Digital Twins and Predictive Analytics
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Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article