The Discrete Phase Modelling Governing The Dynamics Of Biomass Particles Inside A Fast Pyrolysis Reactor

Main Article Content

Muhammad Rabie Omar
Nurhayati Abdullah
Ahmad Rujhan Rais

Abstract

The influences of several important biomass pyrolysis process parameters
such as the biomass feedstock type, flow pressure, biomass feeding rate and biomass particle size play an important role to ensure an efficient pyrolysis process. Unfortunately, the determination of these parameters can be cumbersome and often requires the method of trial and error. As a result, our work discusses the idea of the application of discrete phase modelling (DPM) in the fast pyrolysis process so that the optimum value of these essential
parameters can be determined numerically. The numerical test demonstrated in this paper involving the fast pyrolysis of wood indicates that the application of DPM in the simulation is feasible for obtaining the initial prediction of the optimum process parameters.

Article Details

How to Cite
Muhammad Rabie Omar, Nurhayati Abdullah, and Ahmad Rujhan Rais. 2026. “The Discrete Phase Modelling Governing The Dynamics Of Biomass Particles Inside A Fast Pyrolysis Reactor”. Kajian Malaysia 31 (1): 105-19. https://doi.org/10.21315/.
Section
Articles

References

Bridgwater, A. V., Meier, D. & Radlein, D. (1999). An overview of fast pyrolysis

of biomass. Org. Geochem., 30, 1479–1493. https://doi.org/10.1016/S0146-6380(99)00120-5

Abdullah, N. & Gerhauser, H. (2008). Bio-oil derived from empty fruit bunches.

Fuel, 87(12), 2606–2613. https://doi.org/10.1016/j.fuel.2008.02.011

Papadikis, K. et al. (2009). Application of CFD to model fast pyrolysis of biomass.

Fuel Process. Technol., 90, 504–512. https://doi.org/10.1016/j.fuproc.2009.01.010

Papadikis, K., Gu, S. & Bridgwater, A. V. (2009). CFD Modelling of the fast

pyrolysis of biomass in fluidized bed reactors: Modelling the impact of biomass

shrinkage. Chem. Eng. J., 149, 417–427. https://doi.org/10.1016/j.cej.2009.01.036

Mellin, P. et al. (2014). Computational fluid dynamics modelling of biomass fast

pyrolysis in a fluidized bed reactor, using a comprehensive chemistry scheme.

Fuel, 117, 704–715. https://doi.org/10.1016/j.fuel.2013.09.009

Mellin, P. et al. (2013). A Euler-Euler approach to modelling biomass fast pyrolysis

in fluidized-bed reactors: Focusing on the gas phase. Appl. Therm. Eng., 58, 344–

https://doi.org/10.1016/j.applthermaleng.2013.04.054

Di Blasi, C. (1996). Heat, momentum and mass transport through a shrinking

biomass particle exposed to thermal radiation. Chem. Eng. Sci., 51(7), 1121–1132.

https://doi.org/10.1016/S0009-2509(96)80011-X

Di Blasi, C. (2000). Modelling the fast pyrolysis of cellulosic particles in fluid-

bed reactors. Chem. Eng. Sci., 55, 5999–6013. https://doi.org/10.1016/S0009-2509(00)00406-1

Ravindra K. A. (1985). On the use of the arrhenius equation to describe cellulose

and wood pyrolysis. Thermochim. Acta, 91, 343–349. https://doi.org/10.1016/0040-6031(85)85227-8

Sulaiman, F. & Abdullah, N. (2011). Optimum conditions for maximizing

pyrolysis liquids of oil palm empty fruit bunches. Energy, 36, 2352–2359.

https://doi.org/10.1016/j.energy.2010.12.067

Bridgwater, A. V. (2012). Review of fast pyrolysis of biomass and product

upgrading. Biomass Bioenergy, 38, 68–94. https://doi.org/10.1016/j.biombioe.2011.01.048

Sinha, S. et al. (2000). Modelling of pyrolysis in wood: A review. Sol. Energy Soc.Ind., 10, 41–62.

Holzer, A. & Sommerfeld, M. (2008). New simple correlation formula for

the drag coefficient of non-spherical particles. Powd. Technol., 184, 361–365.

https://doi.org/10.1016/j.powtec.2007.08.021

Brown, D. J. (1982). The questionable use of the arrhenius equation to

describe cellulose and wood pyrolysis. Thermochim. Acta, 54, 377–379.

https://doi.org/10.1016/0040-6031(82)80032-4

Aarne Vesilind, P. (1980). The Rosin-Rammler particle size distribution. Res. Rec.

Conserv., 5, 275–277. https://doi.org/10.1016/0304-3967(80)90007-4

Wai-Chun, R., Chan, M. K & Barbara B. K. (1985). Modelling and experimental

verification of physical and chemical processes during pyrolysis of a large biomass

particle. Fuel, 64, 1505–1513. https://doi.org/10.1016/0016-2361(85)90364-3

Mate, M. (2016). Numerical modelling of wood pyrolysis. Post-graduate diss.,

KTH Institute of Technology, Stockholm, Sweden.

Ranzi, E., Debiagi, P. & Frassoldati, A. (2017). Mathematical modeling of fast

biomass pyrolysis and bio-oil formation. Note I: Kinetic mechanism of biomass

pyrolysis. ACS Sustain. Chem. Eng., 5, 2867–2881. https://doi.org/10.1021/acssuschemeng.6b03096

Rodriguez-Alejandro, D. A. et al. (2018). Numerical simulation of a pilot-scale

reactor under different operating modes: combustion, gasification and pyrolysis.

Biomass Bioenergy, 116, 80–88. https://doi.org/10.1016/j.biombioe.2018.05.007

Alper, K., Tekin, K. & Karagöz, S. (2015). Pyrolysis of agricultural residues

for bio-oil production. Clean Tech. Environ. Policy, 17, 211–223. https://doi.org/10.1007/s10098-014-0778-8

Karagöz, S. (2009). Energy production from the pyrolysis of waste biomasses.

Int. J. Energy Res., 33, 576–581. https://doi.org/10.1002/er.1493