Improving RIMPUFF Prediction Using CALMET Diagnostic Meteorological Model

The Risø Mesoscale PUFF model (RIMPUFF) predicts dispersion of released hazardous material and plays an important role in the emergency response system of many Chinese nuclear power plants (NPPs). The wind field over the calculation domain is a critical input of RIMPUFF, which dominates the performance of RIMPUFF. Due to the complex topography of most Chinese NPP sites, it remains challenging to provide a refined wind field for RIMPUFF prediction. To solve the problem, California Meteorological Model (CALMET) is coupled with RIMPUFF for wind field calculation in this study. Moreover, the computing scope and capability of RIMPUFF are enhanced in order to obtain more accurate prediction for the emergency response and source term inversion in nuclear accidents. Except for that the unlimited amount of grid with higher resolution is supported, a new sampling module is added to RIMPUFF for predicting the concentration of radioactive materials and dose at number-unbound arbitrary location. To verify the CALMET-RIMPUFF method, a wind tunnel experiment that replicates the topography of one Chinese NPP site within 10 km-range, is conducted. In the experiment scenario, the speed and vertical profile of the incoming flow is carefully set according to the annual mean wind speed and wind profile data measured in recent years on the meteorological tower of this NPP. The results demonstrate that the wind field calculated by CALMET is consistent with the topography. With this wind field, the RIMPUFF-predicted concentration distribution matches the measurements well both qualitatively and quantitatively. Moreover, the calculation of U.S. Environmental Protection Agency (EPA) statistical evaluation metrics indicate that the random scatter is within a factor of 1.8 and the FAC2 is nearly 80%. It proves the acceptability of CALMET-RIMPUFF over the complex topography of Chinese NPP sites.