A new semi-empirical model for pressure drop prediction in a packed bed of smooth and rough particles: Derivation and verification

Новая полуэмпирическая модель прогноза падения давления в набитом слое из гладких и шероховатых частиц: вывод и верификация
Dmitry Pashchenko, H. M. Quinn
2026-01-01

Hypothetical Q-Channel (HQC)Quinn Fluid Flow Model (QFFM)fluid current (CQ)normalized dimensionless pressure gradient (PQ)wall normalization coefficient (λ)
The accurate prediction of pressure drop in packed beds is fundamental to numerous chemical, mechanical, and environmental engineering applications. While traditional models such as the Ergun equation and Reynolds number-based correlations have been widely employed, they suffer from inherent limitations and lack a unified framework bridging packed beds and empty conduits. This paper presents a comprehensive derivation of the Quinn Fluid Flow Model (QFFM), a novel theoretical framework developed from first principles. The QFFM establishes a universal linear relationship between the normalized dimensionless pressure gradient (PQ) and the fluid current (CQ), expressed as PQ=k1+k2CQ. A key innovation is the conceptualization of any closed conduit as a “packed conduit” via the Hypothetical Q-Channel (HQC) and the wall normalization coefficient (λ), which inherently incorporates the effects of tortuosity, viscous boundary layers, and surface roughness. By unifying the description of flow through packed beds, the new semi-empirical model offers a robust, physics-based alternative to conventional semi-empirical correlations, validated across diverse flow regimes and particle morphologies.
1
QFFM establishes a universal linear relationship between normalized dimensionless pressure gradient (PQ) and fluid current (CQ): PQ = k1 + k2 CQ.
2
QFFM unifies the description of flow in packed beds and empty conduits, offering a physics-based alternative to traditional semi-empirical correlations like the Ergun equation.
3
The Quinn Fluid Flow Model (QFFM) is derived from first principles, providing a novel theoretical framework for pressure drop prediction in packed beds.
4
The model introduces the Hypothetical Q-Channel (HQC) and wall normalization coefficient (λ) to treat any closed conduit as a 'packed conduit', incorporating tortuosity, viscous boundary layers, and surface roughness.
5
The semi-empirical model is validated across diverse flow regimes and particle morphologies, demonstrating robustness compared to conventional correlations.

Packed bed (and equivalently packed conduits) of smooth and rough particles with associated Hypothetical Q-Channel representation

Prediction and modelling of pressure drop / normalized dimensionless pressure gradient (PQ) as a linear function of fluid current (CQ) via the Quinn Fluid Flow Model, including effects of tortuosity, viscous boundary layers, wall normalization (λ), and surface roughness across flow regimes and particle morphologies

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2026-01-01
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Dmitry Pashchenko
H. M. Quinn
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