MRCNN: Multi-input residual convolution neural network for three-dimensional reconstruction of bubble flows from light field images
Accurate measurement of bubbles in air-water two-phase flows holds immense significance in the realm of thermal hydraulics assessments within nuclear reactors. Nevertheless, conventional bubble measurement techniques grapple with challenges encompassing system intricacy, limited real-time capabiliti...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
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Series: | Nuclear Engineering and Technology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573324004595 |
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