Spacer grids with mixing vanes are generally used in fuel assemblies of Pressurized Water reactor (PWR), because that mixing vanes could enhance the lateral turbulent mixing in subchannels. Thus, heat exchangements ar...
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ISBN:
(纸本)9784890471676
Spacer grids with mixing vanes are generally used in fuel assemblies of Pressurized Water reactor (PWR), because that mixing vanes could enhance the lateral turbulent mixing in subchannels. Thus, heat exchangements are more efficient, and the value of departure from nucleate boiling (DNB) is greatly increased. Actually turbulent mixing is composed of two kinds of flows: swirling flow inside the subchannel and cross flow between subchannels. Swirling flow could induce mixing between hot water near the rod and cold water in the center of the subchannel, and may accelerate deviation of the bubbles from the rod surface. Besides, crossing flow help to mixing water between hot subchannels and cold subchannels, which impact relatively large flow area. As a result, how to accurately capture and how to predict the complicated mixing phenomenon are of great concernments. Recently many experimental studies has been conducted to provide detailed turbulent mixing in rod bundle, among which Laser Doppler Velocimetry method is widely used. With great development of Computational Fluid Dynamics, CFD has been validated as an analysis method for nuclear engineering, especially for single phase calculation. This paper presents the CFD simulation and validation of the turbulent mixing induced by spacer grid with mixing vanes in rod bundles. Experiment data used for validation came from 5 X5 rod bundle test with LDV technology, which is organized by science and technology on reactor system design technology laboratory. A 5 X5 rod bundle with two spacer grids were used. Each rod has dimension of 9.5 mm in outer diameter and distance between rods is 12.6 mm. Two axial bulk velocities were conducted at 3.0 m/s for high Reynolds number and 1.0 m/s for low Reynolds number. Working pressure was 1.0 bar, and temperature was about 25 V. Two different distances from the downstream of the mixing spacer grid and one from upstream were acquired. Mean axial velocities and turbulent intensities (Wrms
For the purpose of figuring out the thermal-hydraulic behaviors during bottom reflooding in the narrow rectangular channel of plate-type fuel reactor, experimental apparatus was established to simulate the bottom refl...
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Thermal characteristics during startup of CSR1000 are directly related to the security of supercritical water reactors. The heat transfer model during power-raising phase is built according to the sliding pressure mod...
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Recently, the advancement of deep learning in discriminative feature learning from 3D LiDAR data has led to rapid development in the field of autonomous driving. However, automated processing uneven, unstructured, noi...
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Stress intensity factors(SIFs) due to thermal-mechanical load has been established by using weight function method. Two reference stress states sere used to determine the coefficients in the weight function. Results w...
Stress intensity factors(SIFs) due to thermal-mechanical load has been established by using weight function method. Two reference stress states sere used to determine the coefficients in the weight function. Results were evaluated by using data from literature and show a good agreement between them. So, the SIFs can be determined quickly using the weight function obtained when cracks subjected to arbitrary loads, and presented method can be used for probabilistic fracture mechanics analysis. A probabilistic methodology considering Monte-Carlo with neural network (MCNN) has been developed. The results indicate that an accurate probabilistic characteristic of the KI can be obtained by using the developed method. The probability of failure increases with the increasing of loads, and the relationship between is nonlinear.
An overview of the applications of deep learning in ophthalmic diagnosis using retinal fundus images is presented. We also review various retinal image datasets that can be used for deep learning purposes. Application...
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In this paper, Eulerian two-fluid model coupled with extended wall boiling model is used to simulate the subcooled boiling flow in PSBT subchannel test. Improved sub-models are used to describe the heat flux distribut...
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