INTRODUCTION
In this laboratory exercise we used Monte Carlo method for defining neutron flux, using the simulated experimental setup. Monte Carlo method solves the complicated 3 dimensional equations, through random samplings. But as u get the result there exists some uncertainty.
The present laboratory exercise aims to describe the Monte Carlo method and to learn its
application in particle transport modeling. The Monte Carlo method is a numerical method of solving mathematical and physical problems through random sampling. We get the results of neutron thermal flux using the Serpent code.
THEORETICAL BACKGROUND
– Describe the theory behind the experiment. Present the mathematical and physical framework.
Description of the modeling – Explain how the experiment is modeled in Serpent. Describe
the input file.
Description of the results – First of all the obtained data from the simulations should be
presented. Give the raw data as it is before you perform any calculations. Use the layout to present your data and calculations nice and clear. Use tables when suitable, otherwise make plots. Don't forget to present the uncertainty.
nps error Flux number of neutrons that reached the target
100 000 9.2% 6.19147 *10^4 131
500 000 4.186% 6.22261*10^4 771
1. What is the difference of deterministic code and Monte Carlo (MC) code and what is their application area?
MC is the statistic method, using probability and statistical samplings. No transport equation needed, but the equation of probability density of particles (integral transport equation). So in this method statistical error is determined using direct continuous cross-section data. The more statistical samplings the less is the statistical error. That´s why it is time consuming, but the deterministic method is fast on the contrary. And deterministic method on the contrary is not solving global problem, it is...