CFD Simulation of Heat Transfer in Fluidized Bed Reactor.

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CFD Simulation of Heat Transfer in Fluidized Bed Reactor

I Nyoman Suprapta Winaya

1, a

_{, I Made Agus Putrawan}

2,b

_,

I Nyoman Gede Sujana

2

_{, Made Sucipta}

4,c

1,4_{Mechanical Engineering Department, Udayana University, Bali-Indonesia} 2,3_{Magister Program of Mechanical Engineering, Udayana University, Bali-Indonesia} a_{ins.winaya@me.unud.ac.id,}b_{agus_ft_unud@yahoo.co.id,}c_{m.sucipta@me.unud.ac.id}

Keywords: CFD, heat transfer, fluidized bed, Syamlal-O’Brein drag coefficient, Eulerian

Abstract

This study aims to predict heat transfer from a heated bed in a gas fluidized bed using Syamlal-O’Brien drag coefficient. Discrete particles model with the Navier-Stokes equation and Eulerian multiphase are used to approach heat transfer simulation. Coefficient of heat transfer which is related to Nusselt Number and volume fraction are calculated using Gunn model which was compiled from C++_{program language. The effect of fluidization velocity variation on the heat} transfer coefficient comes to the fore, indicating the heat transfer and solid volume fraction at the bed height are very dependent. Contour of solid volume fraction and temperature distribution are also presented.

Introduction

Fluidization is defined as the contacting techniques through which fine solids are transformed into a fluid using either gas or liquid. In fluidization contact between the gas and solid particle occurs appropriately because its wide range of contact surface. Using wastes as a fuel in fluidized bed system needs a deep understanding on fluidization phenomena. In this study, a Fluent Computational Fluid Dynamics (CFD) program was applied to simulate fluid flow that is expected to provide information about the feasibility of the utilization of solid waste as a fuel

Simulation of CFD has been widely developed recently, and it is one of the popular tools used in simulating the fluidization [1]. The program could provide the flexibility to change the design parameters without much cost, providing faster time of the trial, and also able to provide a detailed information about the flow field especially in the area of measurement which is difficult or impossible to obtain [2]. Armstrong and Luo [3] developed a model approach Syamlal-O'Brien drag coefficient which showed more local fluctuations on the basis of particle terminal velocity with slight sensitivity to the microscopic scale. Tasirin, et al. [4] conducted an experimental study as well as modeling and it was found for a higher in gas velocity the fluidization process could be improved. Fluidization behavior involves three important phases namely: the particle-dominated, predominantly gas and a mixture of both.

CFD Model

Eulerian model in Fluent program is an important tool to study the solid particulate phase which involves the complex inter-phase momentum. Therefore, it is important to use the correct drag law to predict the early onset of fluidization occurred. Syamlal O’Brien model has been successfully applied to predict hydrodynamic phenomena on fluidized bed compares to the experimental data. The kinetic theory of granular flow (KTGF) applied with a two-fluid Eulerian-Eulerian model carried out to heat transfer mechanism due to complexity problem from multiphase flow. Standard-setting Syamlal O'Brien is as follows [5]:

Applied Mechanics and Materials Vol. 493 (2014) pp 267-272 © (2014) Trans Tech Publications, Switzerland

doi:10.4028/www.scientific.net/AMM.493.267

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=3₄

, , − 1

Where Ksg, α, Res , CD, vs, vg and vr,s are the momentum exchange coefficient between solid and gas phase, volume fraction, Reynold number of solid phase, drag coefficient, velocity of solid and gas, the coefficient of terminal velocity for the solid phase respectively.

In the gas phase, Eulerian model is treated as a continuum, which can be described by a set of volume average Navier-Stokes equations. For global mass balance is in the form of conservative as:

+ ∇. = 0 2

Where , and is the fraction of each space, the density of the gas, and the gas phase velocity respectively. Thus, balance equation for the individual in the gas phase can be written as follows:

+ ∇. = . + . (3)

Here Yα is a mass fraction in the gas phase, . , is the net production rate due to gas-phase reactions. Gas-phase momentum equation is written as follows:

+ ∇. + ∇ + ∇. + = (4)

+ ∇. + + ∇. = (5)

Where; p, ,g, e, and Igs are indicated as pressure, voltage, gravity, energy, energy rate and momentum exchange term between the gas phase and particulate phases respectively.

