The concept and methodology of traditional Defense in Depth (DID) was challenged in the Fukushima nuclear accident. In order to fix the weakness of the traditional emergency strategies of nuclear power plants (NPPs) and to enhance the DID for nuclear safety, the U.S. Nuclear Energy Institute (NEI) put forward the concept of Diverse and Flexible Coping Strategies (FLEX) for the special purpose of beyond-design-basis external event (BDBEE) hazard mitigation and the corresponding FLEX support guidelines (FSG). The theory has been wildly spread and accepted by many countries that generate nuclear power. The research on the FLEX strategy is a new trend in nuclear engineering in the recent decade. It provides not only fixed on-site equipment/devices but also on- and off-site portable resources to strengthen the reliability of the nuclear safety system, especially for the disaster/hazards (similar to the Fukushima nuclear accident) triggered by BDBEEs. After a brief introduction of the FLEX strategy, four opportunities and ten challenges are summarized. Subsequently, in view of these challenges and technical difficulties, five suggestions for future work are recommended.

Opinion mining and sentiment analysis based on social media has been developed these years, especially with the popularity of social media and the development of machine learning. But in the community of nuclear engineering and technology, sentiment analysis is seldom studied, let alone the automatic analysis by using machine learning algorithms. This work concentrates on the public sentiment mining of nuclear energy in German-speaking countries based on the public comments of nuclear news in social media by using the automatic methodology, since compared with the news itself, the comments are closer to the public real opinions. The results showed that majority comments kept in neutral sentiment. 23% of comments were in positive tones, which were approximate 4 times those in negative tones. The concerning issues of the public are the innovative technology development, safety, nuclear waste, accidents and the cost of nuclear power. Decision tree, random forest and long short-term memory networks (LSTM) are adopted for the automatic sentiment analysis. The results show that all of the proposed methods can be applied in practice to some extent. But as a deep learning algorithm, LSTM gets the highest accuracy approximately 85.6% with also the best robustness of all.

To enhance the defense in depth for nuclear safety after the Fukushima nuclear accident, the U.S. Nuclear Energy Institute put forward the concept of diverse and flexible coping strategies and the corresponding FLEX support guidelines for the special scenarios of extended loss of alternating current power and loss of ultimate heat sink caused by beyond-design-basis external event. Subsequently, the idea of the FLEX strategy was broadly accepted and spread widely. The introduction of the concept of FLEX strategy into the defense in depth was the biggest improvement for nuclear safety in the recent decade. This paper has reviewed the concept of traditional defense in depth and its weakness that led to the Fukushima nuclear accident, which led to the development motivation for the FLEX strategy. The research progress of the FLEX strategy in different countries in the past ten years has been reviewed. Based on the literature, and the aforementioned review, some recommendations for future work have been presented.