CFD-DEM coupled with thermochemical sub-models for biomass gasification: Validation and sensitivity analysis

Wang, Shuai; Luo, Kun; Fan, Jianren

doi:10.1016/j.ces.2020.115550

Cited by 146 publications

(33 citation statements)

References 77 publications

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“…Nitrogen and oxygen were not detected. Besides, gas yields were calculated according to Equation (13); their values are presented in Table 4.…”

Section: Supercritical Water Gasificationmentioning

confidence: 99%

“…About experiments, fuel synthesis has been performed above critical temperature of water up to 1123 K in catalytic/non-catalytic batch or continuous flow reactors made of different materials. All these parameters are aimed to describe the reaction mechanism, look for the optimum operating conditions, and perform numerical simulation [3][4][5][6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…For instance, lignocellulosic biomass is typically constituted by cellulose (45-50%), hemicellulose (20-25%) and lignin (20-25%). The reaction mechanism that induces water is complex at these conditions, as demonstrated elsewhere [3][4][5][6][7][8][9][10][11][12][13][14][15]. Initially, biomass material conversion produces intermediates by hydrolysis and the water solvating power effect.…”

Section: Introductionmentioning

confidence: 99%

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Gasification of Psidium guajava L. Waste Using Supercritical Water: Evaluation of Feed Ratio and Moderate Temperatures

et al. 2021

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Biomass waste, as raw material for renewable energy, is an attractive alternative since it does not compete with human food supply. An emerging alternative for its treatment is supercritical water gasification (SCWG), due to the high moisture content of some types of biomass. On this regards, guava fruit (Psidium guajava L.) is one of the most wasted agro-food products in Mexico. This motivated us to evaluate gasification of guava waste on dry biomass base under supercritical water conditions for the first time, with the aim of analyzing the impact of moderate temperatures and feed ratios as reaction parameters on gas products. Temperature was varied in the range of 673.15–773.15 K and using a batch reactor loaded with biomass:water (B:W) mass ratios of 1:1, 1:4, and 1:6. Furthermore, the obtained solid, liquid, and gas phase products were characterized. Hydrogen (H2), carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), ethane (C2H6), propane (C3H8), and butane (C4H10) were identified in gas phase and quantified by means of a gas chromatograph equipped with a TCD detector. Liquid and solid phase products were subjected to Fourier Transform Infrared spectroscopy analyses. This preliminary research indicated that high temperature operation and high biomass:water mass ratio enhanced gas yields (mol/kg) of about 4.137 for CH4, 6.705 for CO2, and 7.743 for H2; whereas the selectivity and gas efficiency for hydrogen was 65.26% and 58.94%, respectively.

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“…Nitrogen and oxygen were not detected. Besides, gas yields were calculated according to Equation (13); their values are presented in Table 4.…”

Section: Supercritical Water Gasificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Gasification of Psidium guajava L. Waste Using Supercritical Water: Evaluation of Feed Ratio and Moderate Temperatures

et al. 2021

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“…The particle–particle interaction, like particle–particle conduction, collision, friction, and clustering can significantly affect the pyrolysis reaction 13 . The gas–particle interaction, like drag force, heat, and mass transfer can affect the biomass particles hydrodynamics, residence time, and chemical reactions in the reactor 14‐18 . Also, the reactor geometry and operating conditions, like pressure and heating jacket temperature can affect pyrolyzer performance.…”

Section: Introductionmentioning

confidence: 99%

“…Different computational models have been developed to simulate biomass pyrolysis, including multifluid model, 19 CFD‐DEM model, 16 and multiphase particle in cell model 20 . However, the biomass particles were assumed to be isothermal in most of the reactor scale models.…”

Section: Introductionmentioning

confidence: 99%

Coupling particle scale model and SuperDEM‐CFD for multiscale simulation of biomass pyrolysis in a packed bed pyrolyzer

Gao

Rogers

2021

AIChE Journal

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An efficient biomass pyrolysis process requires a comprehensive understanding of the chemical and physical phenomena that occur at multi‐length and time scales. In this study, a multiscale computational approach was developed and validated for biomass pyrolysis in a packed‐bed reactor by integrating pyrolysis kinetics, a particle scale model, and Superquadric Discrete Element Method‐Computational Fluid Dynamics (SuperDEM‐CFD) in open‐source code MFiX. A one‐dimensional particle–scale model that discretizes the characteristic length of biomass particle into layers was developed to predict the intraparticle phenomena inside a single particle. The 1D model was validated by comparing it with a single biomass particle pyrolysis experiment. A recently developed SuperDEM‐CFD model was employed to simulate the non‐spherical particle–particle contact and fluid‐particle interaction. The coupled model was applied to simulate the pyrolysis of cubic biomass particles in a packed bed and validated by comparing with experimental data. Simulation with and without particle–scale model was compared, and the effect of the gas–solid heat transfer models was also investigated.

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Numerical study of biomass gasification combined with CO₂ absorption in a bubbling fluidized bed

et al. 2023

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Biomass gasification combined with CO 2 absorption-enhanced reforming (AER) in a bubbling fluidized bed (BFB) reactor is numerically studied via the multiphase particle-in-cell (MP-PIC) method featuring thermochemical and polydispersity submodels. A novel bubble detection algorithm is proposed for efficiently characterizing bubble morphology. The effects of several crucial operating parameters on the microscale particle behaviors, mesoscale bubble dynamics, and macroscale reactor performance of the AER gasification process are analyzed. Compared with conventional gasification, AER gasification reduces the CO 2 concentration by 33.58% but elevates the H 2 concentration by 32.13%. Higher operating temperature and steam-tobiomass (S/B) ratio promote H 2 generation but deteriorate gasification performance.A lower operating pressure improves gas-solid contact efficiency and gasification performance as the increased operating pressure inhibits bubble dynamics and particle kinematics. Compared with pure sand as bed material, the mixed bed material (CaO:sand = 1:1) significantly improves gasification performance by enhancing H 2 generation and CO 2 removal.

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CFD-DEM coupled with thermochemical sub-models for biomass gasification: Validation and sensitivity analysis

Cited by 146 publications

References 77 publications

Gasification of Psidium guajava L. Waste Using Supercritical Water: Evaluation of Feed Ratio and Moderate Temperatures

Gasification of Psidium guajava L. Waste Using Supercritical Water: Evaluation of Feed Ratio and Moderate Temperatures

Coupling particle scale model and SuperDEM‐CFD for multiscale simulation of biomass pyrolysis in a packed bed pyrolyzer

Numerical study of biomass gasification combined with CO₂ absorption in a bubbling fluidized bed

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CFD-DEM coupled with thermochemical sub-models for biomass gasification: Validation and sensitivity analysis

Cited by 146 publications

References 77 publications

Gasification of Psidium guajava L. Waste Using Supercritical Water: Evaluation of Feed Ratio and Moderate Temperatures

Gasification of Psidium guajava L. Waste Using Supercritical Water: Evaluation of Feed Ratio and Moderate Temperatures

Coupling particle scale model and SuperDEM‐CFD for multiscale simulation of biomass pyrolysis in a packed bed pyrolyzer

Numerical study of biomass gasification combined with CO2 absorption in a bubbling fluidized bed

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Numerical study of biomass gasification combined with CO₂ absorption in a bubbling fluidized bed