As the decommissioning of nuclear power plants increases, there is an increasing interest in the amounts of radioactive waste. Especially, the radiation dose limit for packaging of radioactive wastes shall not exceed 2 mSv·h−1 and 0.1 mSv·h−1 on contact and at 2 m, respectively in South Korea. The DEMplus provides various environmental geometry and all properties such as materials, absorptions, and reflections and the estimation of the radiation dose rates is based on the radiation interactions of the designed 3D geometry model. With the consideration of the radiation dose rate by using DEMplus and its strategy of packaging plan, the radiation shielding was optimized and estimated in this paper. The modular shielded containers (MSC) with shielding inserted were used for radioactive wastes that require shielded packaging. In order to verify the accuracy of the estimated radiation dose rate by using DEMplus, the estimated results were compared with those obtained using MicroShield. The trends of the estimated radiation dose rates using DEMplus and the estimation of MicroShield were similar to each other. The results of this study demonstrated the feasibility of using DEMplus as a means of estimating the radiation dose limit in packaging plan of the radioactive waste.

Hydrologic responses to variations in storm direction provide useful information for the analysis and prediction of floods and the development of watershed management strategies. However, the prediction of hydrologic responses to changes in storm direction is a difficult task that requires meteorological simulations and extensive computation. It is also difficult to identify the center of rotation of a storm affecting a basin of interest. Therefore, we propose a simple approach of rotating the basin position relative to the storm within the rainfall-runoff simulation model instead of changing the pathway of the storm, which we term the Basin Rotation Method (BRM). The proposed BRM was tested on four major typhoon events in South Korea. The results illustrated that the original basin orientation (i.e., before it was rotated) exhibits earlier and higher peak discharge and earlier recession compared to the basin after rotation. We conclude that the proposed method (BRM) is a viable alternative for use in assessing the directional influence of moving storms on floods caused by historical rather than hypothetical storm events.

Radars have been widely employed to detect precipitation and to predict rainfall. However, the radar-based estimate of rainfall is affected by uncertainties or errors such as mis-calibration, beam blockage, anomalous propagation, and ground cutter. Even though these uncertainties of radar rainfall estimate (RRE) have been studied, their effect on a runoff simulation especially to the peak discharge and peak time have not been much focused. Therefore, the objective of current study is to analyze the effect of the RRE uncertainties or errors based on synthetic simulation of RRE and its effect on peak discharge. First of all, mean of modeled radar rainfall is fixed (e.g., 100mm) and its error variance was set as ±10mm, ±20mm, ±40mm, and ±50mm independent to each grid cell. This independent simulation is based on white-noise process. The second simulation included a spatial-correlation between grid cells in simulating the error variance. The relationship between the distances of rain gauges and the corresponding correlations was modeled with the power law function. The parameters of the function were estimated through meta-heuristic method (specifically harmony search). Moreover, in order to find the correlation of observed data, the whole data from 27 rain gauges in the basin and the corresponding RRE from the dual polarization radar on Mt. Bisl in Korea were employed. The results of the former simulation (independent errors to each grid cell) show that the bias of the peak discharge is increased along with the variance increased, which is caused by influence of zero values. In the latter simulation (spatially correlated errors between grid cells), the results show that the peak discharge variance from the latter presents much larger than that of the former. Furthermore, the spatial distribution pattern of the modeled radar rainfall exhibited very similar to that of the real rainfall. Finally, we concluded that the error variance of RRE on runoff simulation leading bias and high uncertainty.