source to a conical source.
 
I am late in answering this question, but maybe it will help somebody else.

There are two options when you are simulating a situation like this with a point source.
You can "restrict" the source to a cone or you can "bias" the source in the direction of the cone.

The difference between the two cases is that in the restrict case, the tally, which can be per emitted photon, will be different from the isotropic case by some factor depending upon how small the solid angle of the cone is compared to the isotropic source.

In the biasing case, you will still get the run time efficiency of the restrict case, but the tally will still be as if you were simulating an isotropic case.

I am the author of a Python library for generating MCNP input decks which can make this very simple.
https://github.com/pnnl/CardSharpForMCNP
Look for a function called: "insertSource_PointWithAngularAndEnergyDistrib"
In particular look for the parameter "dirDistrib" which can take one of three options: None, Bias, Restrict.

Hope that helps!
 
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