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Total Ambient Dose Equivalent Buildup Factors for Portland Concrete
Paulina Duckic1, Robert Bruce Hayes2
1University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia.
Health Physics
|July 26, 2018
Summary
This study calculates ambient dose equivalent buildup factors for Portland concrete using MCNP6 simulations. It also explores a machine learning model for predicting these factors, crucial for radiation shielding design.
Area of Science:
- Nuclear Engineering and Radiation Shielding
- Computational Physics
- Materials Science
Background:
- Accurate calculation of radiation shielding effectiveness is critical for nuclear safety and radiation protection.
- Buildup factors, which account for scattered radiation, are complex to determine due to numerous variables like geometry, source energy, and material composition.
- Standard Portland concrete is a widely used shielding material, necessitating detailed characterization of its shielding properties.
Purpose of the Study:
- To calculate total ambient dose equivalent buildup factors for Portland concrete slabs using Monte Carlo simulations.
- To investigate the sensitivity of buildup factors to variations in concrete composition (water content, aggregate).
- To develop a machine learning model (Support Vector Regression) for predicting concrete buildup factors.
Main Methods:
- Utilized Monte Carlo N-Particle software MCNP6 for simulating neutron and gamma-ray transport through Portland concrete.
- Calculated transmitted dose rates and subsequently derived total buildup factors for various source types (Cf, Am-Be) and neutron energies (0.025 eV to 14 MeV).
- Performed sensitivity analysis by varying water content and aggregate amounts in the concrete composition.
Main Results:
- Successfully calculated ambient dose equivalent buildup factors for Portland concrete under diverse conditions.
- Quantified the credible dispersion in buildup factors due to variations in concrete composition, highlighting sensitivity to water and aggregate content.
- Developed and validated a Support Vector Regression model for predicting concrete buildup factors, offering a potential alternative to complex simulations.
Conclusions:
- The study provides essential data on radiation buildup factors for Portland concrete, aiding in the design of effective shielding.
- Sensitivity analysis reveals key material parameters influencing shielding performance, guiding material selection and optimization.
- The developed machine learning model demonstrates promise for efficient and accurate prediction of concrete buildup factors in radiation shielding applications.
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