Isotopes of alkali and alkaline earth metals (AM and AEM) are the main contributors to the heat load and the radiotoxicity of spent fuel (SF) . These components are separated from the SF and dissolved in a molten LiCl in an electrolytic reduction process. A mass transfer model is developed to describe the diffusion behavior of Cs, Sr, and Ba in the SF into the molten salt. The model is an analytical solution of Fick's second law of diffusion for a cylinder which is the shape of a cathode in the electrolytic reduction process. And the model is also applied to depict the concentration profile of the oxygen ion which is produced by the electrolysis of LiO. The regressed diffusion coefficients of the model correlating the experimentally measured data are evaluated to be greater in the order of Ba, Cs, and Sr for the metal ions and the diffusion of the oxygen ion is slower than the metal ions which implies that different mechanisms govern the diffusion of the metal ions and the oxygen ions in a molten LiCl.

The transfer function was introduced to establish the prediction method for the DO concentration at the intaking point of Kongju Water Works System. In the most cases we analyze a single time series without explicitly using information contained in the related time series. In many forecasting situations, other events will systematically influence the series to be forecasted(the dependent variables), and therefore, there is need to go beyond a univariate forecasting model. Thus, we must build a forecasting model that incorporates more than one time series and introduces explicitly the dynamic characteristics of the system. Such a model is called a multiple time series model or transfer function model. The purpose of this study is to develop the stochastic stream water quality model for the intaking station of Kongju city waterworks in Keum river system. The performance of the multiplicative ARIMA model and the transfer function noise model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the transfer function noise model lead to the improved accuracy.