Major accidents at nuclear power plants generate huge amounts of radioactive waste in a short period of time over a wide area outside the plant boundary. Therefore, extraordinary efforts are required for safe management of the waste. A well-established remediation plan including radioactive waste management that is prepared in advance will minimize the impact on the public and environment. In Korea, however, only limited plans exist to systematically manage this type of off-site radioactive waste generating event. In this study, we developed basic strategies for off-site radioactive waste management based on recommendations from the IAEA (International Atomic Energy Agency) and NCRP (National Council on Radiation Protection and Measurements), experiences from the Fukushima Daiichi accident in Japan, and a review of the national radioactive waste management system in Korea. These strategies included the assignment of roles and responsibilities, development of management methodologies, securement of storage capacities, preparation for the use of existing infrastructure, assurance of information transparency, and establishment of cooperative measures with international organizations.

The leading source of occupational fatalities is a portable ladder in Korea because it is widely used in industry as work platform. In order to reduce victims, it is necessary to establish preventive measures for the accidents caused by portable ladder. Therefore, this study statistically analyzed injury death by portable ladder for recent 10 years to investigate the accident characteristics. Next, to monitor wearing of safety helmet in real-time while working on a portable ladder, this study developed an object detection model based on the You Only Look Once(YOLO) architecture, which can accurately detect objects within a reasonable time. The model was trained on 6,023 images with/without ladders and safety helmets. The performance of the proposed detection model was 0.795 for F1 score and 0.843 for mean average precision. In addition, the proposed model processed at least 25 frames per second which make the model suitable for real-time application.