In this study, the heat transfer is determined only in the zone of solid concentration. The heat energy transfer is simplified as the two difference temperatures of gas-solid phase as Eq. 6. The heat transfer coefficient with related to Nusselt Number and volume fraction from both phase is calculated using Eq. 7.

, = ℎ − (6)

ℎ =6 7 Where; qs,g, Kg, Tg , Ts , dp, Nus, , are indicated as heat flux, gas thermal conductivity, temperature each phase, diameter particles, Nusselt number and volume fraction of gas-solids respectively. Hence, the Nusselt number is calculated using Gunn model as follows [6]:

= 7 − 10 g+ 5 g . 1 + 0.7 . 8 Where; Res and Pr are indicated as Reynold and Prandtl number respectively.

Numerical Set-Up and Grid Study

In order to reduce the computation time, the reactor system is designed as 5.08 cm and 70 cm for diameter and height of reactor respectively with static bed height of 10 cm as seen in Fig. 1. Air fluidization velocity is varied at 0.05, 0.09 and 0.13 cm/s with waste particle size of 0.03 cm.

The next entry on the stage is determining boundary conditions of the reactor section which is divided as: the bottom is assumed as velocity inlet of the gas (side entrance), wall on each side and pressure side outlet is assumed as side exit, and conditioning circumstances in the face is the fluid mesh. For the initial condition, it is assumed to be adiabatic wall in which the gas phase is not going to

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slip along the wall while allowing for the solid phase of contact that refers to the Syamlal-O’Brien drag coefficient. Eulerian granular iteration process is used for the gas phase and dense granules in modeling of fluidized bed volume fraction. This model allows the processing issues in two different phases of the volume control in the grid. Granular phase is assumed to have a uniform diameter and solid-gas phase is completed individually with the mass and momentum equations (Eq. no. 3).

Simulation of heat transfer is carried out in Two-Dimension (2D) grid model and analyzed using a model of Eulerian multiphase. Computation domain 2D discretized using rectangular cells (Quad) with mesh total size of 0.41 and 0.29 cm for vertical and horizontal side respectively, and terminated in steps of 0.005 s with 2000 iterations. The program can replace the partial differential equations of continuity, momentum, and energy with algebraic equations which is an approximation of the original continuum problem into a particle discrete model.

The process of selection menu which include the equation solver can be used to complete the calculation in the simulation process. However, in some special case containing custom equations such as heat transfer model is not included in the program. Heat transfer analysis on the fluidized bed system simulation is affected by initial parameters such as material properties, flow rate, operating temperature, density and the flow multiphase model equations. Hence, the C++ language program is used to compile the mechanistic heat transfer model (eq. 7) into CFD program. The wall temperature from reactor is set at 300 K (ambient temperature) and the solids phase is conditioned at combustion mode temperature as high as 973 K. The initial determination of the parameters that used in the simulation process can be seen from tables 1 and 2.

Fig. 1. Outline of a typical numerical setup Table 1. Fluent Model using in simulation

Model Settings

Space 2D

Solver time Unsteady

Viscous k epsilon

Wall Treatment Standard Wall Functions Multiphase Model Solid fluid

Entry side Solid wall 70 cm

5.08 cm

Exit side

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Table 2. Parameter properties of gas and waste particles

Gas Properties Unit

g gas velocity 0.05; 0.0 9; 0.13 [cm/s]

g gas density 1.225 [ kg/m3]

g viscosity 1.79x10-5 [kg/m.s]

g gravity acceleration 9.81 [m/s]

P freeboard pressure 1.01 x 105_[Pa]

Particles

hbed height bed static 10 [cm]

dp particle diameter 0.03 [cm]

s particle density 328 [kg/m3]

s Specific heat 2000 [J/kg.K]

s solids conductivity 0.08 [W/m.K]

Result and Discussion

Variations of air velocity flow into the reactor certainly have an important role on the characteristics of bed hydrodynamic. As the velocity increased the gradient of fluidization velocity also increased as shown in the Fig. 2 as the red colour. The domination between solid and gas can be well visualized using CFD simulation.

