There are several external support facilities that support personnel, materials, and equipment for any nuclear power plant in the world. In Japan, using the lessons of the Fukushima Daiichi accident, the Mihama Nuclear Emergency Assistance Center was established in 2016 to support a nuclear power plant by supplying materials and equipment such as remote-control robots. The purpose of this paper is to summarize the support contents of external support facilities worldwide and compare the contents used at the Mihama Nuclear Emergency Assistance Center, National SAFER Response Center in the USA, Force d’Action Rapide du Nucleaire in France, and Kemtechnische Hilfsdienst GmbH in Germany. There are roughly two types of external support facility. One type of facility supports remote control materials and equipment. The other type of facility supports alternative power supplies and cooling equipment for severe accidents. In addition to these materials and equipment, some external support facilities support radiation control and protection materials. Moreover, this paper summarizes and compares the ways of transporting materials and equipment among external support facilities since the variety of transportation is important to the effectiveness of the support.

To achieve a higher level of safety in the Rokkasho reprocessing plant, it is important to predict the failure mechanism extensively and proactively. Although the effort toward such proactive approaches to explore the possibility of potential failure mechanisms has been based mainly on human experience, the possibility of overlooking important failure mechanisms should be decreased as much as possible. In the present study, the concept of Generalized Failure Mechanism Knowledge (GFMK) has been practically applied to the Rokkasho reprocessing plant, and the applicability of the proposed method to the maintenance activities has been evaluated. GFMK is a knowledge scheme that describes failure mechanisms independent of any particular subject. In this scheme, specific conditions are generalized, which allows us to apply GFMK to completely different equipment. The GFMK base has been built from the records of trouble at the Rokkasho reprocessing plant and applied to the SFP cooling pump to derive possible failure modes, and its appropriateness has been confirmed. As one of the derived failure mechanisms has not been considered in the maintenance activities, the authors believe that the proposed method may contribute to avoiding overlooking possible failures.

This paper describes a method of predicting the break diameter in a loss-of-coolant accident of a pressurized water reactor with machine learning using the data obtained by the safety parameter display system. From the variation in reactor coolant pressure, two feature data, the time difference between LOCA and the time when pressure shows the minimum rate, and the mean pressure decrease rate are determined. The programming language MATLAB is used to extract these feature data and learn them by Gaussian process regression. There are some dispersion factors, such as the break location on the reactor coolant pipe and 1 min sampling timing. The learning results by GPR show relative errors of 7.8% for a 4-loop plant and 9.5% for a 3-loop plant. The learning results are valid for the delay times of 30 and 60 min from the reactor shutdown to LOCA. If the break diameter expands during LOCA, the predicted diameter is useful as input for the plant simulation.

Age-related degradations of various cables used in nuclear power plants have been of constant concern. In general, many types of polymer material are selected for cable insulators because of their high insulating performance. However, they are degraded in not only their mechanical performance but also their electric performance by radiation exposure. Since current inspection methods, such as measuring the insulation resistance, require substantially high costs and workloads, simplified nondestructive methods will be useful. We have developed a digital hammering inspection system with an AE (acoustic emission) sensor. This system detects the degradations of cable insulators due to radiation exposure and aging by assessing the frequency distributions obtained by FFT (fast Fourier transform) analysis of measured signals. In this study, we evaluated the relationship between the natural frequency obtained by the digital hammering system and the breaking elongation measured by the tensile testing of the insulating materials after electron beam irradiations of up to a maximum of 2,000 kGy for cables including those used in a nuclear power plant for about 30 years.

An improvement of the electricity generation cost evaluation method for High Temperature Gas-cooled Reactors (HTGRs) has been performed. Japan Atomic Energy Agency (JAEA) had completed the commercial HTGR concept named Gas Turbine High Temperature Reactor (GTHTR300) and the electricity generation cost evaluation method approximately a decade ago. The cost evaluation was developed on the basis of the method of Federation of Electric Power Companies (FEPC). The FEPC method was markedly revised after the Fukushima Daiichi nuclear disaster. Moreover, the escalation of material and labor costs for the decade should be considered to evaluate the latest cost. Therefore, we revised the cost evaluation method for GTHTR300 and the determined cost was compared with that of the Light Water Reactor (LWR). As a result, it was found that the electricity generation cost of HTGR of 7.9 yen/kWh is cheaper than that of LWR of 11.7 yen/kWh by approximately 30% at the capacity factor of 70%.