Monte Carlo-Based Fuzzy TOPSIS and CFD Thermal Modeling for Inert Gas Selection in TN-32B Dry Cask Storage

The type of inert gas utilised for spent fuel storage at the Rooppur Nuclear Power Plant (RNPP) has a significant impact on the thermal performance and safety of the TN-32B dry cask storage system. To determine the suitable gas, this study used fuzzy TOPSIS decision-making, Monte Carlo sensitivity analysis, and CFD simulations with ANSYS Fluent. Under a 34 kW decay heat load, the effects of air, nitrogen, argon, and helium were assessed for a single fuel assembly. The estimated peak temperatures were below the 649 K statutory safety limit: 635 K for helium, 621 K for argon, 591 K for nitrogen, and 589 K for air. For estimating uncertainties in decision-making criteria, fuzzy TOPSIS was applied using 10,000 Monte Carlo simulations, which accounted for a ±20% variation in criteria weights. The outcomes consistently pointed to argon as the most favorable option, showing the highest mean closeness coefficient of 0.681 and ranking first in 79.6% of the simulations. Nitrogen was identified as a strong alternative, with a mean closeness coefficient of 0.647 and securing a second-place position in 20.4% of the simulations. However, neither helium nor air reached the top rank in any simulation, and their mean closeness factors were 0.418 and 0.582, respectively, making them less advantageous. Our combined CFD–MCDM framework offers a methodical and useful approach to choosing dry cask fill gases, enhancing the security and dependability of SNF storage for new NPP projects.