Prediction and assessment of optimal concrete compositions for overall radiation protection and reduced global warming potential.

ABSTRACT: Developing an efficient radiation-shielding concrete composition holds paramount importance for nuclear, medical, and defence facilities. The intricate interactions between various radiation particles and materials across different energy ranges present challenges in designing effective and resilient overall shielding structures. This study presents a novel approach that integrates machine learning and genetic algorithms (GA) to optimize concrete compositions for enhanced radiation shielding against gamma and neutron rays across a wide energy spectrum. By leveraging these advanced techniques, six compositions (concrete_1-concrete_6) spanning different density ranges were derived from an extensive database developed from the previous experimental researches. Subsequently, the shielding effe

SUBMITTER: Saxena S 

PROVIDER: S-EPMC11833061 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature