Flow through packed beds: Experimental and numerical validation of the Quinn fluid flow model
Течение через засыпные слои: экспериментальная и численная валидация модели течения жидкости Куинна
2025-08-01
SCID: 54.1/45aam8pa
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Ergun equationQFFMQuinn fluid flow modelcomputational fluid dynamicsfluid current (CQ)laminar, transient, and turbulent regimesnormalized dimensionless pressure gradient (PQ)packed beds pressure dropparticle-resolved simulationsrecirculating flow loop experiments
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Abstract (AI)
This study presents the experimental and numerical validation of the Quinn fluid flow model (QFFM), a novel theoretical framework for predicting pressure drop in packed beds and closed conduits. The QFFM, derived from first principles, establishes a universal linear relationship between the normalized dimensionless pressure gradient (PQ) and fluid current (CQ), expressed as PQ=k1+k2CQ. The model bridges the gap between empirical correlations and particle-resolved simulations, offering an approach for both empty and particle-packed systems. Experimental validation was conducted using a recirculating flow loop with precise pressure and temperature measurements, while numerical simulations employed high-fidelity computational fluid dynamics model. Numerical tests were conducted for a wide range of operational and design parameters of the packed beds for two types of fluid: water and air. Results demonstrate excellent agreement between QFFM predictions and experimental data across laminar, transient, and turbulent flow regimes, with discrepancies below 3.7%. The QFFM outperforms traditional models like the Ergun equation by inherently accounting for tortuosity and microscale flow phenomena. This work highlights the model's potential for optimizing industrial packed-bed systems, providing a useful tool for engineers and researchers.
Key Findings
1
Experimental validation using a recirculating flow loop and high-fidelity CFD simulations for water and air show QFFM predictions agree with data across laminar, transient, and turbulent regimes within 3.7% discrepancy.
2
Numerical tests covered a wide range of operational and design packed-bed parameters, confirming QFFM robustness for different conditions and fluids.
3
QFFM is derived from first principles and bridges empirical correlations with particle-resolved simulations, applicable to empty and particle-packed systems.
4
QFFM outperforms traditional models like the Ergun equation by inherently accounting for tortuosity and microscale flow phenomena, improving pressure-drop prediction.
5
The Quinn fluid flow model (QFFM) establishes a universal linear relation PQ = k1 + k2 CQ between normalized dimensionless pressure gradient and fluid current for packed beds and closed conduits.
Research Object
Packed beds and closed conduits with flowing fluids (water and air) used to validate the Quinn fluid flow model
Research Subject
Validation of the Quinn fluid flow model (QFFM) predicting normalized dimensionless pressure gradient vs. fluid current (PQ = k1 + k2 CQ), i.e., model accuracy in predicting pressure drop across laminar, transient, and turbulent regimes and its comparison to traditional models
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2025-08-01
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Cited by3
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Computational fluid dynamics simulations of fluid flow through the packed beds: A study of contact point treatments2025
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