Shutdown dose rate calculation for fission reactors: An application of the MS-CADIS method to OPAL

There have been considerable advances of shutdown dose rate (SDDR) calculation methods for fusion related problems, however applications of these methods in the fission reactor field have hitherto been sparse. The present study attempts to bridge this gap by investigating the applicability of SDDR calculation methods for fission reactor problems. Specifically, we aim to assess and validate whether recent advances in SDDR methods can be successfully applied in fission research reactors. To this end, we estimate the shutdown dose rate distribution at the Open Pool Australian Light water reactor (OPAL) using the rigorous two step (R2S) computational method, and we compare the calculated results with the experimental data. This method utilizes a 3D reactor model implemented in the Monte Carlo N-Particle (MCNP) transport code, the AutomeD VAriaNce reduction Generator (ADVANTG) code for geometry discretization and variance reduction calculations, and the Oak Ridge Isotope GENeration (ORIGEN) inventory code for activation calculations. To ensure robustness, we employ two variance reduction techniques, Forward Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) and Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS). To the best of our knowledge, this is the first MS-CADIS method implementation for fission reactor problems. The SDDR is estimated at ten locations within the experimental hall, all situated more than 4 m away from the reactor core. The paper shows that, the experimental observations are within the lower and upper bounds of the simulation results for 4 out of 10 locations, while the remaining observations are within a factor of 7, with one significant outlier. The calculated average dose rate is within 5% of the nominal values of the experimental observations for 3 locations. The computational results are within statistical uncertainty by using two different variance reduction techniques, with significant computational advantage of MS-CADIS over FW-CADIS for SDDR calculations. The results indicate that the combination of SDDR distribution maps, estimated dose rate energy dependance, and activation information are powerful tools in identifying the radioisotopes and reactor components dominating the SDDR. These results can contribute to better radiation safety practices in contaminated areas, by enabling the minimal dose path planning or by improving radiation shielding.