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Probabilistic risk assessment (PRA) is an effective methodology that could be used to improve the safety of nuclear power plants in a reasonable manner. Dynamic PRA, as an advanced PRA, allows for more realistic and detailed analyses by handling time-dependent information. However, the applications of this method to practical problems are limited because it remains in the research and development stage. This study aimed to investigate the possibility of utilizing dynamic PRA in risk-informeddecision-making. Specifically, the author performed an accident sequence precursor (ASP) analysis on the failure of emergency diesel generators that occurred at Unit 1 of the Tomari Nuclear Power Plant in Japan using dynamic PRA. The results were evaluated by comparison with the results of simplified classical PRA. The findings indicated that dynamic PRA may estimate lower risks compared with those obtained from classical PRA by reasonable modeling of alternating current power recovery. The author also showed that dynamic PRA can provide detailed information that cannot be obtained with classical PRA, such as uncertainty distribution of core damage timing and importance measure considering the system failure timing.

Economic constraints are driving the electric power industry to seek improved methods for monitoring, control, and diagnostics. To increase plant availability, various techniques have been implemented in industry to assess equipment condition to prevent system inoperability. The availability of a large number of measured signals and additional component information and the increasing number of signal processing options to analyze sampled data motivate the assimilation of such diverse information into a plantwide condition monitor. The use of fuzzy logic is described herein for the purpose of performing the decision making regarding the system status and the possible need for component maintenance. Fuzzy-logic-based diagnostic monitoring is applied to data acquired from instrumentation within operating facilities.

Neutron production methods are an integral part of research and analysis for an array of applications. This paper examines methods of neutron production, and the advantages of constructing a radioisotopic neutron irradiator assembly using252Cf. Characteristic neutron behavior and cost-benefit comparative analysis between alternative modes of neutron production are also examined. The irradiator is described from initial conception to the finished design. MCNP modeling shows a total neutron flux of 3 × 105 n/(cm2·s) in the irradiation chamber for a 25 μg source. Measurements of the gamma-ray and neutron dose rates near the external surface of the irradiator assembly are 120 μGy/h and 30 μSv/h, respectively, during irradiation. At completion of the project, total material, and labor costs remained below $50,000.

This paper addresses the problem of fission material reproduction increase in thermal reactors. Reproduction increase is achieved while decreasing the fission material content in the fuel. In that case, a decrease of neutron loss in construction materials and a neutron leakage decrease are required for obtaining reactor criticality. Effectiveness of the reactor functioning can be increased by the use of additional neutron sources, for example, n‐2n reaction in beryllium framing.
The possibility of additional neutron source development with the use of fast neutrons with an energy distribution close to the fission spectrum in the major part of thermal reactor core is researched in this paper.

Nuclear power plant operating data are characterized by a large variety, strong coupling, and low data value density. When using machine learning techniques for fault diagnosis and other related research, feature selection enables dimensionality reduction while maintaining the physical meaning of the original features, thus improving the computational efficiency and generalization ability of the learning model. In this paper, a correlation-based feature selection algorithm is developed to implement feature selection of nuclear power plant operating data. The proposed algorithm is verified by experiments and compared with traditional correlation-based feature selection algorithms. The experiments and comparison results show that the proposed algorithm is effective in realizing the dimensionality reduction of nuclear power plant operating data.

The spherical fuel elements are adopted in the high-temperature gas-cooled reactor pebble-module (HTR-PM). The fuel elements will be discharged continuously from the reactor core and transported into the fuel transport pipelines during the reactor operation, leading to spatially varying dose outside the pipeline. In this case, the dose evaluation faces two major challenges, including dynamic source terms and pipelines with varying lengths and shapes. This study tries to handle these challenges for HTR-PM through comprehensive calculations using the QAD-CGA program and to design the corresponding shielding of the pipeline. During the calculation, it is assumed that a spherical fuel element stays in different positions of the pipelines in turn, and the corresponding dose contributions were calculated. By integrating the dose contributions at different positions, the dose at the points of interest can be obtained. The total dose is further determined according to the assumed fuel elements transport speed of 5 m/s and total 6000 fuel elements transportation per day. Two types of fuel transport pipelines and two source terms were considered, i.e., the spent fuel element transport pipelines with corresponding spent fuel source term and the different burn-up fuel element transport pipelines with the average burn-up fuel source term. Doses at different points of interest were calculated with no shielding scenario and with lead shielding of different thicknesses scenario. To evaluate the shielding effect, the dose limit of the orange radiation zone of HTR-PM and the radiation damage thresholds from NCRP report No.51 were both adopted. The calculated results show that, for pipelines that transport the spent fuel, a 4 cm lead shielding will be enough. And for pipelines that transport fuel elements with different burn-up, a 5 cm lead shielding will be added. The method and results can provide valuable reference for other work of HTR-PM.