Total Ambient Dose Equivalent Buildup Factor Determination for Nbs04 Concrete

Area of Science:

• Nuclear Engineering
• Radiation Shielding Physics
• Computational Physics

Background:

• Buildup factors are essential for point kernel method radiation shielding calculations.
• The point kernel method faces challenges in neutron shielding due to complex neutron transport and energy-dependent cross sections.
• Accurate buildup factors require precise simulation of radiation interactions within shielding materials.

Purpose of the Study:

• To calculate total ambient dose buildup factors for NBS04 concrete using neutron and secondary gamma ray transmission factors.
• To investigate the sensitivity of these factors to variations in concrete water content.
• To develop a machine learning model for predicting buildup factors.

Main Methods:

• Utilized MCNP6™ code with updated cross sections to compute neutron and secondary gamma ray transmission factors.
• Performed sensitivity analysis by varying water content in concrete.
• Employed support vector regression (a machine learning technique) to build a predictive model for buildup factors.

Main Results:

• Calculated and tabulated neutron and secondary gamma ray transmission factors and total ambient dose buildup factors for NBS04 concrete.
• Demonstrated a significant impact of water content variations on both transmission and buildup factors.
• Developed a machine learning model capable of predicting buildup factors with approximately 20% relative error.

Conclusions:

• The study provides essential data for neutron shielding applications using NBS04 concrete.
• Water content is a critical parameter influencing the effectiveness of concrete shielding.
• The developed machine learning model offers a practical tool for estimating buildup factors, enhancing the applicability of shielding calculations.