Multiphase fluid dynamics coupled fast pyrolysis of biomass in a rectangular bubbling fluidized bed reactor: Process intensification

Upadhyay, Mukesh; Park, Hoon Chae; Choi, Hang Seok

doi:10.1016/j.cep.2018.04.028

Cited by 25 publications

(5 citation statements)

References 44 publications

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“…Semi-global chemical kinetics were incorporated for the pyrolysis reaction in the solid and fluid flow. A CFD multi-phase particle-in-cell approach showed a perfect match with experimental studies [97]. However, there was a significant difference in the product yield when compared to other experimental studies due to the application of different chemical kinetics on the secondary decomposition reaction of the tar when using computational particle fluid dynamics (CPFD), whereby the semi-global kinetics obtained from a spouted bed thermo-gravimetric analyzer (MSB-TGA) were used to predict the product yield.…”

Section: Cfd In Conventional Pyrolysis Reactorssupporting

confidence: 56%

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Kulkarni,

Mishra,

Palla

et al. 2023

Energies

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Pyrolysis, a process for extracting valuable chemicals from waste materials, leverages computational fluid dynamics (CFD) to optimize reactor parameters, thereby enhancing product quality and process efficiency. This review aims to understand the application of CFD in pyrolysis. Initially, the need for pyrolysis and its role in biomass valorization are discussed, and this is followed by an elaboration of the fundamentals of CFD studies in terms of their application to the pyrolysis process. The various CFD simulations and models used to understand product formation are also explained. Pyrolysis is conducted using both conventional and microwave-assisted pyrolysis platforms. Hence, the reaction kinetics, governing model equations, and laws are discussed in the conventional pyrolysis section. In the microwave-assisted pyrolysis section, the importance of wavelength, penetration depth, and microwave conversion efficiencies on the CFD are discussed. This review provides valuable insights to academic researchers on the application of CFD in pyrolysis systems. The modeling of pyrolysis by computational fluid dynamics (CFD) is a complex process due to the implementation of multiple reaction kinetics and physics, high computational cost, and reactor design. These challenges in the modeling of the pyrolysis process are discussed in this paper. Significant solutions that have been used to overcome the challenges are also provided with potential areas of research and development in the future of CFD in pyrolysis.

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Section: Cfd In Conventional Pyrolysis Reactorssupporting

confidence: 56%

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Kulkarni,

Mishra,

Palla

et al. 2023

Energies

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“…CFD modeling techniques have been widely used for studying the thermal decomposition of biomass under inert , and air/steam conditions. , The CFD tool has been efficiently used in modeling pyrolysis in fluidized bed reactors due to their efficient heat and mass transfer rates along with even product distributions. Xue et al used the Euler–Euler model for the fast pyrolysis of biomass in a fluidized bed reactor.…”

Section: Modeling Approaches To the Pyrolysis Processmentioning

confidence: 99%

Recent Modeling Approaches to Biomass Pyrolysis: A Review

2021

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Biomass pyrolysis is a thermochemical conversion process that undergoes a complex set of concurrent and competitive reactions in oxygen-depleted conditions. A considerable amount of the literature uses lumped kinetic approaches to predict pyrolysis products. Despite the prolonged studies, the science of pyrolysis chemistry and models’ capability to simulate the exact conversion phenomenon has unraveled yet. In this review, an initiative was made by compiling existing mathematical models for biomass pyrolysis viz., lumped and distributed kinetic models, particle, and reactor models. An absolute analysis of computational fluid dynamics (CFD), artificial neural network (ANN), and ASPEN Plus models was also conducted. It was observed that the coupling of distributed kinetic models with CFD provides a better understanding of the hydrodynamic reaction of particles under reactive flow with the influence on reactor performance and predicts exact product yield. Furthermore, the pros and cons of each modeling technique are also highlighted individually. Finally, considering the future perspective of biomass pyrolysis with respect to the modeling approach, suggestions have been incorporated.

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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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Multiphase fluid dynamics coupled fast pyrolysis of biomass in a rectangular bubbling fluidized bed reactor: Process intensification

Cited by 25 publications

References 44 publications

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Recent Modeling Approaches to Biomass Pyrolysis: A Review

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

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