Decay Heat Uncertainty Analysis for VVER Spent Nuclear Fuel

Abstract Total Monte Carlo (TMC) extends the Monte Carlo method, using stochastic techniques and random sampling to solve the Boltzmann transport equation in spent nuclear fuel (SNF) depletion analysis. TMC evaluates the impact of uncertainties in nuclear data, such as cross sections and fission product yields, on SNF characteristics, focusing on decay heat, which is crucial for SNF handling and management. TMC generates random nuclear data variations within uncertainty ranges for Monte Carlo simulations, resulting in outcome distributions (e.g., decay heat) that reflect real-world behavior uncertainties. The uncertainty analysis examined a standard VVER-440 nuclear fuel. Using the serpent 2 code and referencing the endf/b-viii.0 and tendl nuclear data libraries, the study focused on the impact of cross sections and fission product yield nuclear data uncertainty on the decay heat of a standard VVER-440 nuclear fuel. The time frame chosen for both post-reactor shutdown and long-term for spent fuel cask loading is chosen, providing a comprehensive view of the nuclear fuel cycle.