Particle migration at solid surfaces and heat transfer in bubbling fluidized beds—I. Particle migration measurement systems

Molerus, O.; Burschka, A.; Dietz, Severine

doi:10.1016/0009-2509(94)00445-w

Cited by 42 publications

(26 citation statements)

References 4 publications

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“…The particle size is a very important parameter influencing the wall‐to‐bed heat transfer. The experimentally observed decrease in the heat‐transfer coefficient for larger particles is predicted very well by the model that accounts for the local porosity profile near the wall (see Figure 13a) and agrees with the findings of many researchers 23. For the fluidized bed with larger particles the thickness of the gas film between the first layer of particles and the heated wall is larger, as schematically depicted in Figure 13b, which increases the resistance of the wall‐to‐bed heat transfer.…”

Section: Computational Resultssupporting

confidence: 90%

Wall‐to‐bed heat transfer in gas–solid bubbling fluidized beds

et al. 2005

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Section: Computational Resultssupporting

confidence: 90%

Wall‐to‐bed heat transfer in gas–solid bubbling fluidized beds

et al. 2005

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“…However, particles do not accommodate perfectly against a wall and some of them do not actually touch the wall (for fixed beds this can be readily observed through transparent vessels). Also, the mobility showed by particles adjacent to surfaces in bubbling fluidized beds (as reported by Makhorin et al, 1978;and Molerus et al, 1995) can produce transient detachment. Therefore, there are reasons to believe that an average separation gap may exist.…”

Section: Introductionmentioning

confidence: 82%

“…Admitting that a relatively loose packing takes place in the first layer of particles, and considering that visual observation reveals that particles in contact to immersed surface are mobile (see Makhorin et al, 1978;and Molerus et al, 1995), it is also certainly possible that particles have the chance to detach temporarily from the wall, modifying the average value of the parameter to'…”

Section: Evaluation Of Parameters From Experiments In Freely Bubblingmentioning

confidence: 97%

Evaluation of Conductive Heat Transfer Mechanisms Between an Immersed Surface and the Adjacent Layer of Particles in Bubbling Fluidized Beds

Mazza¹,

Mariani²,

Barreto³

1997

Chemical Engineering Communications

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The evaluation of the heat transfer coefficient h w p between a heat exchanging surface immersed in a gas fluidized bed and the adjacent layer of dense phase particles is analyzed in this contribution. Gas convective and radiant effects are not included in the present analysis.The inclusion of h w p , or an equivalent formation, in mechanistic models describing heat transfer has been necessary because the sudden voidage variation close to the immersed wall restrains significantly the heat transfer rate. However, there is not at present a widely accepted expression to evaluate hwp'A precise formulation for h w p accounting for transient conduction inside .spherical particles, the Smoluchowski effect, the concentration of particles in the adjacent layer (N p) and an effective separation gap (to) is developed here.Although N p can be estimated, in principle, from experimental evidence in packed beds, and it is reasonably expected that to = 0, the analysis of experimental heat transfer rates in moving beds, packed beds, and bubbling fluidized beds indicate that values of h w p are, in general, smaller than expected from these assumptions. Appropriate values of to and N p are then estimated by fitting the experimental data. The probable effect of surface asperities is also discussed by analyzing a simplified geometrical model. It is concluded that the parameter to can be also effective to account for particle roughness, independently of thermal properties.

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“…Usually, for heat transfer estimations, the parameters that more directly reflect the peculiarity of this bed structure are the surface renewal frequency [2,9,[15][16][17][18][19] and the void fraction near the exchange surface [3,9,12,13,16]. These parameters can be estimated by direct methods, as optical investigations [12][13][14][15] and Positron Emission Particle Tracking (P.E.P.T.) techniques [2], or indirect ones, such as numerical simulations [3,[16][17], abrasion [18] or heat transfer [9,20] measurements.…”

Section: Introductionmentioning

confidence: 99%