In the context of a geological repository for nuclear waste, fast and accurate predictions of decay heat are needed for different applications ranging from canister loading optimization to comparing decay heat predictions from state-of-the-art codes with experimental measurements. This work uses a large database of simulated pressurized water reactor (PWR) spent nuclear fuel (SNF) with an extensive range of fuel parameters to demonstrate that by using only the burnup, initial enrichment, and cooling time of the SNF, it is possible to predict the decay heat of a PWR SNF.

A linear interpolation model has been developed using the simulated data and tested on data from decay heat measurements using a calorimeter. The model code was also made publicly available [V. Solans, “Python Script for the Prediction of Decay Heat from PWR Spent Nuclear Fuel Using Fuel Parameters,” Zenodo (2024)]. The results show that the decay heat can be well predicted, with the relative error between measurements and predictions ranging between 4% and 8%. After correcting for a systematic deviation between predictions and experimental results using the limited set of experimental measurement data available, the relative error can be further reduced to 2% to 3%.