ANN Prediction of Linear Attenuation Coefficients for 40MgO–30B2O3–30SiO2 System
DOI:
https://doi.org/10.22399/ijasrar.56Keywords:
ANN, Radiation shielding, Phy-X/PSD, LACAbstract
Radiation shielding is of great importance for protecting human health, which has led to increasing research on alternative shielding materials. Glass materials are widely used in various applications, making it essential to investigate their radiation attenuation properties. In this study, the radiation shielding characteristics of magnesium borosilicate glasses were predicted by partially substituting B₂O₃ with MgO using Artificial Neural Network (ANN). The glass samples were prepared with compositions of 30SiO₂–30B₂O₃–40MgO. The linear attenuation coefficient (LAC) was obtained and compared with the results obtained Phy-X/PSD.
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