Airflow versus pressure drop for a mixture of bulk wood chips and bark at different moisture contents

Grubecki, I.

doi:10.1016/j.biosystemseng.2015.08.008

Cited by 13 publications

(5 citation statements)

References 48 publications

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“…The characterization results express a functional relationship between 6 the physical properties and flowability of biomass particles. In particular, results for the dimensions and shape of biomass particles may be used to predict the pressure drop within a bed of ground particles [25]. The outcomes of this study will help towards using more precise input information in modeling the thermochemical conversion of single particles, as well as the design and optimization of the feeding system in power plants.…”

Section: Objectivesmentioning

confidence: 99%

“…Comprehensive information about the actual size, shape and density of biomass particles is crucially important in the industrial application that handle the particulate materials. Predicting the pressure drop across a bed of particles is one example of the applications [25]. Hoppers, screws, pneumatic transportation in pipelines and feeding systems in thermochemical conversion processes are other examples.…”

Section: Introductionmentioning

confidence: 99%

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Size, shape and flow characterization of ground wood chip and ground wood pellet particles

et al. 2016

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Section: Objectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Size, shape and flow characterization of ground wood chip and ground wood pellet particles

et al. 2016

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“…To describe the hydrodynamics behavior of fluidizing systems, the Ergun equation has been widely used for predicting the Δ P / H profile as a function of particle properties, and U g varied from the fixed bed to fluidized bed. There are several studies on fine-tuning the Ergun equation by changing the two constant values: a 1 and a 2 in eq or deriving a new correlation with their solid properties. ,, Δ P H = a 1 ρ g u g 2 ⌀ d p ( 1 − ε ) ε 3 + a 2 μ u g ⌀ 2 d p 2 ( 1 − ε ) 2 ε 2 where a 1 and a 2 are 1.75 and 150 for the conventional Ergun equation, respectively. It was found that the Ergun equation did not adequately predict the hydrodynamic behavior in the developing region.…”

Section: Resultsmentioning

confidence: 99%

“…There are several studies on fine-tuning the Ergun equation by changing the two constant values: a 1 and a 2 in eq 1 or deriving a new correlation with their solid properties. 40,65,66…”

Section: Model Evaluationmentioning

confidence: 99%

Hydrodynamics Behavior of Ternary Biomass Mixtures with Silica Sand in Fluidized Beds: Experiment and Artificial Neural Network Model Development

Soanuch,

Pareek,

Piumsomboon

et al. 2023

Ind. Eng. Chem. Res.

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Understanding the hydrodynamic behavior of irregular-shaped particles is vital for optimizing fluidized bed systems. In this study, the effect of binary and ternary biomass mixtures of silica sand in a gas–solid fluidized bed on pressure drop (ΔP/H) profiles was investigated experimentally as a function of superficial gas velocity (U g). It was observed that using a mixture of particles increases the overall complexity of the system. The experimental results were also used to develop an artificial neural network (ANN) model. The five dimensionless parameters were used to train the network with the expected output of the ΔP/H profiles. The statistical analyses were used to compare the performance of the model between one and two hidden layers. The results showed that the ANN model with only one hidden layer could accurately predict the fluidization behavior with an R 2 of 0.95.

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“…The observed changes in the fractional composition of the tested particles can be explained by the fact that at higher moisture content of the particles, an insufficient separation of MP occurs due to their adhesion to larger particles. Finer particles show the ability to agglomerate with the larger ones, which escalated with the increase in their moisture content [ 34 ].…”

Section: Resultsmentioning

confidence: 99%

Characterisation of Wood Particles Used in the Particleboard Production as a Function of Their Moisture Content

et al. 2021

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The properties of particleboards and the course of their manufacturing process depend on the characteristics of wood particles, their degree of fineness, geometry, and moisture content. This research work aims to investigate the physical properties of wood particles used in the particleboard production in dependence on their moisture content. Two types of particles currently used in the production of three-layer particleboards, i.e., microparticles (MP) for the outer layers of particleboards and particles for the core layers (PCL), were used in the study. The particles with a moisture content of 0.55%, 3.5%, 7%, 10%, 15%, and 20% were tested for their poured bulk density (ρp), tapped bulk density (ρt), compression ratio (k), angle of repose (αR), and slippery angle of repose (αs). It was found that irrespective of the fineness of the particles, an increase in their moisture content caused an increase in the angle of repose and slippery angle of repose and an increase in poured and tapped bulk density, while for PCL, the biggest changes in bulk density occurred in the range up to 15% of moisture content, and for MP in the range above 7% of moisture content, respectively. An increase in the moisture content of PCL in the range studied results in a significant increase in the compression ratio from 47.1% to 66.7%. The compression ratio of MP increases only up to 15% of their moisture content—a change of value from 47.1% to 58.7%.

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Airflow versus pressure drop for a mixture of bulk wood chips and bark at different moisture contents

Cited by 13 publications

References 48 publications

Size, shape and flow characterization of ground wood chip and ground wood pellet particles

Size, shape and flow characterization of ground wood chip and ground wood pellet particles

Hydrodynamics Behavior of Ternary Biomass Mixtures with Silica Sand in Fluidized Beds: Experiment and Artificial Neural Network Model Development

Characterisation of Wood Particles Used in the Particleboard Production as a Function of Their Moisture Content

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