Journal of Nuclear Fuel Cycle and Waste Technology

A method for predicting the level of radioactive waste during the preliminary decommissioning stage of a nuclear reactor is presented, utilizing both Monte Carlo and deterministic codes simultaneously. An autonomous simulation code, developed in Python, was created to estimate radioactive waste during the decommissioning of both PWR and CANDU reactors. The materials considered for activation analysis include only concrete, stainless steel, and vessel steel. Neutron flux is calculated using MCNP, a Monte Carlo-based code, while SCALE-ORIGEN, which is based on the matrix exponential method, is used to perform the activation analysis. The developed RSAM (Reactor Structures Activation Module) serves as a bridge between these two codes, enabling the automatic generation of activation analysis input files and the interpretation of results. Additionally, RSAM can autonomously conduct activation sensitivity analysis based on material data from NUREG-3474. To verify RSAM’s performance, activation analyses were conducted on the structural components of CANDU and OPR-type reactors. The developed Module effectiveness was demonstrated through case studies on CANDU and OPR reactor (→ PWR and PHWR), indicating its broad applicability and potential as a valuable tool for nuclear power plant decommissioning projects.

Keywords

MCNP, ORIGEN-S, Activation analysis, Impurity, Structure material