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Volume 46 Issue 5
Oct.  2025
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Sun Niujia, Zhang Heng, Hang Qin, Wang Wencong, Liu Caixue, Zhang Peilai, Li Jiayi, Wang Xiangfan. Experimental Study of Bubble Distribution Characteristics in a 10×10 Rod Bundle Subchannel Based on Mask R-CNN[J]. Nuclear Power Engineering, 2025, 46(5): 243-248. doi: 10.13832/j.jnpe.2024.090054
Citation: Sun Niujia, Zhang Heng, Hang Qin, Wang Wencong, Liu Caixue, Zhang Peilai, Li Jiayi, Wang Xiangfan. Experimental Study of Bubble Distribution Characteristics in a 10×10 Rod Bundle Subchannel Based on Mask R-CNN[J]. Nuclear Power Engineering, 2025, 46(5): 243-248. doi: 10.13832/j.jnpe.2024.090054

Experimental Study of Bubble Distribution Characteristics in a 10×10 Rod Bundle Subchannel Based on Mask R-CNN

doi: 10.13832/j.jnpe.2024.090054
  • Received Date: 2024-09-14
  • Rev Recd Date: 2025-03-06
  • Available Online: 2025-10-15
  • Publish Date: 2025-10-15
  • The rod bundle structure is widely used in critical equipment such as reactor cores and steam generators, and the geometric and physical parameters of the bubbles in their subchannels play a crucial role in the numerical prediction of mass transfer and heat transfer processes. This paper conducts an experimental study on the air-water two-phase flow behavior in the subchannels of a 10×10 rod bundle, using high-speed imaging combined with Mask R-CNN to investigate the effects of gas flow rate and nozzle diameter at different heights on bubble size, shape, and void fraction. The results show that under the constraint of narrow gaps, approximately 45% of the bubbles maintain a stable ellipsoidal shape. When the nozzle diameter reaches 0.3 mm, about 30% of the bubbles undergo significant deformation. Due to the limited gap space, the bubble diameter peaks around 2 mm, but as the gas flow rate and nozzle diameter increase, the bubble generation frequency rises, and the void fraction increases accordingly. During the bubble ascent, the diameter slightly increases, but the bubble number decreases along the axis, ultimately leading to a reduction in the void fraction.

     

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  • [1]
    刘浩, 张卢腾, 周文雄, 等. 2×2棒束通道内流动沸腾空泡份额分布实验研究[J]. 核动力工程, 2023, 44(6): 104-110. doi: 10.13832/j.jnpe.2023.06.0104.
    [2]
    郭涌辉. 小隙径比反应堆棒束通道内间隙涡街流场特性数值研究[D]. 哈尔滨: 哈尔滨工程大学, 2022.
    [3]
    WANG W C, LIU C X, HUANG L Y. The first application of modified neutron source multiplication method in subcriticality monitoring based on Monte Carlo[J]. Nuclear Engineering and Technology, 2020, 52(3): 477-484. doi: 10.1016/j.net.2019.08.014
    [4]
    WANG W C, HUANG L Y, LIU C X, et al. First application of large reactivity measurement through rod drop based on three-dimensional space–time dynamics[J]. Nuclear Science and Techniques, 2021, 32(2): 13. doi: 10.1007/s41365-021-00856-4
    [5]
    WEN D Z, CHEN W G, YIN J L, et al. Overlapping bubble detection and tracking method based on convolutional Neural network and Kalman Filter[J]. Chemical Engineering Science, 2022, 263: 118059. doi: 10.1016/j.ces.2022.118059
    [6]
    张恒, 吕雪, 李华, 等. 用于等离子体三维重建的光场反卷积方法[J]. 光学学报, 2023, 43(7): 0715001. doi: 10.3788/AOS221789
    [7]
    张恒, 吕雪, 刘东, 等. 核电人工智能应用: 现状、挑战和机遇[J]. 核动力工程, 2023, 44(1): 1-8. doi: 10.13832/j.jnpe.2023.01.0001
    [8]
    SOIBAM J, SCHEIFF V, ASLANIDOU I, et al. Application of deep learning for segmentation of bubble dynamics in subcooled boiling[J]. International Journal of Multiphase Flow, 2023, 169: 104589. doi: 10.1016/j.ijmultiphaseflow.2023.104589
    [9]
    ZHOU W, MIWA S, TSUJIMURA R, et al. Bubble feature extraction in subcooled flow boiling using AI-based object detection and tracking techniques[J]. International Journal of Heat and Mass Transfer, 2024, 222: 125188. doi: 10.1016/j.ijheatmasstransfer.2024.125188
    [10]
    CUI Y Z, LI C X, ZHANG W L, et al. A deep learning-based image processing method for bubble detection, segmentation, and shape reconstruction in high gas holdup sub-millimeter bubbly flows[J]. Chemical Engineering Journal, 2022, 449: 137859. doi: 10.1016/j.cej.2022.137859
    [11]
    YAN H J, ZHANG H Y, LIU L, et al. Effect of gas flow rate and nozzle diameter on bubble size and shape distributions in bubble column[J]. Transactions of Nonferrous Metals Society of China, 2024, 34(5): 1710-1720. doi: 10.1016/S1003-6326(24)66501-5
    [12]
    KURIMOTO R, NEUMEISTER R F, KOMINE R, et al. Shapes and terminal velocities of single bubbles rising through fiber bundle in stagnant water[J]. Chemical Engineering Science, 2024, 299: 120557. doi: 10.1016/j.ces.2024.120557
    [13]
    WANG K, JUNYA I, LI C Y, et al. Invariant aluminum CHF under electron beam irradiation conditions for downward-facing flow boiling[J]. Applied Thermal Engineering, 2023, 220: 119810. doi: 10.1016/j.applthermaleng.2022.119810
    [14]
    HE K M, GKIOXARI G, DOLLÁR P, et al. Mask R-CNN[C]//Proceedings of 2017 IEEE International Conference on Computer Vision. Venice: IEEE, 2017: 2980-2988.
    [15]
    杨程. 图像分析技术用于液相中气泡群粒径分布的检测[D]. 南京: 南京大学, 2015.
    [16]
    谭万尧, 刘晓晶, 吴德操, 等. 基于激光截面成像法的气液两相流气泡群特征测量[J]. 光学学报, 2022, 42(15): 1510001. doi: 10.3788/AOS202242.1510001
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