Detailed CFD modelling of fast pyrolysis of different biomass types in fluidized bed reactors

Eri, Qitai; Wang, Baolu; Peng, Jing; Zhao, Xiaoxian; Li, Ting

doi:10.1002/cjce.23180

Cited by 12 publications

(5 citation statements)

References 27 publications

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“…For instance, ANSYS FLUENT [25,44,47,[52][53][54], Multiphase Flow with Interphase eXchanges (MFIX) [33,37,55,56], OpenFOAM [26,27,29,30,35,38,57,58] etc. have been used frequently for simulation of reacting multiphase flow including combustion [52], gasification [52][53][54] and pyrolysis process [44,47,48,52,56,59]. Among them, ANSYS FLUENT has attracted the attention of engineers and researchers due to features including its user-friendly environment, capability of modelling complex geometries inside ANSYS workbench interface, programming facility by adding user defined functions (UDF), having most recent empirical correlations for granular heat transfer and drag as well as the KTFG (Kinetic Theory of Granular Flow); models that are needed for description of interphase transport phenomena.…”

Section: Introductionmentioning

confidence: 99%

Parametric analysis of pyrolysis process on the product yields in a bubbling fluidized bed reactor

Jalalifar

Garaniya

Hawboldt

et al. 2018

Fuel

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This paper presents a numerical study of operating factors on the product yields of a fast pyrolysis process in a 2-D standard lab-scale bubbling fluidized bed reactor. In a fast pyrolysis process, oxygen-free thermal decomposition of biomass occurs to produce solid biochar, condensable vapours and non-condensable gases. This process also involves complex transport phenomena and therefore the Euler-Euler approach with a multifluid model is applied. The eleven species taking part in the process are grouped into a solid reacting phase, condensable/non-condensable phase, and non-reacting solid phase (the heat carrier). The biomass decomposition is simplified to ten reaction mechanisms based on the thermal decomposition of lignocellulosic biomass. For coupling of multi-fluid model and reaction rates, the time-splitting method is used. The developed model is validated first using available experimental data and is then employed to conduct the parametric study. Based on the simulation results, the impact of different operating factors on the product yields are presented. The results for operating temperature (both sidewall and carrier gas temperature) show that the optimum temperature for the production of bio-oil is in the range of 500-525°C. The higher the nitrogen velocity, the lower the residence time and less chance for the secondary crack of condensable vapours to non-condensable gases and consequently higher bio-oil yield. Similarly, when the height of the biomass injector was raised, the yields of condensable increased and non-condensable decreased due to the lower residence time of biomass. Biomass flow rate of 1.3 kg/h can produce favourable results. When larger biomass particle sizes are used, the intraparticle temperature gradient increases and leads to more accumulated unreacted biomass inside the reactor and the products' yield decreases accordingly. The simulation indicated that the larger sand particles accompanied by higher carrier gas velocity are favourable for bio-oil production. Providing a net heat equivalent of 6.52 watts to the virgin biomass prior to entering the reactor bed leads to 7.5 % higher bio-oil yields whereas other products' yields stay steady. Results from different feedstock material show that the sum of cellulose and hemicellulose content is favourable for the production of bio-oil whereas the biochar yield is directly related to the lignin content.

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Section: Introductionmentioning

confidence: 99%

Parametric analysis of pyrolysis process on the product yields in a bubbling fluidized bed reactor

Jalalifar

Garaniya

Hawboldt

et al. 2018

Fuel

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Section: Introductionmentioning

confidence: 99%

“…The important factors, including biomass types, heating rate, and temperature, in the pyrolysis process have been studied by some researchers [20][21][22][23]. The fast pyrolysis of four different biomass types was examined by Eri et al via detailed CFD modelling [23]. Their study showed that cellulose-rich biomass produced the highest bio-oil yield, and the generated char was mainly from the lignin and cellulose of the biomass.…”

Section: Introductionmentioning

confidence: 99%

Hydrogen-Rich Gas Production from Two-Stage Catalytic Pyrolysis of Pine Sawdust with Nano-NiO/Al2O3 Catalyst

Zheng

et al. 2022

Catalysts

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Hydrogen production from biomass pyrolysis is economically and technologically attractive from the perspectives of energy and the environment. The two-stage catalytic pyrolysis of pine sawdust for hydrogen-rich gas production is investigated using nano-NiO/Al2O3 as the catalyst at high temperatures. The influences of residence time (0–30 s) and catalytic temperature (500–800 °C) on pyrolysis performance are examined in the distribution of pyrolysis products, gas composition, and gas properties. The results show that increasing the residence time decreased the solid and liquid products but increased gas products. Longer residence times could promote tar cracking and gas-phase conversion reactions and improve the syngas yield, H2/CO ratio, and carbon conversion. The nano-NiO/A12O3 exhibits excellent catalytic activity for tar removal, with a tar conversion rate of 93% at 800 °C. The high catalytic temperature could significantly improve H2 and CO yields by enhancing the decomposition of tar and gas-phase reactions between CO2 and CH4. The increasing catalytic temperature increases the dry gas yield and carbon conversion but decreases the H2/CO ratio and low heating value.

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“…So far, the Computational Fluid Dynamic (CFD) method has been recognized as a useful tool in predicting the product yields of chemical processes, as well as plant design and optimization. Most of the recent CFD studies were applied to biomass pyrolysis in fluidized bed reactors [19][20][21][22][23]. Papadikis et al [24][25][26][27][28][29] simulated biomass fast pyrolysis in fluidized beds assuming two Eulerian phases and one Lagrangian phase in a 3-D domain.…”

Section: Introductionmentioning

confidence: 99%

CFD modeling and experimental validation of biomass fast pyrolysis in a conical spouted bed reactor

Hooshdaran

Haghshenasfard

Hosseini

et al. 2021

Journal of Analytical and Applied Pyrolysis

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Detailed CFD modelling of fast pyrolysis of different biomass types in fluidized bed reactors

Cited by 12 publications

References 27 publications

Parametric analysis of pyrolysis process on the product yields in a bubbling fluidized bed reactor

Parametric analysis of pyrolysis process on the product yields in a bubbling fluidized bed reactor

Hydrogen-Rich Gas Production from Two-Stage Catalytic Pyrolysis of Pine Sawdust with Nano-NiO/Al2O3 Catalyst

CFD modeling and experimental validation of biomass fast pyrolysis in a conical spouted bed reactor

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