新型液压机械混合垂直提升系统的输送阻力预测

Xiangwei Liu, Shuhao Yang
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摘要

目的:最近提出了一种用于深海采矿的新型液压机械混合垂直提升系统。准确预测输送阻力对系统的工程设计非常重要。粗颗粒的堵塞流是系统中的主要流态。迄今为止,人们很少关注粗颗粒堵塞流的压降预测。本文旨在研究八种理论压降模型对塞流压降预测的适用性。研究方法研究了八个理论压降模型。此外,还开发了一套液压机械混合垂直升降试验装置。这项实验工作的新颖之处在于形成了粗颗粒的堵塞流,并可通过测试装置测量堵塞的提升力。试验采用了不同的颗粒大小、提升速度和塞子重量。颗粒大小在 13、18 和 25 毫米之间变化。提升速度从 0.02m/s 到 0.1m/s 不等。塞子重量从 5 千克到 10 千克不等。测试颗粒的雷诺数范围在 208 到 2,000 之间。结果得出了八个压降模型的预测误差,并与本研究中收集的实验数据进行了比较。结果发现,在大多数测试条件下,所有压降模型都有类似的预测趋势。除 Rose 模型外,所有模型产生的平均预测误差都小于 15%。Rose 模型的平均预测误差为 20.59%。Ergun 模型的平均预测误差为 12.43%。结论从本研究中可以看出,在给定的实验条件下,所选的八个压降模型中,Ergun 模型产生的预测误差最小。因此,Ergun 模型被认为最适用于计算拟议垂直提升系统的输送阻力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Conveying Resistance for a Novel Hydraulic-mechanical Hybrid Vertical Lifting System
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.
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