# MCNP Simulation of Tokamak Energy Deposition

• marco_nuc
In summary, the user is looking for a way to accurately calculate energy deposition in multiple materials within their mesh domain in MCNP. One potential solution is to use the FMESH4 card with the MATERIAL modifier or the FMESH:R and FMESH:RZ cards to define different materials for each mesh cell or region.
marco_nuc
Hello there,

I am using mcnp6 to simulate a tokamak. I am interested in the energy deposition in the blanket and I am using a fmesh4 and the tally multiplier fm4 as follow:

fmesh4:n ORIGIN=0 -24.2 -50 OUT=CF
imesh=35.2 iints=352
jmesh=24.2 jints=484
kmesh=50 kints=1
fm4 (-1 1 1 -4)

Now, MCNP allows you to use only one material in the fm card, in my case material 1. Unfortunately, I have six different materials (in several different cells) in the mesh domain and I am wondering if there's a way to make mcnp aware of that such that it'll automatically consider different materials of different cells in the mesh domain. I could use six different fm4, one fore each material, and merge the six outputs in a single matrix representing my blanket but it would be really tedious. I hope someone can help. I have read about a wild-card material 0 but I can't figure out how that works :(

Hello,

Thank you for your post. It seems like you are facing a common issue in MCNP simulations, where you have multiple materials in your mesh domain and want to accurately calculate the energy deposition in each material. One potential solution to this problem is to use the FMESH4 card with the MATERIAL modifier, which allows you to specify different materials for each mesh cell.

The syntax for this card is:

FMESH4:n ORIGIN=ox oy oz OUT=CF
imesh=ix iints=nix
jmesh=jy jints=niy
kmesh=kz kints=niz
MATERIAL=(mat1,mat2,mat3,...)

This will assign mat1 to the first mesh cell, mat2 to the second mesh cell, and so on. You can also use the WILD card material 0 to assign the default material to all other mesh cells.

Additionally, you can use the FMESH:R and FMESH:RZ cards to define a region or region-z mesh, respectively, which allows you to define different materials for each region.

I hope this helps you in your simulation. If you have any further questions, please feel free to ask. Best of luck with your research!

## 1. How does MCNP simulate tokamak energy deposition?

MCNP (Monte Carlo N-Particle) is a computer code used to simulate the transport of particles through matter. In the context of tokamak energy deposition, MCNP uses a combination of nuclear data, geometry descriptions, and user-defined input parameters to track the interactions of energetic particles with the materials in a tokamak device.

## 2. What types of particles can be simulated with MCNP for tokamak energy deposition?

MCNP is capable of simulating a wide range of particles, including neutrons, photons, electrons, protons, and ions. This makes it a useful tool for studying energy deposition in tokamaks, which typically involve a variety of particle species.

## 3. How accurate are MCNP simulations of tokamak energy deposition?

The accuracy of MCNP simulations depends on the quality of the input data and the complexity of the system being simulated. In general, MCNP has been shown to produce results that agree well with experimental data for tokamak energy deposition, but it is important to validate and verify the simulation results with experimental data in order to ensure accuracy.

## 4. Can MCNP simulate the effects of plasma turbulence on tokamak energy deposition?

Yes, MCNP has the ability to incorporate turbulence effects into its simulations. This is achieved through the use of specialized models that describe the behavior of turbulent plasmas and their interactions with energetic particles.

## 5. How can MCNP simulations of tokamak energy deposition be used to optimize tokamak designs?

MCNP simulations can provide valuable insights into the behavior of energetic particles in tokamak devices, allowing for the optimization of various design parameters such as material composition, geometry, and operating conditions. By using MCNP to study different design options, scientists can identify the most efficient and effective configurations for tokamak energy deposition.

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