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Mujumdar (1990) proposed a novel two-dimensional SHS ISD to minimize from the advantages of SHS as a drying medium (discussed elsewhere in this book). Hosseinalipour and Mujumdar (1997) carried out a

funda-include drying of mono-sized particles entrained into one of the opposing jets with SHS as the drying medium. Furthermore, the effects of all key operating pressure for various size particles entering the system at dif-ferent locations within the jet were examined. It was shown that under certain conditions the particles penetrate deep into the opposite stream before being re-entrained into the impingement zone. This phenomenon may repeat itself several times, resulting in longer residence times for the larger particles. The smaller particles follow the streamlines and exit the chamber with shorter residence times.

There are several advantages to a mathematical simulation of the sys-tem when there are numerous parameters affecting the outcome. ISD provides a particularly challenging transport problem for

computa-Wang and Mujumdar, 2007a, 2007b). In view of the fact that no detailed

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Mujumdar, 2007; Tamir, 1994). These are the semicircular configurations (e.g., drying, puffing, and carrying out certain thermally induced

biochem-the problems of scale-up when using round ducts in ISDs and to benefit

verification of various geometrical configurations (Wang et al., 2006;

turbulence measurements are available in the literature for a confined This effect can be attributed to a different flow pattern that results in

flash drying in the pneumatic duct and drying in a swirling stream

dur-mental computational fluid dynamic analysis of the confined opposing jet system for the first time to explore the flow fields in both single- and two-phase particle–gas turbulent flows. A two-two-phase turbulence model was used to predict the turbulent two-phase flow. This study was extended to

parameters (e.g., geometry, flow rate, and steam temperature) as well as

tional fluid dynamics (CFD) simulations but at the same time allows

© 2009 by Taylor & Francis Group, LLC

72 Advanced Drying Technologies

opposing jet system, the model of Hosseinalipour and Mujumdar remains to be validated with data. The results, however, are physically realistic. For numerical details, the reader is referred to the source work (Hosseinalipour, 1997).

Some of the basic conclusions of the simulation work are summarized as follows: The residence time of particles in the ISD decreases with increasing Reynolds number of the jet (stream) but increases with spac-ing between the opposspac-ing nozzles. Particles enterspac-ing closer to the jet mid-plane tend to have longer residence times. Increasing steam temperature yields better drying performance. The effect of operating pressure is quite complex due in part to the highly nonlinear behavior of the system and the effect of pressure on thermophysical properties of steam. The optimum operating pressure for SHS drying of particles in the surface water removal period in the simple opposing jet system model was found residence time for the particles. The existence of optimum pressure is, inherently highly nonlinear nature of the hydrodynamics involved as well as the nonlinearity of temperature dependence of the thermal and physical properties of the carrier medium. This remains a challenging problem for both theoretical and experimental research.

More advanced mathematical models along with careful experimental data are needed to design and analyze ISD systems more reliably. There is a further complication associated with the fact that the entrained particles may agglomerate or disintegrate on collision with other particles. Also, little is known about the collision characteristics of wet particles, which must depend on their moisture content, as well.

Symbols

C Heat capacity, J/kg K d Particle diameter, m D Duct diameter, m F Force, N

g Acceleration due to gravity, m/s²

h ²

H Distance between accelerating ducts, m k Thermal conductivity, W/m K

L Dimensionless distance

∆P Pressure drop, Pa t Time, s

T Temperature, K (°C) u Velocity, m/s x Coordinate, m

X Moisture content, kg/kg (% w.b.)

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to be 202 kPa, which gave a higher heat-transfer coefficient and longer however, very difficult to explain in simple physical terms due to the

Heat-transfer coefficient, W/m K

© 2009 by Taylor & Francis Group, LLC

Greek Symbols

β Volumetric concentration of solids, m³/m³ μ Dynamic viscosity, kg/m s

ν Kinematic viscosity, m²/s ρ Mass density, kg/m³ ζ Friction factor Subscripts cr Critical

g Gas

p Particle (droplet) s Solid (suspension) t Terminal

max Maximum

0

1 Inlet

2 Outlet Superscripts

* Dimensionless parameter Dimensionless Numbers

Eu = ∆P/(u²ρ)ρρ Euler number Gu = (T – TTT )/Tp Gukhman number Nu = hdp/k Nusselt number Pr = cμ/k Prandtl number Re = u0D/ν Reynolds number

Re_p= u0d_p/ν Particle Reynolds number

Re_r= (u ± up)d_p/ν Reynolds number (based on relative velocity) Re_t = utd_p/ν Reynolds number (based on terminal velocity)

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