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Assessment of the three-dimensional flow field in the reactor pressure vessel in Hualong One nuclear power plants

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This study uses computational fluid dynamics (CFD) to investigate the three-dimensional flow field under normal operating conditions in the reactor pressure vessel (RPV) in the Hualong One nuclear power plants (NPPs). With a particular focus on the flowrate distribution at the core inlet, the numerical framework is validated against the integral hydraulic experiment in a 1:4-scaled RPV of CNP1000, the prototype of the Hualong One reactor. The simulation results of the normalized flowrate at the core inlet agree reasonably well with the measured data. Based on the experimental data, several methods of calibrating the CFD turbulence model coefficients are suggested by introducing the concepts of data assimilation and machine learning. The flow field in a realistic RPV for Hualong One is predicted using the validated numerical framework, showing that the flowrate distribution at the core inlet is nearly homogeneous and that the turbulent intensity is acceptably low for each fuel assembly. It can provide essential information for the reactor core thermal–hydraulic design and the fuel assembly mechanical assessment.
Title: Assessment of the three-dimensional flow field in the reactor pressure vessel in Hualong One nuclear power plants
Description:
This study uses computational fluid dynamics (CFD) to investigate the three-dimensional flow field under normal operating conditions in the reactor pressure vessel (RPV) in the Hualong One nuclear power plants (NPPs).
With a particular focus on the flowrate distribution at the core inlet, the numerical framework is validated against the integral hydraulic experiment in a 1:4-scaled RPV of CNP1000, the prototype of the Hualong One reactor.
The simulation results of the normalized flowrate at the core inlet agree reasonably well with the measured data.
Based on the experimental data, several methods of calibrating the CFD turbulence model coefficients are suggested by introducing the concepts of data assimilation and machine learning.
The flow field in a realistic RPV for Hualong One is predicted using the validated numerical framework, showing that the flowrate distribution at the core inlet is nearly homogeneous and that the turbulent intensity is acceptably low for each fuel assembly.
It can provide essential information for the reactor core thermal–hydraulic design and the fuel assembly mechanical assessment.

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