Linking micro‐scale predictions of capillary forces to macro‐scale fluidization experiments in humid environments

LaMarche, Casey Q.; Miller, A. Woodruff; Liu, Peiyuan; Hrenya, Christine M.

doi:10.1002/aic.15281

Cited by 38 publications

(45 citation statements)

References 74 publications

(156 reference statements)

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“…70,74 The coefficient of kinetic (sliding) friction, l k , is another important modeling parameter in DEM models. To restrict particle rotation, 75 l k is measured with particle sleds: four particles glued to the corners of a small, thin glass plate (microscope slide). Each sled is released cleanly from the top of an inclined plane in a humidity controlled box 75 maintained at approximately 20% relative humidity (RH).…”

Section: Particle Characterizationmentioning

confidence: 99%

“…To restrict particle rotation, 75 l k is measured with particle sleds: four particles glued to the corners of a small, thin glass plate (microscope slide). Each sled is released cleanly from the top of an inclined plane in a humidity controlled box 75 maintained at approximately 20% relative humidity (RH). The DVC highspeed camera is set up perpendicular to the inclination angle to record the motion of the sleds which is aided by the use of UV paint a black light.…”

Section: Particle Characterizationmentioning

confidence: 99%

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Experimental data for code validation: Horizontal air jets in a semicircular fluidized bed of Geldart Group D particles

et al. 2018

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Experiments were conducted with 6 mm plastic beads (Geldart Group D) in a semi‐circular, gas‐fluidized bed with side jets. Attention was paid to particle characterization and bed measurements, making the resulting dataset ideal for CFD‐DEM validation and uncertainty quantification. The bed was operated slightly above and below the minimum fluidization velocity, with additional fluidization provided by one of two pairs of opposing jets located above the distributor near the flat, front face of the unit. Care is taken to report material properties and bed conditions with either measured distribution functions or uncertainty bounds. High‐speed video imaging and particle tracking velocimetry are used to extract bin‐averaged velocity profiles, which are used to extract jet penetration depths. The time‐averaged mean and standard deviation of the bed pressure drop is also reported. Finally, the lower jets are also inserted into the bed until the opposing jets merge to form a spout‐like pattern. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2351–2363, 2018

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Section: Particle Characterizationmentioning

confidence: 99%

Section: Particle Characterizationmentioning

confidence: 99%

Experimental data for code validation: Horizontal air jets in a semicircular fluidized bed of Geldart Group D particles

et al. 2018

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“…70 Following the same procedure described above, we estimate the two parameters (F c,max ) and (D c ) for the corresponding square-force cohesion model, as shown in Figure 7. The cohesion among these particles under a relative humidity of 80% is modeled by a rigorous capillary force model detailed in our recent work.…”

Section: Parameter Evaluations For the Square-force Cohesion Model VImentioning

confidence: 99%

“…The cohesion among these particles under a relative humidity of 80% is modeled by a rigorous capillary force model detailed in our recent work. 70 Following the same procedure described above, we estimate the two parameters (F c,max ) and (D c ) for the corresponding square-force cohesion model, as shown in Figure 7. The defluidization curve based on the square-force cohesion model is plotted along with that using the rigorous capillary force model in Figure 8, where good agreement is again observed, demonstrating the robustness of the proposed extraction method.…”

Section: Parameter Evaluations For the Square-force Cohesion Model VImentioning

confidence: 99%

“…Estimation of the input values for the squareforce cohesion model using the defluidization curve in CFD-DEM simulations based on a rigorous capillary force model 70. Bottom plot: extraction of the estimated maximum cohesive force F c,max,Cap,est by mapping the normalized packed bed pressure drop Dp Ã pb on a fifth order polynomial fitting of the variation of Dp Ã pb with F c,max (red solid line).…”

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A square‐force cohesion model and its extraction from bulk measurements

et al. 2018

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Accurate modeling of interparticle forces in DEM is critical to predicting the rheology of cohesive particles. Rigorous cohesion models usually include parameters associated with particle surface roughness. However, both roughness measurement and its distillation into appropriate model parameters remain challenging. We propose a square‐force cohesion model, where cohesive force remains constant until a cutoff separation, above which cohesion vanishes. We demonstrate the square‐force model is a valid surrogate of more rigorous models. Specifically, when two parameters of square‐force model are chosen to match the two key quantities governing dense and dilute flows, namely maximum cohesive force and critical cohesive energy, respectively, DEM results using square‐force and more rigorous models show good agreement. For practical application of the square‐force model to lightly cohesive systems, a method is established to extract its parameters via defluidization, enabling determination of particle–particle cohesion from simpler bulk measurements than complicated and expensive scans on individual grains. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2329–2339, 2018

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Cohesive grains: Bridging microlevel measurements to macrolevel flow behavior via surface roughness

et al. 2016

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SignificanceUnderstanding fine-particle flows relies on van der Waals cohesion modeling, requiring a method to consider measured surface roughness. A robust scheme to extract roughness parameters from AFM surface maps, achieving accurate predictions of microscale measured cohesion is proposed. Macroscale quantitative agreement is demonstrated by comparing defluidization predictions to measurements, which are sensitive to cohesion and system-size independent. Agreement in both microscale and macroscale comparisons highlights the role of individual particle properties on bulk granular systems.

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Linking micro‐scale predictions of capillary forces to macro‐scale fluidization experiments in humid environments

Cited by 38 publications

References 74 publications

Experimental data for code validation: Horizontal air jets in a semicircular fluidized bed of Geldart Group D particles

Experimental data for code validation: Horizontal air jets in a semicircular fluidized bed of Geldart Group D particles

A square‐force cohesion model and its extraction from bulk measurements

Cohesive grains: Bridging microlevel measurements to macrolevel flow behavior via surface roughness

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