A Modeling of Biomass Fast Pyrolysis using CFD in a fluidized bed reactor

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1 Ref: C0273 A Modeling of Biomass Fast Pyrolysis using CFD in a fluidized bed reactor Young Min Ju, Department of Biosystems Engineering, Kangwon National University, Hyoja 2 Dong, Chuncheon, Republic of Korea Seung Hui Eo, Department of Biosystems Engineering, Kangwon National University, Hyoja 2 Dong, Chuncheon, Republic of Korea Kang Yol Lee, Eco Plant Co., Ltd., Gyeonggi, Republic of Korea Beom Goo Lee, Eco Plant Co., Ltd., Gyeonggi, Republic of Korea Dae Hyun Kim, Department of Biosystems Engineering, Kangwon National University, Hyoja 2 Dong, Chuncheon, Republic of Korea Abstract The study focused on analysis of yield products generated during fast pyrolysis of biomass in fluidized bed reactor and comparism simulation data with experimental data. The Computational Fluid Dynamics (CFD) modeling for this purpose has been developed. CFD program (ANSYS FLUENT v.14.5) was used for simulation of fast pyrolysis. Complex pyrolysis reaction scheme of biomass sub-components was applied for simulation of pyrolysis reaction. This pyrolysis reaction scheme included the detail reaction of cellulose, hemicellulose & lignin. The gas products obtained from pyrolysis were mainly CO 2, CO, CH 4, H 2, C 2 H 4. Predicted result were compared with experimental data in respect of deviation, and deviation of CH 4, H 2, CO was about 0.98%P, 14.81%P, 2.75%P respectively, and deviation of CO 2, CO is about 3.45%P, 16.39%P respectively. In the future, it will be possible for the production of bio-oil and its component through more detailed model. Keywords: Fluidized bed reactor, Biomass, Fast pyrolysis, Bio-oil, CFD 1 Introduction Recently, Bio-oil generated from fast pyrolysis has been attracted attention as new renewable energy. Especially, Bio-oil has high density energy, carbon cycle type, low transportation costs. Fast pyrolysis process means a conversion of biomass derived, temperature not exceeding 500 range, to liquid fuel. Accordingly, many processes of the production of bio-oil have been developed. At this point, modeling of the fast pyrolysis process is challenging in many ways. Such studies understand the relationship between a number of complex mechanisms of the decomposition process and competitive chemo-physical phenomena of the reactor, and complex structure of biomass. The modeling is proceeding by applying a CFD simulation, which have thermo-chemical and physical properties of the reactor and economic benefits of the virtual design. Currently, several studies in the analysis of CFD simulation for pyrolysis have been done as a representative, resulting from fast pyrolysis of liquid, gas, solid components. Other studies are concentrated on non-uniform reaction of biomass particles, in addition, several studies are concentrated on substances generated by thermal decomposition and kinetics. In a re- Proceedings International Conference of Agricultural Engineering, Zurich, /7

2 cent study, the complex reaction of thermal decomposition and the overall biomass pyrolysis process was applied to the analysis. Therefore, in this study, CFD simulation for the pyrolysis of biomass in the fluidized bed reactor is analyzed. For this application, the flow of gas, particle phase, and extensive equation based on physical and chemical theory in the reactor is applied. In addition, UDF (User Defined Function) for detailed pyrolysis reaction was applied, which helped for precise prediction of composition generated from pyrolysis process, and this prediction was to validate simulation with experimental data. 2 Materials and methods 2.1 Configuration and description of fluidized bed reactor for CFD simulation A schematic overview of the fluidized bed reactor modeled in CFD simulation is shown in Fig. 1 and assumed to feed nitrogen and biomass at the inlet. Inside the reactor, the vapor generated from pyrolysis is produced to the outlet. Domain for CFD simulation is indicated by a dotted line. 2.2 Modeling approach Modeling of this study is applied as follows: The Eulerian multiphase flow equation is applied to a each one of the gas phase and the solid phase of the substance between the momentum and heat exchange transfer. Pyrolysis reaction equation for a subcomponent of biomass is applied and reaction rate of decomposition of each subcomponent is applied by the UDF. As stated above, the pyrolysis reaction equation follows a system of tar cracking reaction presented from Blondeau and Jeanmart [Blondeau et al., 2012] and detailed pyrolysis reaction presented from Ranzi et al. [Ranzi et al., 2008]. Reaction pathway is shown in Fig. 2 [Melin et al., 2014]. The flow of a fluidized bed reactor is assumed to be turbulent. In addition, analysis was applied to the transient state and the decision of convergence is reduced below to 1x10-3 in residuals Species transport in multiphase flows The multiphase flow of CFD calculation is based on continuity equations. Chemical species conservation equation of multiphase mixture is represented in the eqation (1), is local mass fraction, is net rate of production of homogeneous species, is mass transfer, is the diffusion flux, is heterogeneous reaction rate. ( ) ( ) ( ) The Heterogeneous reaction rate is defined by UDF for reaction 1-15 of primary pyrolysis reaction (Fig. 1). [Melin et al., 2014] Gas phase Gas phase is modified conservation equations for mass, momentum and energy. Gas phase in multiphase flow is assumed to be continuity equations. the eqation (2) is the conservation of mass of continuity equation for gas phase, where is velocity and is mass transfer, is the density, is volume fraction. The source term is defined by the user. ( ) ( ) ( ) Proceedings International Conference of Agricultural Engineering, Zurich, /7

