Multi-pass Monte Carlo simulation method in nuclear transmutations.

Area of Science:

• Computational Physics
• Nuclear Engineering
• Simulation Methods

Background:

• Direct Monte Carlo simulations require constant probabilities for accuracy.
• Physical systems, such as activation/transmutation setups, involve evolving probabilities.
• Simulating systems with Avogadro-scale components presents computational challenges due to minute probability shifts.

Purpose of the Study:

• To develop a method for handling changing probabilities in Monte Carlo simulations.
• To increase the precision of simulations for evolving physical systems.
• To provide an accessible introduction to Monte Carlo methods for students in nuclear reactor physics.

Main Methods:

• Proposing a method to dynamically adjust probabilities during simulation.
• Implementing an approximating approach for fast calculations.
• Focusing on applications in nuclear reactor simulations.

Main Results:

• The proposed method addresses the limitations of static probability simulations.
• It offers a way to improve the accuracy of simulations with evolving components.
• The approach is designed to be computationally feasible within current resources.

Conclusions:

• The novel Monte Carlo method effectively handles dynamic probability changes.
• This technique enhances simulation precision for complex, evolving systems.
• It serves as a valuable tool for both research and educational purposes in nuclear reactor physics.