To efficiently manage the waste packages like drums, it is meaningful to utilize the data of placement and emplacement of disposed waste in geological storage. For the transparent and real-time management of disposal data, both technical as well as administrative factors must be included. To this end, MIRAE-EN Co., Ltd. has developed a radioactive waste tracking and management system (m-trekⓇ v1.0) through radioactive waste management life cycle which is supported by KETEP. Enhancing the functional features of m-trekⓇ, IoT-based drum location measuring and data of those drums, such as position, radionuclides, activity, and dose etc., are to be collected and monitored through data modeling and visualization, which might be utilized in emplacing the loaded drums according to specifically certain criteria of internal and external data of disposal site. Position measuring using Beacon utilizes Received Signal Strength Indicator (RSSI) to locate the correct position in 3D area. Since RSSI is affected by the surrounding environment, it is required to corrective optimization. In addition, error and deviation of previously applied Gaussian filter method, was corrected and improved through AI learning model. According to this location information and those data, the prototype in future provides the visualization of drum position and its relevant data for administrative purpose such as monitoring, emplacement and other management policy.

In order to treat groundwater containing high levels of nitrate, nitrate reduction by nano sized zero-valent iron (nZVI) was studied using batch experiments. Compared to nitrate removal efficiencies at different mass ratios of nitrate/Fe0, the removal efficiency at the mass ratio of 0.02% was the highest(54.59%). To enhance nitrate removal efficiency, surface modification of nZVI was performed using metallic catalysis such as Pd, Ni and Cu. Nitrate removal efficiency by Cu-nZVI (at catalyst/Fe0 mass ratio of 0.1%) was 66.34%. It showed that the removal efficiency of Cu-nZVI was greater than that of the other catalysts. The observed rate constant (kobs) of nitrate reduction by Cu-nZVI was estimated to 0.7501 min-1 at the Cu/Fe mass ratio of 0.1%. On the other hand, TEM images showed that the average particle sizes of synthetic nZVI and Cu-nZVI were 40~60 and 80~100 nm, respectively. The results imply that catalyst effects may be more important than particle size effects in the enhancement of nitrate reduction by nZVI.