Experimental and numerical investigation of sands and Geldart A biomass co‐fluidization

Lu, Liqiang; Yu, Jia; Gao, Xi; Xu, Yupeng; Shahnam, Mehrdad; Rogers, William A.

doi:10.1002/aic.16969

Cited by 24 publications

(19 citation statements)

References 51 publications

(59 reference statements)

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“…The third drag model used in this research was derived for coarse grid simulation of small Geldart A particles by filtering fine grid simulation results 43 . It has been used to simulate the co‐fluidization of sands and Geldart A biomass particles 44 . Its formation is attached in Appendix B.…”

Section: Methodsmentioning

confidence: 99%

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Open source implementation of glued sphere discrete element method and nonspherical biomass fast pyrolysis simulation

Shahnam

Rogers

2021

AIChE Journal

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In this research, a glued-sphere discrete element method was implemented in the open-source, computational fluid dynamics software MFiX. The implementation was verified using a cylinder-wall collision and then validated by simulating the packing and fluidization of nonspherical particles. The validated code was applied to simulate fast pyrolysis of nonspherical biomass particles in a bubbling fluidized bed. The glued sphere occupancy ratio was proposed to quantify the quality of shape resolution using glued sphere. Shape resolution showed significant influence on the packing height in the simulation of particle packing and an occupancy ratio of 80% was recommended. Its influence is minor in fully fluidized bed but can be eight times higher in packed bed. Three tested heat transfer models predicted similar yields of elongated biomass fast pyrolysis. The solver developed in this research can be used to simulate other multiphase reacting flows involving nonspherical particles.

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Section: Methodsmentioning

confidence: 99%

“…43 It has been used to simulate the co-fluidization of sands and Geldart A biomass particles. 44 Its formation is attached in Appendix B.…”

Section: Drag Modelsmentioning

confidence: 99%

Open source implementation of glued sphere discrete element method and nonspherical biomass fast pyrolysis simulation

Shahnam

Rogers

2021

AIChE Journal

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“…The fast pyrolysis of biomass was investigated using a multiscale approach, combining coarse-grain particle scale simulations with reactor scale modelling [91,92]; similarly, coarse grain DEM-CFD combined with reduced-order modelling was used to simulate a pilot-scale updraft coal gasification reactor [93]. Bubbling fluidization of a sand-biomass mixture was compared against experiment for degree of mixing and pressure drop (average and fluctuations) [94,95]. Different testing methods for measuring solids distribution have been compared and improved by simulating the so-called "travelling fluidized bed" [96].…”

Section: Bubbling/spouted/liquid Fluidized Bedsmentioning

confidence: 99%

Coarse-Grain DEM Modelling in Fluidized Bed Simulation: A Review

2021

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In the last decade, a few of the early attempts to bring CFD-DEM of fluidized beds beyond the limits of small, lab-scale units to larger scale systems have become popular. The simulation capabilities of the Discrete Element Method in multiphase flow and fluidized beds have largely benefitted by the improvements offered by coarse graining approaches. In fact, the number of real particles that can be simulated increases to the point that pilot-scale and some industrially relevant systems become approachable. Methodologically, coarse graining procedures have been introduced by various groups, resting on different physical backgrounds. The present review collects the most relevant contributions, critically proposing them within a unique, consistent framework for the derivations and nomenclature. Scaling for the contact forces, with the linear and Hertz-based approaches, for the hydrodynamic and cohesive forces is illustrated and discussed. The orders of magnitude computational savings are quantified as a function of the coarse graining degree. An overview of the recent applications in bubbling, spouted beds and circulating fluidized bed reactors is presented. Finally, new scaling, recent extensions and promising future directions are discussed in perspective. In addition to providing a compact compendium of the essential aspects, the review aims at stimulating further efforts in this promising field.

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“…Further investigation 19 showed that the Ganser correction 21 of the Gidaspow drag model 22 can be used to calculate the drag coefficient of non‐spherical biomass particles as it accounts for the influence of particle shapes. For coarse grid CFD simulations of Geldart‐A particles (biochar in this research), the unresolved sub‐grid structures can be accounted with the filtered drag model 23,24 that is a correction to the regular drag models such as the Wen‐Yu drag model. In this article, the filtered drag is coupled with the Ganser drag to address the influence of both unresolved sub‐grid structures and particle shapes.

β_{Ganser ‐ Filtered} goodbreak= β_{Ganser - Wen ‐ Yu} ((), 1 goodbreak- H_{Filtered})

where

β_{Ganser ‐ Filtered}

is the drag coefficient combines sub‐grid correction and non‐spherical correction.…”

Section: Computational Fluid Dynamic Modelsmentioning

confidence: 99%

Experiment and computational fluid dynamics investigation of biochar elutriation in fluidized bed

Rowan

et al. 2021

AIChE Journal

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In fluidized bed biomass fast pyrolysis, the biomass is converted to biochar and elutriated. The elutriation rate is a key parameter in reactor designs and operations. This research presents a video‐based continuous measurement of biochar elutriation rate in a fluidized bed with sands and biomass as bed materials. The fluidized bed is simulated with the computational fluid dynamics—coarse‐grained discrete element method (CFD‐CGDEM) in MFiX. The fluidization behavior of nonspherical sands can be more accurately captured when a rolling friction model is used. The predicted elutriation rate is close to the experimental measurement when the particle size distributions are considered and the filtered drag with a shape correction is used. These results validated the accuracy of the MFiX‐based CFD framework for the prediction of biochar elutriations in the fluidized bed biomass fast pyrolysis reactor.

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Experimental and numerical investigation of sands and Geldart A biomass co‐fluidization

Cited by 24 publications

References 51 publications

Open source implementation of glued sphere discrete element method and nonspherical biomass fast pyrolysis simulation

Open source implementation of glued sphere discrete element method and nonspherical biomass fast pyrolysis simulation

Coarse-Grain DEM Modelling in Fluidized Bed Simulation: A Review

Experiment and computational fluid dynamics investigation of biochar elutriation in fluidized bed

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