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.
Nikitin et al. (Fri,) studied this question.