3 The conservation equation of momentum for gas phase is the eqation (3), where is the stress-strain tensor, is external body force, is lift force, is the wall lubrication force, is virtual mass force, is turbulent dispersion force, is interaction force. ( ) ( ) The conservation equation of energy for gas phase is the eqation (4), where is heat flux, is intensity of heat exchange, is interphase enthalpy. ( ) ( ) Solid phase The conservation equation of momentum for the solid phase is the eqation (5), where solids pressure, is total number of phases. is ( ) Geometry, mesh and boundary condition The Geometry used in the simulation is 2D (two-dimensional). The mesh is composed of 1071 nodes and 1000 cells. Biomass and nitrogen injected in 3m/s and 0.2m/s velocity respectively at the pyrolysis reactor. The component ratio of cellulose, hemicellulose and lignin is according to the data in Mellin et al. [Melin et al., 2014]. Detailed boundary condition and material parameters used in the simulation is shown in Table Heterogeneous reaction and tar cracking reaction Complex scheme of pyrolysis reaction is decomposed into each composition. Cellulose, hemicellulose and lignin consisted of biomass is each decomposed to gas, tar compounds and char respectively is by primary reaction. Furthermore, sub-components generated from intermediate products are degraded to gas and char. Detailed chemical dissolution systems of primary pyrolysis reaction are shown in Table 2. After primary pyrolysis takes place, secondary pyrolysis reaction is occurred by tar compounds. Finally, tar compounds are decomposed to gas and char by thermal cracking. The detailed thermal cracking reactions are shown in Table 3. 3 Results and Discussion The fluidized bed reactor simulation using CFD was conducted for 10.25s, and the results were compared with experiment. The gas products obtained from simulation were mainly CH 4, H 2, CO 2, CO and C 2 H 4, and each mole fraction of gas species was 15.28%, 21.21%, 24.85%, 31.31% and 7.35% respectively. The experimental data referred to [Melin et al., 2014], each mole fraction of gas species CH 4, H 2, CO 2, CO and C 2 H 4 was 14.3%, 6.4%, 38.3%, 47.7%, 4.6% respectively. Predicted results were compared with experimental data in respect of deviation, and deviation of CH 4, H 2, C 2 H 4 is about 0.98%P, 14.81%P, 2.75%P re- Proceedings International Conference of Agricultural Engineering, Zurich, /7

4 spectively, and deviation of CO 2, CO is about 3.45%P, 16.39%P respectively shown in Table 4. 4 Conclusions In this paper, gas species prediction, generated from biomass fast pyrolysis in fluidized bed reactor was compared with experimental data. For this, complex primary and secondary pyrolysis reaction was simulated by CFD model. Even though pyrolysis reaction in the modeling is complex, and varied multiphase fluid equation is applied, the predicted results had good agreement with the experimental data. However, the deviation in H 2 and CO was relatively bigger so that accurate modeling should be developed. To improve modeling, more research in pyrolysis phenomenon is needed. From now on, simulation for accurate prediction is progress by three-dimensional figuration will be carried out. Also designed modeling will be applied in vacuum pyrolysis reactor. 5 Acknowledgements This study was supported by 2013 Research fund from Eco Plant. 6 References ANSYS FLUENT Theory Guide. ANSYS, Inc Blondeau J, Jeanmart H. (2012) Biomass pyrolysis at high temperature: prediction of gaseous species yields from an anisotropic particle. Biomass Bioenergy, 41, Mellin P, Zhang Q, Kantarelis E.(2013) An Euler-Euler approach to modeling biomass fast pyrolysis in fluidized-bed reactor. Appl therm Eng, 58, Mellin P, Efthymios Kantarelis, Weihong Yang.(2014) Computational fluid dynamics modeling of biomass fast pyrolysis in a fluidized bed reactor. using a comprehensive chemistry scheme. Fuel, 117, Ran zi E, Faravelli T, Frassoldati A, Migliavacca G, Pierucci S, Sommariva S.(2008) Chemical kineics of biomass pyrolysis. Energy Fuel, 22, Proceedings International Conference of Agricultural Engineering, Zurich, /7

