Understanding MCNP Output File: Mean Alpha Energy and Particle Distribution

In summary: I'm sorry I can not help you more.In summary, MCNP tells the user that the mean alpha energy is 7.19310E-04 after a million simulations, and that the error in the mean value is +/- 0.0002. Additionally, the input file is in mode p, which only photon data is being transported.
  • #1
zincsulphide
9
0
Hi there,

I would like some help understanding the attached MCNP output file.

The file tells me that the mean alpha energy is 7.1931E-04 after a million simulations.

I have two questions:
  1. Does the file tell me anywhere what the error in the mean value is (+/-)? Or can I simply work this out from the central limit theroem (1/sqr(number of samples)) = 0.001 MeV
  2. Does the output file list the number of particles in each energy bin, or the average energy of each energy bin? I would like to plot a histogram of number of particles in each bin (or mean bin energy) vs. energy bins. I think the mean energy of each bin is as follows, but I am not sure.
2.0000E-01 1.97533E-04 0.0018
4.0000E-01 1.88478E-04 0.0018
6.0000E-01 3.33297E-04 0.0010
8.0000E-01 0.00000E+00 0.0000
1.0000E+00 0.00000E+00 0.0000
1.2000E+00 0.00000E+00 0.0000
1.4000E+00 0.00000E+00 0.0000
1.6000E+00 0.00000E+00 0.0000
1.8000E+00 0.00000E+00 0.0000
2.0000E+00 0.00000E+00 0.0000
total 7.19309E-04 0.0002

https://docdro.id/M06dhFQ

Thank you for any help
 
Last edited:
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  • #2
Hi,
you write:
"The file tells me that the mean alpha energy is 7.1931E-04 after a million simulations."
remember that MCNP normalized the results with one particule. The result does not depend of the number of particle simulated.
Second you write "alpha Energy" but your input file is in mode p (only photons are transported no alpha !)
you write " mean alpha Energy" but you used a F4 tally : it is not not a enrgy but a fluence !
etc.
 
  • #3
PSRB191921 said:
Hi,
you write:
"The file tells me that the mean alpha energy is 7.1931E-04 after a million simulations."
remember that MCNP normalized the results with one particule. The result does not depend of the number of particle simulated.
Second you write "alpha Energy" but your input file is in mode p (only photons are transported no alpha !)
you write " mean alpha Energy" but you used a F4 tally : it is not not a enrgy but a fluence !
etc.

Yes I'm self-teaching MCNP and finding it quite difficult.

Can I ask two questions:

1. When inputting dimensions into the cell and surface cards, does MCNP assume they are in centimeters?

2. For my task I am modelling the detection of efficiency of zinc sulphide for detecting alpha particles. If I am altering detector distance, is it appropriate to plot a graph of fluence against detector distance, or is there a more appropriate measurement?

Thanks again
 
  • #4
hi
1 yes in cm
2it is interesting to have the response in function of energy
 

Related to Understanding MCNP Output File: Mean Alpha Energy and Particle Distribution

1. What is MCNP Output File?

MCNP (Monte Carlo N-Particle) is a computer code used to simulate the transport of particles through matter. The output file contains the results of the simulation, including the mean alpha energy and particle distribution.

2. What is mean alpha energy?

Mean alpha energy is the average energy of alpha particles emitted from a radioactive source. It is an important parameter in radiation protection and can be calculated from MCNP simulations.

3. How is mean alpha energy calculated in MCNP?

MCNP calculates the mean alpha energy by tracking the energy of each alpha particle as it travels through the simulated material. The average of these energies is then calculated and reported in the output file.

4. What is particle distribution?

Particle distribution refers to the spatial distribution of particles within a given material or region. In the context of MCNP output files, it refers to the distribution of alpha particles within the simulated material.

5. How can understanding MCNP output file help in radiation research?

MCNP output file provides valuable information about the transport of particles through matter, which is crucial in radiation research. It can help in understanding the behavior of alpha particles and their effects on materials, as well as in designing and optimizing radiation shielding materials.

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