Comparison of deterministic and Monte Carlo methods in shielding design

Area of Science:

• Nuclear engineering
• Radiation shielding analysis
• Computational physics

Background:

• Deterministic methods in radiation shielding are computationally efficient but may suffer accuracy issues at low energies.
• The use of extrapolated build-up factors in deterministic codes can introduce significant errors, especially under varying geometrical conditions.
• Monte Carlo (MC) methods offer high accuracy but are computationally intensive.

Purpose of the Study:

• To evaluate the accuracy of deterministic shielding calculation methods at low energies.
• To compare the performance of a commercial deterministic code (MicroShield) against a Monte Carlo code (MCNP).
• To analyze the impact of parameters like energy and geometry on shielding calculation accuracy.

Main Methods:

• Deterministic shielding calculations were performed using MicroShield 5.05.
• Monte Carlo simulations were conducted using MCNP for comparison.
• Sensitivity analysis was applied to parameters such as energy and geometrical conditions (point/cylindrical sources, slab shield).

Main Results:

• Deterministic methods showed potential for significant errors in low-energy shielding calculations when relying on extrapolated build-up factors.
• Comparison revealed discrepancies between deterministic and Monte Carlo results, particularly sensitive to energy and geometry.
• The study quantified the impact of build-up factor extrapolation and geometrical complexities on shielding results.

Conclusions:

• Deterministic methods require careful validation for low-energy shielding applications, especially when geometrical conditions deviate from standard data.
• Accurate build-up factor data or alternative approaches are crucial for improving the reliability of deterministic shielding calculations.
• Monte Carlo methods remain a benchmark for accurate shielding assessments, particularly in complex scenarios.