5 Fig. 1. System of fluidized bed reactor Fig. 2. Reaction pathways used in the model [Melin et al., 2014] Proceedings International Conference of Agricultural Engineering, Zurich, /7

6 Fig.3. Comparison of simulated and experimental data CH 4 H 2 CO 2 CO C 2 H 4 Fig.4. Main species in contour of mole fraction in a reactor Table 1. Data used for the simulation Material parameters Gas phase Solid phase Boundary parameters Phase 1 (Gas) Phase 2 (Solid) Heat conductivity (w/m-k) Heat capacity (J/kg-k) Mixing-law Viscosity (kg/m-s) 6e-05 Mass Diffusivity (m 2 /s) 1e-07 Heat conductivity (w/m-k) 1.5 Heat capacity (J/kg-k) Mixing-law Viscosity (kg/m-s) 1.72e-05 Mass Diffusivity m 2 /s) 1e-12 Inlet velocity (m/s) 3 Inlet Temperature (k) 973 Inlet Mass Fractions (N 2) 1 Inlet velocity (m/s) 0.2 Inlet Temperature (k) 310 Inlet Mass Fractions (Cell) [Melin et al., 2014] Inlet Mass Fractions (HCell) [Melin et al., 2014] Inlet Mass Fractions (LignC) [Melin et al., 2014] Inlet Mass Fractions (LignH) [Melin et al., 2014] Inlet Mass Fractions (LignO) [Melin et al., 2014] Proceedings International Conference of Agricultural Engineering, Zurich, /7

7 Table 2. Primary pyrolysis reactions [Melin et al., 2014] Reaction A (s -1 ) E (kj/mol) 1 Cell CellA 8X h (kj/kg) 2 Cell 5H2O + 6Char 8X CellA LVG 4T CellA 0.95HAA + 0.2Acetaldehyde HMFU + 0.2Acetone CO CO + 0.9H2O + 0.1CH Char 1X Hcell 0.4Hcell Hcell2 1X HCell1 0.75H CO CO + 0.5Formaldehyde Methanol Ethanol H2O CH C2H Char 3X HCell1 Xylan 3T HCell2 CO CH C2H CO + 0.8H Formaldehyde Methanol Ethanol H2O Char 1X LignC 0.35LignCC + 0.1pCoumaryl Phenol C2H4 + 1H2O CH CO+ 1H Char 4X LignH LignOH + Acetone 2X LignO LignOH + CO2 1X LignCC 0.3pCoumaryl + 0.2Phenol Acrylic-acid + 0.7H2O CH CO + H Char 5X LignOH Lign + H2O + Methanol CH C2H4 + 2CO + 0.7H Char 3X Lign Lumped-phenol 8T Lign H2O + 2CO + 0.2Formaldehyde + 0.4Methanol + 0.2Acetaldehyde + 0.2Acetone + 0.6CH C2H H Char 1.2X H2O(l) H2O(g) 5.3X Table 3. Secondary pyrolysis reactions [Melin et al., 2014] Reaction A (s-1) E (kj/mol) 1 HMFU 3CO + 1.4C2H4 4.28X h (kj/kg) 2 Acetone 0.5CO H C2H4 4.28X pcoumaryl CO C2H4 + 3Char 4.28X Phenol 0.5CO C2H Char 4.28X Xylan 2CO2 + H C2H4 4.28X LVG 2.5CO H C2H4 4.28X HAA 2CO + 2H2 4.28X Glyoxal 2CO + H2 4.28X Lumped-phenol 2CO2 + 3C2H4 + 3Char 4.28X Acrylic CO2 + C2H4 4.28X Table 4. Comparison of simulated and experimental data Experiment [Melin Simulation [Melin Species et al., 2014] et al., 2014] Simulation Error (%P) CH H CO CO C 2 H Proceedings International Conference of Agricultural Engineering, Zurich, /7

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