Modeling Of Rice Husks Gasification In A Fluidized Bed Reactor

Modeling Of Rice Husks Gasification In A Fluidized Bed Reactor

P. L. Mtui

College of Engineering and Technology, University of Dar es Salaam

P. O. Box 35131, Dar es Salaam, Tanzania

Abstract

Gasification of biomass has increasingly become a promising alternative to direct combustion. The paper presents a study where rice husks were gasified in a fluidized bed using air to determine gas yield and composition as a function of equivalence ratio. Mathematical modeling of the gasification process is based on the computational fluid dynamics (CFD) technique where the conservative transport equations were modeled in a fluidized

for gasification and combustion of rice husks.

The model results compared well with published experimental data, therefore indicating that the model can be a useful tool for the prediction of performance variables of fluidized bed reactor for rice husks gasification process.

Key Words: biomass, gasification, hydrodynamics, kinetics, fluidization, rice

husks, modeling.

reactor coupled with the kinetic equations

1. Introduction

   The environmental concerns towards the use of fossil fuels increasingly drive interest in the biomass gasification process as biomass is a potential source of renewable energy. However, biomass is not presently competitive with fossil fuels. Fossil fuel contributes to the major portion of worlds total energy consumption. According to the As mentioned by Xiong et al [3], the World Energy Assessment Report, says that 80% of the worlds primary energy consumption is contributed by fossil fuel while 14% by renewable sources (out of which biomass contributes 9.5%). This implies that future sustainable energy scenario requires a combination of factors such as renewable resources and advanced energy technology. Traditionally, biomass is used as energy source of energy for cooking and heating particularly in the developing countries. Biomass gasification systems are of prime importance as modern technologies. Among all biomass conversion processes,

   gasification is one of the promising ones. This is particularly so because the energy efficiency in case of gasification is higher than that of combustion by David Ross [1] and Fryda [4].

   The gasification process is defined as a thermo chemical conversion of carbonaceous material under reducing atmosphere to produce combustible gases frequently know as syngas which is a mixture mainly of CO and H2. In a gasifier reactor, the carbonaceous material undergoes gasification process at a controlled oxygen and temperature.

   Fluidized beds reactors are widely used type gasifier reactor for biomass gasification as they offer a number of advantages such as high heat transfer rates, good temperature control and ability to handle a wide variation of feed materials. A fluidized bed is a packed bed through which fluid flows at such a high velocity that the bed is loosened and the particle-fluid mixture behaves as though it is a fluid. Thus, when a bed of

   particles is fluidized, the entire bed can be transported like a fluid, if desired. Both gas and liquid flows can be used to fluidize a bed of particles.

2. Model Description

   The 40 kg/hr rice husks gasifier reactor is shown in Figure 1 whose diameter and height are 0.3m and 5m, respectively. Air flows through a porous plate at the bottom

   of the reactor at a velocity of 0.5 m/s. Rice husks are injected at the sand bed which has been previously fluidized. Momentum is transferred from the bubbling bed to the rice husks biomass particle as well as from the formed bubbles inside the bed. For the design calculations, the physical properties of the rice husk and the inert material (sand) composing the bed were determined. The pertinent process data appear is shown in Table 1.

   .

   Figure 1: Fluidized bed gasifier reactor

   Table 1: Major specifications for fluidized bed rice husks gasifier

   Object	Parameter	Unit
   Reactor	Height (m)	5.0
   	Diameter (m)	0.3
   	Wall material thickness (mm)
   Rice husks
   	Mass flow rate (kg/hr)	40
   	Feed material density (kg/m3)	389
   	Porosity	0.64
   	Particle size (m)	856
   	Thermal conductivity (W/m-K)	0.15
   	Specific heat (kJ/kg-K)	2.5

   Fluidization
   	Sand thermal conductivity (W/m-K)	0.25
   	Sand density (kg/m3)	2650
   	Sand particle size (m)	385
   	Bed porosity	0.46
   	Fluidization air velocity (m/s)	0.5
   	Air temperature (C)	297
   Proximate Analysis	Moisture (%wt)	9.3
   	Volatile matter (%wt)	57.7
   	Fixed carbon (%wt)	15.4
   	Ash content (%wt)	17.6
   	LHV (MJ/kg)	13.56
   Ultimate Analysis
   	Carbon (%wt)	36.6
   	Hydrogen (%wt)	5.83
   	Oxygen (%wt)	36.65
   	Nitrogen (%wt)	3.31

3. Computational Model

   The computational modeling approach in this paper consists mainly of two parts, namely: the chemical kinetics of the gasification process and the hydrodynamics of the fluidized bed reactor.

