Band 87, Heft 6

The paper presents a Computational Fluid Dynamics (CFD) methodology to model gas-liquid boiling flow in a full scale 5 × 5 rod bundle with spacer grid typical in Pressurized Water Reactor (PWR) fuel rod bundle. The CFD modeling method is developed based on the STAR-CCM+ CFD code, including the Eulerian-Eulerian two-fluid model and the improved wall heat partitioning model. The OECD/NRC PWR Sub-channel and Bundle Tests (PSBT) are used as a numerical benchmark to assess the simulation quantitatively. The simulated geometry is a full scale of 5 × 5 fuel rod bundle with 17 spacers, including 7 mixing vane spacers (MV), 8 simple spacers (SS) and 2 non-mixing vane spacers (NMV). The present simulated results are in good agreement with the experimental results, the average error of the simulated cross-section void fraction is less than 20%. Based on the simulations, the axial distributions of second flow intensity, the rod surface temperature, bulk fluid temperature, and the void fraction are discussed. The results show that the spacer grid structures, especially the mixing vane, play an essential part in spreading the bubbles, reducing the void fraction and the rod surface temperature.

This study looks for innovative methods to improve the overall performance of the U-20% Zr metallic fuel. The first solution is to swap out the helium gap for a ternary liquid metal bonded gap while the second involves minimizing the helium gap’s thickness to 0.04 mm in order to minimize its thermal resistance. The proposed solutions have been subjected to neutronic, thermal-hydraulic, and solid structure investigations, and their performance has been contrasted with that of a typical U-20% Zr metallic alloy with a 0.08 mm He-gap. According to neutronic analysis, the investigated fuel materials have almost identical neutronic performance. After using the LM bonded gap, both thermal-hydraulic and solid structure performance improved significantly. The performance of the U-20% Zr with 0.04 mm He-gap was moderate and unattractive to be used since it was deduced that its drawbacks outweighed its benefits.

The nuclear power industry is developing rapidly toward intelligence and scale, the digital twin was combined with the industrial interconnection technology to solve the key problems in the application of the digital twin, such as the three-dimensional model presentation, real-time data docking, and the improvement of intelligence degree. Based on the example of Thorium Molten Salt Reactor-Solid Fuel (TMSR-SF0). Firstly, the three-dimensional twin of nuclear power equipment is constructed and the real-time update of twin data is realized based on the Node-EPICS event driver and Websocket communication protocol; Then, the communication interface with MySQL database is developed to realize the storage and management of data; Finally, the PID control system of molten salt circuit pipeline is integrated with back propagation neural network algorithm, and the efficiency and precision of temperature control system are improved by self-modification of weight. The results show that this system has the functions of three-dimensional display, network communication, data storage, and parameter optimization, and the data update cycle is raised to 100 ms, which can provide a certain reference value for the digital transformation of the nuclear monitoring field.

UPFC device is discussed in this paper along with their models and functions. Moreover, the suggested and the complementally approaches in the current research study. As a result, the methods are divided into three divisions, which are sensitivity analysis based methods, conventional optimization based methods and artificial intelligence (AI) based methods. In addition, artificial intelligence based methods plays a major role in reducing the search space region. However, to optimize the resulting benefits, the placement, sizing and parameter of UPFC device should be determined. This paper presents and discusses in depth an overall review of the last two decades’ studies, including proposed and comparative methods and strategies, approaches, objective functions, UPFC device tools utilized, limitations, contingency situations and all parameters evaluated and simulated. This paper also provides an analysis of UPFC’s various benefits and uses of power flow studies, such as, power loss mitigation, system load ability improvement, power system security, enhancement of voltage stability, cost of generation and UPFC installation and utilizing specific optimization techniques. Therefore, a more weighted overview of the proposed method is presented focused on artificial intelligence optimization methods.

The pressurizer system of pressurized water reactor (PWR) maintains the reactor coolant system pressure during steady-state operation and limits pressure changes during transients. The in/out surge transients will cause pressure variations and they are controlled by either the spray system or the heater system. The spray system is actuated when the pressure exceeds a preset value. The heater system is initiated when the pressure falls below a preset value. The fundamental understanding and a reliable modeling of the pressurizer system behavior under steady state and transient conditions are needed to simulate overall nuclear power plant behavior. In the present study, an algorithm using Python 3.7 is developed to represent the dynamic behavior of the pressurizer system under steady-state and during in/out surge transients. Moreover, RELAP5 code is used to simulate the pressurizer system during the prescribed transients. The analysis and assessment results demonstrate satisfactory control performance during the in/out surge transients that guarantee the safety of PWR during operation. Also, the comparison between Python algorithm and RELAP5 model illustrates the capability and effectiveness of the Python algorithm for dynamic simulation and control.

The dependently of the electrical grid is critical key point to safety of the nuclear research reactor (NRR) operation. This paper provides an optimization approach relying on optimal allocation of UPFC device to obtain higher electrical power quality of such nuclear facilities. The particle swarm optimization (PSO) technique was used to address the optimal UPFC allocation problem. The suggested approach is applied to the IEEE 33-bus test system, and results reveal that the suggested PSO is more efficient in minimizing total power losses and enhancing voltage profile using only one of UPFC device. The results show the technique is good method in this case.