Applications of Machine Learning to Consequence Analysis of Hypothetical Accidents at Barakah Nuclear Power Plant Unit 1

The United Arab Emirates (UAE) built four nuclear power plants at the Barakah site to supply 25% of region’s electricity. Among Nuclear Power Plants, (BNPPs), their main objectives are achieve highest possible safety for environment, operators, and community members; quality reactors energy; production efficiency. To meet these objectives, decision-makers must access large amounts data in case a accident prevent release radioactive materials. Machine learning offers feasible solution propose early warnings help contain accidents. Thus, our study aimed developing testing machine model classify accidents using associated We used Radiological Assessment System Consequence Analysis (RASCAL) software estimate concentration released materials seasons year 2020. applied concentrations as predictors classification tree three types severe Unit 1 BNPPs each season. average accuracy models was 97.3% training 96.5% test data, indicating high efficacy. generated can distinguish between simulated any