空化
水锤
管道运输
压力降
机械
石油工程
下降(电信)
管道(软件)
流量(数学)
材料科学
海洋工程
工程类
机械工程
物理
作者
Changjun Li,Jie He,Wenlong Jia,Fan Yang,Jiuqing Ban,Bolin Qiu
标识
DOI:10.1016/j.petrol.2022.111241
摘要
Transient cavitating flow is a dangerous condition in the operation of large drop crude oil pipelines. Accurately predicting the high pressure generated by cavity collapse is the premise of analyzing and formulating pipeline safety management and control strategies. A new numerical simulation method for one dimension cavitating flow in crude oil pipelines considering the effect of unsteady friction was proposed. The unsteady friction (UF) term is coupled to the classical discrete gas cavity model (DGCM) for modeling the cavitating flow, and the proposed model is called UF-DGCM. The method of characteristics (MOC) is used to solve the UF-DGCM. The validity of the model has been verified with experimental data. The pipeline length of the two test cases is 37.23 m and 15.22 m, respectively, and the pipeline diameter is 22.1 mm and 20.0 mm, respectively. For the two test cases, the accuracy of the prediction results is improved by 6.7% and 4.4%, respectively. A case study of cavitating flow caused by pump shutdown in a pipeline with a length of 35 km and a diameter of 738 mm was performed using UF-DGCM, and the effects of water hammer wave speed, crude oil vapor pressure, and pump shutdown time on cavitating flow were analyzed. The results show that the maximum pressure peak is dependent on the water hammer wave speed. About the increase in the wave speed value of 200 m/s will lead to an increase in the maximum pressure head value of 10.1 m. The increase of pump shutdown time will inhibit the growth of cavities, and increasing the pump shutdown time by 4 s will shorten the existence time of cavities by about 3 s. The extension of the pump shutdown time will prevent cavitating flow. The proposed improved model is more suitable for transient cavitating flow analysis, and the results of flow parameters research will be helpful to prevent cavitating flow in crude oil pipelines.
科研通智能强力驱动
Strongly Powered by AbleSci AI