- #1
Anisur Rahman
- 11
- 1
How Can I Simulate a Narrow Spectrum X-Ray Beam Using MCNP?
- #2
Alex A
Gold Member
- 270
- 180
I ran that at 1/100th the nps in MCNP5 and it produces a spectrum for me. The electron voltage might be set at the RMS of the supply voltage of the tube. That would limit the spectrum a bit, it's not fully correct.
Also of note "e0 0.001 100i 0.328" is a linear interpolation and an electron at 47.9keV can't produce an X ray photon above 47.9keV so most of the spectrum must be blank under these conditions.
If you still think you are getting nothing add your output file to a post.
Also of note "e0 0.001 100i 0.328" is a linear interpolation and an electron at 47.9keV can't produce an X ray photon above 47.9keV so most of the spectrum must be blank under these conditions.
If you still think you are getting nothing add your output file to a post.
- #3
Anisur Rahman
- 11
- 1
Here is my output.
- #4
PSRB191921
- 188
- 92
in your file "sdef par=2" emits photons not electrons. You must write par=3
- #5
Alex A
Gold Member
- 270
- 180
Oh wow, good catch @PSRB191921!
@Anisur Rahman, the output file looks otherwise fine but incomplete. Like the program has been told not to run the problem, or it's crashing or it's being killed. 3e6 on one core of my old laptop took 15mins, 3e8 would have taken a full day, what do you see and do when you run it?
@Anisur Rahman, the output file looks otherwise fine but incomplete. Like the program has been told not to run the problem, or it's crashing or it's being killed. 3e6 on one core of my old laptop took 15mins, 3e8 would have taken a full day, what do you see and do when you run it?
- #6
PSRB191921
- 188
- 92
I make some modifications (see my input and output).
first I modified sdef :
"sdef POS= 5 0 0 PAR=3 ext=0 ERG= 0.06 AXS= -1 0 0 vec -1 0 0 DIR= 1 RAD=d1"
I put "par=3" to emit electrons and not photons
I create an electrons beam on the W target (POS= 5 0 0 ext=0 AXS= -1 0 0 vec -1 0 0 DIR= 1 RAD=d1)
It gives :
I transport electrons only in cell 100 and 107 (imp:e 1 0 0 0 0 0 1 0 0), because there is no point in transporting electrons outside of these areas except to increase the calculation time!
I put a F5 tally at 3 cm (in front of the aluminum filter) and F15 at 10 cm (behind the aluminum filter) note that F4 and F1 did not converge with few particles
it gives this results :
hope it's help
first I modified sdef :
"sdef POS= 5 0 0 PAR=3 ext=0 ERG= 0.06 AXS= -1 0 0 vec -1 0 0 DIR= 1 RAD=d1"
I put "par=3" to emit electrons and not photons
I create an electrons beam on the W target (POS= 5 0 0 ext=0 AXS= -1 0 0 vec -1 0 0 DIR= 1 RAD=d1)
It gives :
I transport electrons only in cell 100 and 107 (imp:e 1 0 0 0 0 0 1 0 0), because there is no point in transporting electrons outside of these areas except to increase the calculation time!
I put a F5 tally at 3 cm (in front of the aluminum filter) and F15 at 10 cm (behind the aluminum filter) note that F4 and F1 did not converge with few particles
it gives this results :
hope it's help
- #7
Anisur Rahman
- 11
- 1
Hi @Alex A and @PSRB191921. I am sorry, i uploaded the incomplete output file. In the mean time, i have changed the geometry. I have changed the par and tally too. But when the electron is emitted, it doesn't collide with the tungsten target. I am not sure why this is happening. Can you help me please? I am uploading the input and the output file here.
- #8
Alex A
Gold Member
- 270
- 180
You have a fatal error,
" fatal error. 9 entries not equal to number of cells = 10."
This seems to apply to,
This is the same as,
So you've assigned 9 importances when you need 10.
" fatal error. 9 entries not equal to number of cells = 10."
This seems to apply to,
Code:
imp:e 1 0 1r 1 0 4r $ 100, 109
Code:
imp:e 1 0 0 1 0 0 0 0 0 $ 100, 109- #9
Anisur Rahman
- 11
- 1
I have corrected this fatal error, but still no photon is being recorded. i am attaching the input and output file.
- #10
Alex A
Gold Member
- 270
- 180
Your void cell is 107, this cell needs to have 0 importance for all (both in this case) particles.
Related to How Can I Simulate a Narrow Spectrum X-Ray Beam Using MCNP?
1. What is MCNP and how is it used to simulate X-ray beams?
MCNP (Monte Carlo N-Particle) is a general-purpose Monte Carlo radiation transport code used for simulating the interaction of radiation with matter. It is widely used in medical physics, health physics, and nuclear engineering to model the behavior of X-ray beams, including their generation, propagation, and interaction with different materials.
2. How can I define a narrow spectrum X-ray source in MCNP?
To define a narrow spectrum X-ray source in MCNP, you need to specify the energy distribution of the photons. This can be done using the SDEF card to define the source and the SI and SP cards to specify the energy bins and their respective probabilities. By carefully selecting these parameters, you can create a source with a narrow energy spectrum.
3. What are the important considerations for setting up the geometry and materials in MCNP for X-ray simulations?
When setting up the geometry and materials in MCNP for X-ray simulations, it is crucial to accurately model the physical setup, including the X-ray source, any collimators, filters, and the target material. The materials must be defined using the appropriate material cards (e.g., M cards) with correct elemental compositions and densities to ensure accurate simulation of X-ray interactions such as scattering and absorption.
4. How can I validate my MCNP simulation results for a narrow spectrum X-ray beam?
Validation of MCNP simulation results can be achieved by comparing them with experimental data or results from other established simulation tools. This involves setting up benchmark experiments or using published data to verify that the simulated X-ray spectra, dose distributions, and other relevant parameters match the expected outcomes within acceptable uncertainties.
5. What are some common challenges and solutions when simulating X-ray beams in MCNP?
Common challenges when simulating X-ray beams in MCNP include ensuring accurate source definition, dealing with statistical uncertainties, and managing computational resources. Solutions include using variance reduction techniques to improve simulation efficiency, refining the energy binning to better represent the narrow spectrum, and conducting sensitivity analyses to understand the impact of different parameters on the results.
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