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Particle tracking, computational fluid dynamics

Fig. 1 0.11 Predicted particle tracks through multiple revolutions of a Triflat tool from a two-dimensional computational fluid dynamics model. The cumulative number of revolutions (n) in each case is indicated. Adapted from Ref 47... Fig. 1 0.11 Predicted particle tracks through multiple revolutions of a Triflat tool from a two-dimensional computational fluid dynamics model. The cumulative number of revolutions (n) in each case is indicated. Adapted from Ref 47...
Fig. 3.1.4. Particle tracks in a cyclone by computational fluid dynamics. The swirl components are not shown. On the left 10 tracks are calculated from the mean flow field on the right 5 particle tracks are shown where the response to the turbulent motion of the gas is taken into account. Conditions cyclone diameter 20 cm, gas inlet velocity 15 m/s, gas at SATP ( standard ambient temperature and pressure , 25 C and 1 atm), particle density 2730 kg/m ... Fig. 3.1.4. Particle tracks in a cyclone by computational fluid dynamics. The swirl components are not shown. On the left 10 tracks are calculated from the mean flow field on the right 5 particle tracks are shown where the response to the turbulent motion of the gas is taken into account. Conditions cyclone diameter 20 cm, gas inlet velocity 15 m/s, gas at SATP ( standard ambient temperature and pressure , 25 C and 1 atm), particle density 2730 kg/m ...
Our understanding of the hydrodynamics of multiphase flows has progressed substantially in the recent three decades, thanks to the development of advanced experimental techniques, particularly laser Doppler anemometry (LDA), particle image velocimetry (PIV), computer-automated radioactive particle tracking (CARPT), and optical bubble probes. In addition, computational fluid dynamics (CFD) simulations allow for inner views in two-phase process equipment. [Pg.284]


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See also in sourсe #XX -- [ Pg.1054 , Pg.1055 ]




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