Novel Pressure Drop Model for Packed Bed Contacting Devices

The pressure drop of fluid flow through packed bed contacting devices or reactors plays a significant role in designing and operating these contacting devices. Hence, during the past decades, many efforts have been made to propose semiempirical correlations for accurately estimating packed bed pressure drop. Nevertheless, the proposed relations could not predict the packed bed pressure drop satisfactorily and deviate significantly from experimental data. To overcome the shortcomings of previously reported relations, in this article, a comprehensive review of the pressure drop models has been conducted, and the strengths and weaknesses of the existing models have been discussed in detail. Then, a new tortuosity model has been developed. This model has been incorporated into a modified Ergun’s model to overcome the shortcomings of previously reported models. To adjust the parameters of the developed model, experimental investigation and computational fluid dynamics (CFD) simulation have been conducted to evaluate the pressure drop model predictions across the experimental setup. In addition, the developed model predictions have been compared against many experimental data reported in the literature, and excellent agreement has been obtained over particle Reynolds number values from 0.2 to 12,000 in the viscous and inertial flow regimes and various bed-to-particle diameter ratios. Moreover, the performance capability of the developed model has been assessed against the existing models reported in the literature, and we found that this model provides the best predictions over a wide range of particle Reynolds number values with the lowest root-mean-square error (RMSE) values.

Authors

Institutions

Publication Details

Journal
Industrial & Engineering Chemistry Research
Published
2025-08-19
DOI
https://doi.org/10.1021/acs.iecr.5c02425
Primary Topic
Granular flow and fluidized beds
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Novel Pressure Drop Model for Packed Bed Contacting Devices

Asghar Molaei Dehkordi, Mohammad Amin Ghayour Najafabadi
Industrial & Engineering Chemistry Research
Granular flow and fluidized beds
article

Novel Pressure Drop Model for Packed Bed Contacting Devices

Asghar Molaei Dehkordi, Mohammad Amin Ghayour Najafabadi
article en

Abstract

The pressure drop of fluid flow through packed bed contacting devices or reactors plays a significant role in designing and operating these contacting devices. Hence, during the past decades, many efforts have been made to propose semiempirical correlations for accurately estimating packed bed pressure drop. Nevertheless, the proposed relations could not predict the packed bed pressure drop satisfactorily and deviate significantly from experimental data. To overcome the shortcomings of previously reported relations, in this article, a comprehensive review of the pressure drop models has been conducted, and the strengths and weaknesses of the existing models have been discussed in detail. Then, a new tortuosity model has been developed. This model has been incorporated into a modified Ergun’s model to overcome the shortcomings of previously reported models. To adjust the parameters of the developed model, experimental investigation and computational fluid dynamics (CFD) simulation have been conducted to evaluate the pressure drop model predictions across the experimental setup. In addition, the developed model predictions have been compared against many experimental data reported in the literature, and excellent agreement has been obtained over particle Reynolds number values from 0.2 to 12,000 in the viscous and inertial flow regimes and various bed-to-particle diameter ratios. Moreover, the performance capability of the developed model has been assessed against the existing models reported in the literature, and we found that this model provides the best predictions over a wide range of particle Reynolds number values with the lowest root-mean-square error (RMSE) values.

Industrial & Engineering Chemistry ResearchVol. 64(34)
Sharif University of Technology (IR)
Sharif University of Technology
Openalex Percentile: Top 78%
Granular flow and fluidized beds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.