Development of a semi-empirical dry pressure drop model for single rotor rotating packed beds across multiple packing types

Rotating packed beds (RPBs) offer substantial process intensification potential, but their industrial application is limited by the lack of reliable and transferable pressure drop correlations. Most existing models are packing-specific or restricted to narrow operating ranges. In this study, dry pressure drop was measured for five geometrically distinct packings that have not been previously investigated, over gas flow rates of 10-50 LPM and rotational speeds of 300-1200 rpm. To enhance the applicability of the pressure drop model across different packing types, a geometric shape correction function was introduced to account for particle-level and bed-level geometric effects. Model parameters were identified using three regression strategies: (i) packing-specific models, which achieved average relative errors of 9.7-13.3%; (ii) a unified correlation, which maintained comparable overall accuracy with an error of 10.7%; and (iii) a generalized model, calibrated using four packings, which achieved a training error of 10.8% and predicted an excluded packing with a deviation of 9.9%, confirming robust extrapolation performance. These results confirm that dry pressure drop in RPBs is governed by the coupled effects of gas flow rate, rotational speed, and packing geometry, and that partial unification across diverse packings is achievable within a physically transparent framework. The experimental dataset and modeling approach provide a robust basis for comparative packing assessment and for future development of more transferable correlations. It should be noted that the present model was developed for dry conditions using a single rotor geometry; direct extrapolation to other rotor sizes or wet operation requires further validation.