Modified Ergun Equation for Airflow through Packed Bed of Loblolly Pine Grinds

Olatunde, Gbenga; Fasina, Oladiran

doi:10.14356/kona.2019003

Cited by 10 publications

(2 citation statements)

References 19 publications

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“…Geldart's classification, particle shape, etc.) (Olatunde and Fasina 2019;Ozahi, Gundogdu, and Carpinlioglu 2008). As the coefficients are increased, both bed pressure drop and fluid drag change proportionally, which is clearly illustrative with increased particle circulation with modified coefficients.…”

Section: Effect Of the Fluid Drag Correlationmentioning

confidence: 77%

Circulating fluidized bed reactors – part 01: analyzing the effect of particle modelling parameters in computational particle fluid dynamic (CPFD) simulation with experimental validation

Bandara

Thapa

Nielsen

et al. 2019

Particulate Science and Technology

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A CPFD hydrodynamic model was developed for a circulating fluidized bed system and the simulation results were validated against experimental data based on particle circulation rate. Sensitivity of the computational mesh was primarily tested and extended grid refinement was needed at the loopseal to match the particle circulation rate with experimental data. The particle circulation rate was independent of the range of number of computational particles used in this study. A 10% reduction of the particle circulation rate was observed as the particle-wall interaction parameter was changed from 0.85 to 0.55 and 17% increment when the close-packed volume fraction was changed from 0.56 to 0.62. The pressure constant in the particle stress model showed the greatest impact for the circulation rate with 57% increment as the constant was changed from 2.5 to 5. The highest absolute variation in the pressure was observed at the loop seal and pressure values were under predicted in all sections. HIGHLIGHTS CPFD simulations are efficient in analyzing fluidized bed systems. Manipulating of particle circulation rate is important in circulating fluidized bed. Pressure constant in particle stress model is the most influential factor. Uncertainties should be minimized prior to optimization of model parameters.

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Section: Effect Of the Fluid Drag Correlationmentioning

confidence: 77%

Circulating fluidized bed reactors – part 01: analyzing the effect of particle modelling parameters in computational particle fluid dynamic (CPFD) simulation with experimental validation

Bandara

Thapa

Nielsen

et al. 2019

Particulate Science and Technology

View full text Add to dashboard Cite

show abstract

“…Geometrical lengths, pressure monitoring locations, particle size distribution and the assumption of spherical particles can be other physical uncertainties for the deviated pressure readings. Olatunde, and Fasina (2019) have mentioned the observed deviations related to coefficients of Ergun equation for different particles. The laminar viscous coefficient has reported to as high as 267 while the turbulent coefficient up to 4.02.…”

Section: Resultsmentioning

confidence: 99%

Analyzing the Effects of Geometrical and Particle Size Uncertainty in Circulating Fluidized Beds using CPFD Simulation

Bandara

Moldestad

Eikeland

2020

Linköping Electronic Conference Proceedings

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Computational fluid dynamic modeling and simulation is becoming a useful tool in the detailed analysis of multiphase flow systems. The level of uncertainty is different depending on selected modeling concept and numerical schemes. Physical uncertainties originated from geometrical dimensions and particle properties are important aspects. In this work, CPFD method was used to analyze the effect of dimensional uncertainty of loopseal pipe diameter and particle size distribution in a circulating fluidized bed. Five different pipe diameters were studied and 20% growth in particle circulation rate was observed as the diameter reduced from 30mm to 26mm. The effect of small changes in the particle size distribution was negligible and the particle circulation rate decreased by 32% with monodisperse particles of mean size.

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Fluid flow through 3D-printed particle beds: a new technique for understanding, validating, and improving predictability of permeability from empirical equations

et al. 2020

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The application of 3D technology for fabrication of artificial porous media samples improves porous media flow studies. The geometrical characteristics of a porous media pore channel: the channel shape, size, porosity, specific surface, expansion ratio, contraction ratio, and the tortuous pathway of the channel can be controlled through advanced additive manufacturing techniques (3D printing), computed tomography imagery (CT imaging) and image analysis methods. These 3D technologies have here been applied to construct and analyze four homogeneous porous media samples with predefined geometrical properties that are otherwise impossible to construct with conventional methods. Uncertainties regarding the geometrical properties are minimized because the 3D-printed porous media samples can be evaluated with CT imaging after fabrication. It is this combination of 3D technology that improves the data acquisition and data interpretation and contributes to new insight into the phenomenon of fluid flow through porous media. The effects of the individual geometrical properties on the fluid flow are then accounted for in permeability experiments in a Hassler flow cell. The results of the experimental work are used to test the theoretical foundation of the Kozeny–Carman equation and the extended version known as the Ergun equation. These equations are developed from analogies to the Hagen–Poiseuille flow equation. Based on the results from the laboratory experiments in this study, an analytical equation based on the analytical Navier–Stokes equations is presented as an alternative to the Hagen–Poiseuille analogy for porous media channels with non-uniform channel geometries. The agreement between experiment and the new equation reveals that the dissipating losses of mechanical energy in porous media flows are not a result of frictional shear alone. The mechanical losses are also a result of pressure dissipation that arise due to the non-uniformity of the channel geometry, which induced spatial variations to the strain rate field and induce acceleration of the velocity field in the flow through the porous medium. It is this acceleration that causes a divergence from linear flow conditions as the Stokes flow criterion (Re ≪ 1) is breached and causes the convective acceleration term to affect the flow behavior. The suggested modifications of theory and the presented experiments prove that the effects of surface roughness (1) do not alter the flow behavior in the Darcy flow regime or (2) in the Forchheimer flow regime. This implies that the flow is still laminar for the Forchheimer flow velocities tested.

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Modified Ergun Equation for Airflow through Packed Bed of Loblolly Pine Grinds

Cited by 10 publications

References 19 publications

Circulating fluidized bed reactors – part 01: analyzing the effect of particle modelling parameters in computational particle fluid dynamic (CPFD) simulation with experimental validation

Circulating fluidized bed reactors – part 01: analyzing the effect of particle modelling parameters in computational particle fluid dynamic (CPFD) simulation with experimental validation

Analyzing the Effects of Geometrical and Particle Size Uncertainty in Circulating Fluidized Beds using CPFD Simulation

Fluid flow through 3D-printed particle beds: a new technique for understanding, validating, and improving predictability of permeability from empirical equations

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