Exploring the potential of artificial intelligence in nuclear waste management: Applications, challenges, and future directions

Abstract

This study examines the increasing potential of artificial intelligence (AI) to transform nuclear waste management by enhancing procedures related to waste classification, treatment, storage, and disposal. The ability of AI to examine extensive datasets via machine learning and data analytics improves the accuracy and efficiency of trash classification. Additionally, AI-driven optimization methods enhance treatment procedures, reduce risks, and guarantee adherence to stringent regulatory standards, resulting in safer management of radioactive materials. These developments in AI enhance operational efficiency and refine decision-making frameworks, facilitating more accurate risk assessments. Integrating AI into nuclear waste management enables stakeholders to negotiate intricate regulatory frameworks more efficiently while minimizing environmental consequences and safeguarding public health.

This report identifies essential domains for forthcoming research and development in AI-augmented nuclear waste management. Essential directives encompass enhancing AI algorithms for real-time surveillance and predictive analytics, facilitating the early identification of possible problems, and enabling more proactive management. Moreover, developing technologies like robotic systems and autonomous platforms possess the capability to automate numerous waste management jobs, hence diminishing human risk exposure. The continuous developments illustrate AI’s revolutionary capacity to tackle critical issues in nuclear waste management, guaranteeing the safe, responsible, and sustainable management of radioactive materials for future generations.