Fig. 2. Contour of fluidization characteristic for different velocity at 10 s

Fig. 3 shows the contour of temperature along the bed reactor at fluidization velocity of 0.05 m/s at the time step of 0 to 10 s. It was observed the heat flux continuously flowed as the velocity was just started. The degradation of the red colour was found to change as the solid fraction decreased mostly until the maximum bed height of 18 cm. The similar behavior was found for different fluidization velocity in which the higher velocity resulted in longer contour temperature distribution.

0.0 5 m/s 0.09 m/s 0. 13 m/s

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Fig. 3. Contour of temperature distribution at velocity of 5 cm/s from 0 to 10 s

Fig. 4 shows the correlation between volumes of solid fraction to heat transfer coefficient (htc) along reactor bed height after 10 s steps of iteration. It is observed that the initial bed height of 10 cm increases until 18 cm at air velocity of 0.05 m/s (vof) with heat transfer coefficient of 500 - 650 W/m2_{K. It is clearly found that the solid volume fraction has a major effect on heat transfer} coefficient. In this study, the heat transfer coefficient above the bed height was not calculated.

Fig. 4 Volume of solid fraction and heat transfer coefficient at air velocity of 5 cm/s.

A similar behavior was observed when the fluidization velocity was increased. The increased in velocity resulted in an increased the solid expansion of 21 and 30 cm at velocity of 9 and 13 cm/s respectively. The increased in solid volume fraction was found between 0.22 – 0.33. The heat transfer phenomenon tends to follow the behavior of the solid volume fraction and it was found at average of 655 W/m2_{K with the maximum of 710 W/m}2_{K at velocity of 0.13 m/s. Fig. 5 shows that the higher} gas velocity resulted in the higher heat transfer coefficient.

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Fig. 5 Heat transfer coefficient along bed height at different velocity Summary

Discrete particles model with Syamlal_O’Brien drag coefficient was used to predict heat transfer from a heated bed in a 2-D bubbling fluidized bed. The two fluid simulation using energy balance and momentum shows a good value to visualize the phenomenom into the bed. The heat transfer coefficient is closely linked to the solids volume fraction in which the dominance of the particles cause the high heat transfer coefficient. It seems that the mechanistic of Gunn model can be well recommended to use in CFD simulation.

Acknowledgement: This study was kindly supported by Directorate of Higher Education-The Indonesia’s Ministry of Education and Culture through Hibah Desentralisasi Pascasarjana of Udayana University: No. 175.62/UN14.2/PNL.01.03.00/2013

References

[1] S. Kallio, M. Gulden, A. Hermason., Experimental study and CFD Simulation of a 2D Circulating Fluidized Bed. Proceedings of the 20th International Conference on Fluidized Bed Combustion, pp. 818 (2009).

[2] Amit Kumar., CFD Modeling of Gas-Liquid-Solid Fluidized Bed. Department of Chemical Engineering National Institute of Technology Rourkela pp.769, Orissa (2008).

[3] L.M. Armstrong, S. Gu dan K.H. Luo. , Study of Wall-to-Bed Heat Transfer In a Bubling Fluidized Bed Using the Kinetic Theory of Granular flow. International Journal of Heat and Mass Transfer 53, pp. 4949-4959, (2010).

[4] S.M. Tasirin, S.K. Kamarudin dan A.M.A. Hweage, Mixing Behavior of Binary Polymer Particles in Bubbling Fluidized Bed. Journal of Physical Science, Vol. 19 (1), pp. 13–29 (2008). [5] M. Syamlal., D. Gidaspow, Hydrodynamics of ﬂuidization: prediction of wall-to-bed heat transfer coefﬁcients, AIChE J, Vol. 31, pp. 127–135(1985).

[6] D.J. Gunn, Transfer on heat or mass to particles in fixed and fluidized beds, International Journal of Heat and Mass Transfer, Vol. 21, pp. 467-476 (1978).