Korea Atomic Energy Research Institute (“KAERI”) has been developing various studies related to the nuclear fuel cycle. Among them, KAERI was focusing on the pyroprocess, which recycles some useful elements white reducing the volume and toxicity of spent nuclear fuel (SNF). Pyroprocess involves the handling of SNF, which cannot be handled directly by the facility worker. Therefore, SNF is handled and processed through remote handling device within a shielded facility such as a hot cell. Nuclear Facilities with such hot cells are called nuclear fuel cycle facilities, and unlike other facilities, heating, ventilating, and air conditioning (HVAC) system are particularly important in nuclear fuel cycle facilities to maintain the atmosphere in the hot cell and remove radioactive materials. In addition, due to the nature of the pyroprocess, which uses molten salt, corrosion is a problem in air atmosphere, so the process can only be carried out in an inert gas atmosphere. KAERI has a nuclear fuel cycle facility called the Irradiation Material Examination Facility (IMEF), and has built and operated the ACPF inside the IMEF, which operates an inert atmosphere hot cell for the demonstration of the pyroprocess. For efficient process development of the pyroprocess, it is necessary to put the developed equipment into the hot cell, which is a radiationcontrolled area, after sufficient verification in a mock-up facility. For this purpose, the ACPF mock-up facility, which simulates the system, space, and remote handling equipment of the ACPF, is operated separately in the general laboratory area. The inert gas conditioning system of the ACPF consists of very complex piping, blowers, and valves, requires special attention to maintenance. In addition, if there is a small leak in the piping within these valves or piping, radioactive materials can be directly exposed to facility workers, so continuous monitoring and maintenance are required to prevent accident. In this study, the applicability of acoustic emission technology and ultrasonic technology for leak detection in the inert gas conditioning system of ACPF mock-up facility was investigated. For this purpose, new bypass pipes and valves were installed in the existing system to simulate the leakage of pipes and valves. Acoustic emission sensors are attached directly to pipes or valves to detect signals, while ultrasonic sensors are installed at a distance to detect signals. The optimal parameters of each technology to effectively suppress background noise were derived and, and the feasibility of identifying normal and abnormal scenarios in the system was analyzed.

This paper describes the development and operation of an autonomous robotic system designed for pyroprocess automation. The unique challenges of pyroprocess automation, such as the need for a highly dry atmosphere to handle materials like chloride, are addressed through this system. For the experiments, a specialized dehumidifier and dry mock-up facility were designed to produce dry air condition. Performances of dry air conditioning for the various simulated situations were evaluated, including assessing worker access within a mock-up to determine the system’s feasibility. To enable automation, containers used for processing materials were modified to fit the gripper system of the gantry robot. The loading and unloading of materials in each equipment were automated to connect them with the robotic system. This gantry robot primarily utilized macro motions to approach waypoints containing process materials, reducing the need for precise approach motions. Its tapered jaw design allowed it to grip target objects even with imperfect positioning. The robot’s motions were programmed initially using a robot simulator for positioning and motion planning, and real-world accuracy was tested in a dry mock-up facility using the OPC platform. Finally, the paper discusses the potential application of XR (eXtended Reality) technology in this context, which could enhance the robot’s operation and provide valuable insights into the automation process. Further analysis of XR technology’s feasibility and benefits for this specific pyroprocess automation system are presented.

With the increasing number of aging buildings across Korea, emerging maintenance technologies have surged. One such technology is the non-contact detection of concrete cracks via thermal images. This study aims to develop a technique that can accurately predict the depth of a crack by analyzing the temperature difference between the crack part and the normal part in the thermal image of the concrete. The research obtained temperature data through thermal imaging experiments and constructed a big data set including outdoor variables such as air temperature, illumination, and humidity that can influence temperature differences. Based on the collected data, the team designed an algorithm for learning and predicting the crack depth using machine learning. Initially, standardized crack specimens were used in experiments, and the big data was updated by specimens similar to actual cracks. Finally, a crack depth prediction technology was implemented using five regression analysis algorithms for approximately 24,000 data points. To confirm the practicality of the development technique, crack simulators with various shapes were added to the study.

Cutting reactor pressure vessels (RPV) into acceptable sizes for waste disposal is a key process in dismantling nuclear power plants. In the case of Kori-1, a remote oxyfuel cutting method has been developed by Doosan Heavy Industry & Construction to dismantle RPVs. Cutting radioactive material, such as RPV, generates a large number of fine and ultrafine particles incorporating radioactive isotopes. To minimize radiological exposure of dismantling workers and workplace surface contamination, understanding the characteristics of radioactive aerosols from the cutting process is crucial. However, there is a paucity of knowledge of the by-products of the cutting process. To overcome the limitations, a mock-up RPV cutting experiment was designed and established to investigate the characteristics of fine and ultrafine particles from the remote cutting process of the RPV at the Nuclear Decommissioning Center of Doosan Heavy Industry & Construction. The aerosol measurement system was composed of a cutting system, purification system, sampling system, and measurement device. The cutting system has a shielding tent and oxyfuel cutting torch and remote cutting robot arm. It was designed to prevent fine particle leakage. The shielding tent acts as a cutting chamber and is connected to the purification system. The purification system operates a pressure difference by generating an airflow which delivers aerosols from the cutting system to the purification system. The sampling system was installed at the center of the pipe which connects the shielding tent and purification system and was carefully designed to achieve isokinetic sampling for unbiased sampling. Sampled aerosols were delivered to the measurement device. A high-resolution electrical low-pressure impactor (HR-ELPI+, Dekati) is used to measure the size distribution of inhalable aerosols (Aerodynamic diameter: 6 nm to 10 μm) and to collect size classified aerosols. In this work, the mock-up reactor vessel was cut 3 times to measure the number distribution of fine and ultrafine particles and mass distribution of iron, chromium, nickel, and manganese. The number distribution of aerosols showed the bi-modal distribution; two peaks were positioned at 0.01−0.02 μm and 0.04–0.07 μm respectively. The mass distribution of metal elements showed bi-modal and trimodal distribution. Such results could be criteria for filter selection to be used in the filtration system for the cutting process and fundamental data for internal dose assessment for accidents. Future work includes the investigations relationships between the characteristics of the generated aerosols and physicochemical properties of metal elements.