   1. Chemical Kinetics Model

      It is widely reported in literature that the actual reaction scheme of biomass gasification is extremely complex because of the formation of over a hundred intermediate products. Because of this complexity, gasification process is generally simplified and modeled in single or multi- steps kinetics. The work presented in this paper follows multi-step kinetics (Figure 1) whose reaction rate is in Arrhenius form as shown in equation 1 which is frequently cited in literature.

      parallel primary reactions with the possibility of a tar cracking reaction; that is, the biomass decomposes to gas, tar and char, and vapor tar decomposes to yield further gas as shown in Figure 2. Tar cracking reactions in the form of secondary reactions were adapted from Di Blasi [2].

      Figure 2: Schematic of biomass gasification and tar cracking [2].

   2. Conservative Governing Equations

      dm m * A * exp E

      (1)

      dt

      RT

      The hydrodynamics of the fluidized bed gasifier was performed by solving the equations of motion of a multiphase system.

      where A is the apparent frequency factor, E

      is the apparent activation energy, and m is the mass of reactant. E is activation energy at a temperature T. R is the universal gas constant.

      The kinetic mechanism employed in our simulation of single particle biomass pyrolysis and gasification accounts for three

      An Eulerianmodel for the mass and momentum for the gaseous phase was applied, while the kinetic theory of granular flow was applied for the conservation of the solid's fluctuation energy. The governing equations are expressed in the following form Gidaspow [7].

      1. Mass conservation

         EulerianEulerian continuum modeling is the most commonly used approach for fluidized bed simulations. The phases are able to interpenetrate and the accumulation

         _

         and I is a unit vector. The bulk viscosity

         s is based kinetic theory of granular flows.

         The Gidaspow [7] inter-phase exchange coefficient is given as follows:

         of mass in each phase is balanced by the convective mass fluxes.

         Gas Phase

         Kgs

         3 C

         4 d

         s g

         g u

         ds

         s ug

         ( g

         )2.65

         ( g g )

         (

         v ) 0

         (2)

         for g 0.8

         (7)

         t

         Solid Phase

         g g g

         s

         s

         d

         d

         d

         d

         K 150

         2

         2

         2

         g 1.75

         s g us ug

         ( s s ) ( v ) 0

         gs

         g s s

         (3)

         t s s s

         for g 0.8

         (8)

      2. Momentum conservation

         In gassolid fluidized beds the sum of forces

      3. Conservation of Energy

         To describe the conservation of energy in

         consists of the viscous force

         _

         s

         , the

         Eulerian multiphase model, a separate enthalpy equation can be written for each

         solids pressure force ps , the body force

         phase:

         s s g the static pressure force s .ps

         and the inter-phase force Kgs (ug us ) for

         Gas Phase

         the coupling of gas and solid momentum equations by drag forces [7].

         t g

         g hg

         g ug hg

         g

         g

         g

         g

         dpg

         dt

         Gas Phase

         ( g gvg ) (

         t g

         _

         gvgvg ) g

         p

         (4)

         g .ug qg Qgs mgs hgs Sq

         (9)

         where, the last three terms are respectively

         • g g g g Kgs (ug us )

         heat conduction, energy transfer with heat

         transfer and energy source and hg is the

         Solid Phase

         specific enthalpy of the gas phase, qg is the

         ( v )

         heat flux, Sg is a source term that includes

         s s s (

         v v )

         p

         t s

         s g s s

         (5)

         sources of enthalpy (e.g., due to chemical

         • ps

         _

         s

         • s

         s g K

         gs (ug

         • us )

           reaction or radiation), Qgs is the intensity

           of heat exchange between the gas and solid

           _

           where the solid-phase stress tensor is

           given by

           phases, and hgs is the inter-phase enthalpy (e.g., the enthalpy of the vapor at the temperature of the droplets, in the case of

           _ T evaporation). Note that solid phase energy

           s s (us us ) s (s

           2 _ (6)

           • 3 s ).us I s

         conservation equation is similar to equation

         (9) above, thus not shown. The fluidized bed heat transfer was based on the work reported by Gunn [8]

   3. Computational Procedure

      The governing partial differential equations for conservative of mass, momentum and energy are discritized and iteratively solved by FLUENT 12 software [6]. Initial conditions are required for the static bed void fraction in the reactor volume, and the bed temperature. The boundary conditions are those of the mass fluxes of the gases and solids at the flow boundary. Each inflow boundary is fully specified by the mass flow rate, void fraction, mass fractions of the gas and solids species and the boundary temperature. The reactor outlet was modeled as pressure outlet boundary.

