2013
DOI: 10.1080/00223131.2013.862189
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Void distribution and bubble motion in bubbly flows in a 4×4 rod bundle. Part I: Experiments

Abstract: Lack of local void fraction data in a rod bundle makes it difficult to validate a numerical method for predicting gas-liquid two-phase flow in the bundle. Distributions of local void fraction and bubble velocity in each subchannel in a 4 × 4 rod bundle were, therefore, measured using a double-sensor conductivity probe. Liquid velocity in the subchannel was also measured using laser Doppler velocimetry (LDV) to obtain relative velocity between bubbles and the liquid phase. The size and pitch of rods were 10 and… Show more

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Cited by 43 publications
(34 citation statements)
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“…This drag model was applied to single bubbles rising through stagnant water in a two by two rod bundle, and the estimation agreed well with their experimental data [14]. The velocity reduction in the near wall region observed in our recent experiments [9] might therefore be predicted by making use of this drag model.…”
Section: Introductionmentioning
confidence: 63%
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“…This drag model was applied to single bubbles rising through stagnant water in a two by two rod bundle, and the estimation agreed well with their experimental data [14]. The velocity reduction in the near wall region observed in our recent experiments [9] might therefore be predicted by making use of this drag model.…”
Section: Introductionmentioning
confidence: 63%
“…Fluxes of n G through the boundary between the shaded and white regions are forced to be zero, which ensures that n G = 0 in the white (near wall) region throughout a simulation. Since bubbles near the rod wall were apt to be spherical [9], the minimum distance between the wall and the bubble center is set at d/2. Bubbles in the gap region took distorted prolate shapes and the maximum aspect ratio was 1.35, where the aspect ratio E is the ratio of the maximum vertical dimension to the maximum horizontal dimension of a bubble.…”
Section: Geometrical Restriction On Bubble Motion In N-based Methodsmentioning
confidence: 99%
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