Three dimensional full-loop CFD simulation of hydrodynamics in a pilot-scale dual fluidized bed system for biomass gasification

Luo, Hao; Lin, Weigang; Song, Wenli; Li, Songgeng; Dam‐Johansen, Kim; Wu, Hao

doi:10.1016/j.fuproc.2019.106146

Cited by 38 publications

(9 citation statements)

References 48 publications

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“…At the same, researchers have used the numerical method to investigate the operating behaviour of the CLC system, which is difficult for experimental measurement [13,14], and it has played a more and more important role for investigating the CLC system [15][16][17]. Two main methods, two-fluid model and discrete element method (DEM), are utilized for simulating the CLC system [18][19][20]. With DEM, one can track the trajectory of each particle and get the information at particle scale.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of a 10 kW Gas-Fueled Chemical Looping Combustion Unit

et al. 2022

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Chemical looping combustion is one novel technology for controlling CO2 emission with a low energy cost. Due to a lack of understanding of the detailed and micro behavior of the CLC process, especially for a three dimensional structure, numerical simulations are carried out in this work. The configuration is built according to the experimental unit and gaseous fuel is used in this work. A two-fluid model considering heterogeneous reactions is established, and the flow behaviour and reaction characteristics are obtained. The temperature in the air reactor increases with height owing to the exothermic reaction of the xidation of the oxygen carrier, while the temperature in the fuel reactor decreases with height due to the endothermic reaction. The oxidation level of the oxygen carrier is obtained by simulation, which is hard for measurement, and the difference between the inlet and outlet is 0.065. The influences of the operating temperature and injection rate of fuel are presented to understand the performance of the system. The highest fuel conversion rate reaches 0.92 under high operating temperature. The numerical results are helpful for acquiring insight on the flow and reactive behaviour of CLC reactors.

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Section: Introductionmentioning

confidence: 99%

Numerical Simulation of a 10 kW Gas-Fueled Chemical Looping Combustion Unit

et al. 2022

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“…The effects of the solids inventory and the configuration of gasifier‐riser connection on the system hydrodynamics were also investigated. Likewise, Luo et al 22 carried out experiments and simulations on a pilot‐scale DFBG system to study the influence of solid inventory on the system hydrodynamics. Concerning this issue, Zou et al 23 analyzed the hydrodynamics and the loop‐seal characteristics of a DFB cold flow system with continuous feeding and discharging of solids by conducting both experiments and three‐dimensional (3D) computational fluid dynamics (CFD) simulation.…”

Section: Introductionmentioning

confidence: 99%

Effect of sand particle size on the hydrodynamics of a dual fluidized bed cold flow system applied for waste‐to‐energy gasifiers

Dinh

Hsiau

et al. 2022

Intl J of Energy Research

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Summary Since the dual fluidized bed (DFB) system has been increasingly adopted for waste‐to‐energy gasification, a three‐dimensional computational fluid dynamics full‐loop model of a DFB cold flow system has been developed to predict the pressure and sand circulation rate (SCR) under various operating conditions. The pressure data were recorded at 18 specified points along the system height. In addition, the SCRs were determined at the two crucial positions connecting the riser and the gasifier and vice versa. The simulation results were then validated against the experimental data, taking into account the effects of the sand particle size (ds), the air inlet velocity in the riser (v0,riser), and the initial gasifier bed height (h0,gasifier). It could be observed in the riser that the flow structures of the smaller ds(s) were almost scattering patterns, while those of the bigger ones were mainly clusters. Compared with bigger ds(s), more homogeneous pressure distributions in the riser and higher bed expansion in the gasifier were obtained with smaller ones. A compromise between the system performance and pre‐treating cost for the feedstock particle sizes should be considered further to achieve the best system performance. On the other hand, the increases of the v0,riser and the h0,gasifier enhanced the gasifier bed pressure, facilitating the downward sand flow back to the riser via the LLS. Although some minor discrepancies existed between the simulation and experimental data, the predicted tendencies agreed well with the measured ones. It was also found that a system operating with ds = 500 μm, at v0,riser = 4.0 m/s and h0,gasifier = 0.25 m yielded stable flow characteristics and optimal global SCR. Moreover, some unexpected phenomena predicted and verified with the experimental observations could be avoided or minimized using suitable particle sizes of the feedstock and operating parameters. In sum, the better validation results with lower errors than our previous study, the more reasonable air‐sand flow patterns, and the substantial predictions of undesirable problems are the significant improvements of this study, providing valuable information for effectively designing and operating the practical DFB hot flow systems. Novelty Statement This study developed a 3D computational fluid dynamics full‐loop model of a DFB cold flow system for predicting the pressure and sand circulation rates under various operating conditions of particle size, inlet velocity, and initial bed height. The better validation results against the experimental data, the more reasonable air‐sand flow patterns, and the substantial predictions of undesirable problems are the significant improvements of this study, providing helpful information for designing and operating the DFB hot flow gasifiers.

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“…To overcome challenges regarding increasing carbon concentration and climate change, renewable energies like biomass, solar radiations and wind have been encouraged to be used because they do not emit greenhouse gases such as carbon dioxide, which plays an important function in global warming [1][2][3][4]. Recently, the interest in biofuels/biomass has grown because of the extensive consideration of sustainable sources of energy [5][6][7]. Biomass has many advantages over fossil fuels as it is a widely available source of energy, less expensive than fossil fuels and helps prevent climate change by reducing GHG [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Hydrogen Production by Applying Biomass Gasification: Artificial Neural Network Modeling Approach

et al. 2021

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In order to accurately anticipate the proficiency of downdraft biomass gasification linked with a water–gas shift unit to produce biohydrogen, a model based on an artificial neural network (ANN) approach is established to estimate the specific mass flow rate of the biohydrogen output of the plant based on different types of biomasses and diverse operating parameters. The factors considered as inputs to the models are elemental and proximate analysis compositions as well as the operating parameters. The model structure includes one layer for input, a hidden layer and output layer. One thousand eight hundred samples derived from the simulation of 50 various feedstocks in different operating situations were utilized to train the developed ANN model. The established ANN in the case of product biohydrogen presents satisfactory agreement with input data: absolute fraction of variance (R2) is more than 0.999 and root mean square error (RMSE) is lower than 0.25. In addition, the relative impact of biomass properties and operating parameters on output are studied. At the end, to have a comprehensive evaluation, variations of the inputs regarding hydrogen-content are compared and evaluated together. The results show that almost all of the inputs show a significant impact on the smhydrogen output. Significantly, gasifier temperature, SBR, moisture content and hydrogen have the highest impacts on the smhydrogen with contributions of 19.96, 17.18, 15.3 and 10.48%, respectively. In addition, other variables in feed properties, like C, O, S and N present a range of 1.28–8.6% and proximate components like VM, FC and A present a range of 3.14–7.67% of impact on smhydrogen.

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Three dimensional full-loop CFD simulation of hydrodynamics in a pilot-scale dual fluidized bed system for biomass gasification

Cited by 38 publications

References 48 publications

Numerical Simulation of a 10 kW Gas-Fueled Chemical Looping Combustion Unit

Numerical Simulation of a 10 kW Gas-Fueled Chemical Looping Combustion Unit

Effect of sand particle size on the hydrodynamics of a dual fluidized bed cold flow system applied for waste‐to‐energy gasifiers

Modeling of Hydrogen Production by Applying Biomass Gasification: Artificial Neural Network Modeling Approach

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