4. Results and discussions

Figure 3 depict the temperature distribution in the gasifier reactor as the equivalence ratio is varied. It is clearly seen that highest reactor temperature is attained when the equivalence ratio is near 1, that is mostly combustion is taking place rather than gasification. On the other hand, the lowest temperature is observed at low equivalence ratio, that is the exothermic reactions are

confined at bottom side of the reactor where limited air enters the reactor and quickly consumed.

The influence of equivalence ratio on the yield of syngas (CO and H2) is shown in Figures 4 and 5, respectively. The highest yield lies between the equivalence ratio 0.39 and 0.26, and that the syngas occupies nearly three quarters of the reactor volume. The uniform temperature distribution in the reactor due to fluidization favors gasification reactions to take place in large volume of the reactor.

Figure 6 depicts that the exit gas temperature decreases with decreasing the equivalence ratio. This was the expected trend which is due to the limited exothermic reactions at low equivalence ratios. On the other hand, Figure 7 provides validation of the CFD model with measured data [5] which compares fairly well.

Figure 3: Temperature distribution in the gasifier with varying equivalent ratio

Figure 4: Distribution of CO concentration in gasifier with varying equivalent ratio

Figure 5: Distribution of H2 concentration in gasifier with varying equivalent ratio

1600

1400

1200

1000

800

600

400

200

0

Equivalence ratio

1600

1400

1200

1000

800

600

400

200

0

Equivalence ratio

Gasifier exit temperature (K)

Gasifier exit temperature (K)

0.957

0.957

0.591

0.591

0.502

0.502

0.386

0.386

0.229

0.229

0.135

0.135

0.068

0.068

0.035

0.035

0.027

0.027

Figure 6: Gasifier exit temperature with varying equivalent ratio

CO H2

0.2

0.16

Mole fraction

Mole fraction

0.12

0.08

0.04

0.957

0.957

0.591

0.591

0.502

0.502

0.386

0.386

0.229

0.229

0.135

0.135

0.068

0.068

0.035

0.035

0.027

0.027

0

Equivalence ratio

Figure 7: Gasifier exit concentration for CO and H2 with varying equivalent ratio

DATA (Ferdinandez) CFD (Model)

0.20

Gas Yield (mole fraction)

Gas Yield (mole fraction)

0.16

0.12

0.08

0.04

0.00

CH4 CO H2

Figure 8: Model validation against measured data reported by Fernandez [5]

6. Conclusion

The simulation results of chemically reactive fluidized bed demonstrates that it is feasible to calculate the coupled effects of heavily-loaded gas-particles hydrodynamics, heat transfer and complicated gasification reactions. The comparison of results with published experimental data showed that the CFD model can be a useful tool when requiring a preliminary prediction of the

performance variables values of pilot biomass fluidized bed gasifiers. That is, the successful results obtained stimulate the potential development of this clean technology for the value-added of agro- wastes by means of the use of the fluidized bed gasification technology. The current model can be a good guide for fluidized bed reactor design and troubleshoot, since it can predict the biomass particle motion and gasification reactions inside the reactor.

References

1. David Ross. (2007), Axial gas profiles in a bubbling fluidized bed biomass gasifier, Fuel, 86, pp. 1417-1429.

2. Di Blasi C., Combust. Sci. Technol. 90 (1993) 315340.

3. Xiong Z. H. and J.Chang (2004), An experimental study on biomass airsteam gasificatin in a fluidized bed , Bioresource Technology, Vol. 95, pp. 95-101.

4. Fryda L. E., K.D.Panapoulos and E.Karkaras (2008), Agglomeration in fluidized bed gasification of biomass, Powder Technology, Vol. 181, pp. 307-320.

5. Fernandes, M., Investigação Experimental de Gaseificação de Biomassa em Leito Fluidizado, Ph.D. Thesis, UNICAMP, Campinas, Brazil (2004)

6. FLUENT 12.0 Users Guide Copyright ANSYS, Inc. (2009)

7. Gidaspow D., R. Bezburuah, J. Ding, Hydrodynamics of circulating fluidized beds, kinetic theory approach, in: Fluidization VII, Proceedings of the 7th Engineering Foundation Conference on Fluidization (1992), pp. 75e82.

8. Gunn, D. J. Transfer of Heat or Mass to Particles in Fixed and Fluidized Beds. Int. J. Heat Mass Transfer, 21:467{476, 1978.