Prediction of Conveying Resistance for a Novel Hydraulic-mechanical Hybrid Vertical Lifting System

Abstract

Objective: Recently a novel hydraulic-mechanical hybrid vertical lifting system was proposed for deep-sea mining. Accurate prediction of conveying resistance is important for the engineering design of the system. Plug flow of coarse particles is the main flow regime in the system. So far rare attention has been paid to the pressure drop prediction of plug flow of coarse particles. This paper aims to investigate eight theoretical pressure drop models on the applicability to predict the pressure drop of plug flow. Methods: Eight theoretical pressure drop models were studied. In addition, a hydraulic-mechanical hybrid vertical lifting test setup was developed. The novelty of this experimental work is that plug flow of coarse particles is formed and the lifting force of the plug can be measured with the test setup. Tests were conducted with varying particle sizes, lifting speeds and plug weights. The particle size is varied among 13, 18, and 25mm. The lifting speed is varied from 0.02m/s to 0.1m/s. The plug weight varies from 5 to 10kg. The range of Reynolds number for the tested particles is between 208 and 2,000. Results: Prediction errors of eight pressure drop models are derived and compared with the experimental data collected during this study. It was found that similar prediction trends are observed for all pressure drop models under most test conditions. Except the Rose model, all models produce average prediction errors less than 15%. The average prediction error for the Rose model is 20.59%. The average prediction error for the Ergun model is 12.43%. Conclusion: From this study it can be seen that the Ergun model produces the smallest prediction error among the eight selected pressure drop models for the given experimental conditions. Therefore, the Ergun model is considered to be most applicable for the calculation of the conveying resistance for the proposed vertical lifting system.