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A hybrid particle image velocimetry (PIV) method is employed to measure the flow and create a dense velocity vector map of a region of interest.
For 3-dimensional hypersonic flows, like in re-entry problems, this induces much too dense velocity grids that cannot be practically used, for memory storage requirements.
This paper proposes a new motion estimation algorithm that is designed for assessing the dense velocity fields of soft tissue motion in a sequence of ultrasonic B-mode images.
Flow map at the pixel resolution; wherein, a dense velocity field (one velocity vector per pixel) is generated.
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On a second step, the time scale of the motion is introduced in the simulated data by means of well-known 2D correlations for the bubble and dense phase velocity.
However, the present work examines and compares not only the bubble hydrodynamics and dense-phase probability within the bed, but also the time-averaged vertical and horizontal component of the dense-phase velocity, the air throughflow and the instantaneous interaction between bubbles and dense-phase.
This discrepancy increases with the height above the distributor of the two-dimensional bed, and it is even larger for the horizontal component of the time-averaged dense-phase velocity.
In other words, the results presented in this work indicate that the fine agreement commonly encountered between simulated and real beds on bubble hydrodynamics is not a sufficient condition to ensure that the dense-phase velocity obtained with two-fluid models is similar to that from experimental measurements on two-dimensional beds.
If the object were to become sufficiently dense, the escape velocity could therefore exceed the speed of light, and light itself would be unable to escape.
The results are presented as dynamic cartography and dense fields of velocity vectors.
Furthermore, gas flow balance calculations show that the ratio of dense phase superficial gas velocity to minimum fluidization velocity increases with both increasing pressure and excess gas velocity.
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