With the development of GEN-IV nuclear reactor technology, the supercritical carbon dioxide (SCO₂) Brayton cycle has attracted wide attention for its simple structure and high efficiency. Correspondingly, a series of research has been carried out to study the characteristics of the cycle. The control flexibility of the power generation system has rarely been studied. This paper carried out a dynamic performance of the 20 MW-SCO₂ recompression cycle based on the Simulink software. In the simulation, the response characteristics of the system main parameters under the disturbances of cooling water temperature, split ratio, main compressor inlet temperature and pressure were analyzed. The results show that the turbine inlet temperature is most affected by the disturbances, with a re-stabilization time of 2500–3000 s. According to the response characteristics of the system after being disturbed, this study proposed a stable operation control scheme. The scheme is coordinated with the main compressor inlet temperature and pressure control, recompressor outlet pressure control, turbine inlet temperature control and turbine load control. Finally, the control strategy is verified with the disturbance of reduced split ratio, and the results show that the control effect is good.

The supercritical carbon dioxide (SCO₂) Brayton cycle, as a substitute for the steam cycle, can be widely used in a variety of power generation scenarios. However, most of the existing SCO₂ cycle studies are restricted to basic thermodynamics research, parameter optimizations, system design in different application fields, and even economic analysis. Considering the load variability and control flexibility of the power generation system, the dynamic performance research of the SCO₂ cycle is also crucial, but the work done is still limited. Based on the previous studies, Simulink software is used in this paper to develop a dynamic model of the 20 MW-SCO₂ recompression cycle, which specifically includes component models that can independently realize physical functions and an overall closed-loop cycle model. A series of comparative calculation are carried out to verify the models and the results are very positive. The SCO₂ recompression power system is built with the developed models and the dynamic model runs stably with a maximum error of 0.56%. Finally, the simulation of the dynamic switching conditions of the 20 MW-SCO₂ recompression cycle are performed and the analysis results supply instructive suggestions for the system operation and control.

The lead Anode (LBE) cooling ADS core is taken as the research object, and the ADS core axial one-dimensional physical thermal coupling model is established. The deterministic method is used to calculate the subcritical flux neutron flux distribution based on Monte Carlo. The method calculates the accelerator beam and the external neutron source generated by the spallation target. The ADS core thermal hydraulic analysis is carried out by a single-channel model, and the fuel elements are respectively divided into nodes in the axial direction and the radial direction, and the influence of thermal feedback on the neutronics characteristics of the subcritical core is considered. The one-dimensional physical thermal coupling model established in this paper can accurately calculate the spatial distribution of key parameters such as neutron flux density, fuel and cladding temperature in ADS core.

In marine nuclear power plants based on molten salt reactors, the complexity of core nuclear reactions, fuel fluidity, and the “false” water level characteristics of the steam generator water level make it unrealistic to establish an accurate mathematical model, so it is difficult to implement traditional PID control methods. This has increased substantially. The fuzzy control has a good solution to this feature. Therefore, combined with the fuzzy control that does not depend on the precise mathematical model of the controlled object, the fuzzy controller of the nuclear power plant is designed, and the control research of the core power is obtained respectively through MATLAB/Simulink simulation. It shows that the designed fuzzy controller can achieve good control of nuclear power plants.