Review of vibration induced by gas-liquid two-phase flow inside pipes

被引:5
作者
Ding, Lin [1 ]
Fu, Yitong [1 ]
Li, Xiang [1 ,2 ]
Ran, Jingyu [1 ]
机构
[1] Chongqing Univ, Key Lab Low grade Energy Utilizat Technol & Syst, Minist Educ China, Chongqing, Peoples R China
[2] Aero Engine Corp China, Sichuan Gas Turbine Estab, Mianyang, Peoples R China
基金
中国国家自然科学基金;
关键词
Gas-liquid two phase flow; Flow-induced vibration; Two-phase flow excitation force; Pipe dynamic response; Noise; DRIFT-FLUX MODEL; HANGING FLEXIBLE RISER; PIPING STRUCTURE; NEURAL-NETWORKS; VOID FRACTION; SLUG FLOW; FORCES; BENDS; DIAMETER; BEHAVIOR;
D O I
10.1016/j.oceaneng.2024.120006
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Two-phase flow is a prevalent phenomenon encountered in engineering systems. In pipelines, the existence of two-phase flow introduces more intricate fluctuations in the excitation force compared to single-phase flow, leading to intensified vibrations known as Flow-Induced Vibration(FIV). FIV in pipelines with two-phase flow involves complex theoretical calculations, experiments, and simulations. This paper provides a comprehensive and detailed review of the internal gas-liquid two-phase FIV without phase change. It covers various aspects, including theoretical models, research methods, factors influencing FIV, factors influencing the dynamic response of pipes, and noise generated by internal two-phase flow. It presents the current frontiers of development in these fields, summarizes existing shortcomings, and outlines research prospects and future challenges. The latest research focuses on the construction of unsteady flow theoretical models, improving the tracking accuracy of phase interfaces, the application of VOF and two-fluid models in different flow patterns, and the application of machine learning. The primary challenge at present is to reduce the uncertainty in void fraction correlations and interphase relationship models; enhance the accuracy of phase interface simulations and effectively capture bubble dynamics in two-phase flow numerical models; and investigate the mechanisms of two-phase FIV coupled with external vortex-induced vibrations in long vertical pipes.
引用
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页数:23
相关论文
共 173 条
[1]   Application of artificial neural network to predict slug liquid holdup [J].
Abdul-Majeed, Ghassan H. ;
Kadhim, F. S. ;
Almahdawi, Falih H. M. ;
Al-Dunainawi, Yousif ;
Arabi, A. ;
Al-Azzawi, Waleed Khalid .
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW, 2022, 150
[2]  
Adegoke A.S., 2020, RES ENG STRUCT MAT J, V6, P207
[3]  
Adegoke A.S., 2020, J ENG RES, V24, P76
[4]  
Adegoke AS, 2017, MATH COMPUT APPL, V22, DOI 10.3390/mca22040044
[5]   X-Ray Flow Visualization in Multiphase Flows [J].
Aliseda, Alberto ;
Heindel, Theodore J. .
ANNUAL REVIEW OF FLUID MECHANICS, VOL 53, 2021, 53 :543-567
[6]   An artificial neural network model for the prediction of entrained droplet fraction in annular gas-liquid two-phase flow in vertical pipes [J].
Aliyu, Aliyu M. ;
Choudhury, Raihan ;
Sohani, Behnaz ;
Atanbori, John ;
Ribeiro, Joseph X. F. ;
Ahmed, Salem K. Brini ;
Mishra, Rakesh .
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW, 2023, 164
[7]   Two-phase flow pattern classification based on void fraction time series and machine learning [J].
Ambrosio, Jefferson dos Santos ;
Lazzaretti, Andre Eugenio ;
Pipa, Daniel Rodrigues ;
da Silva, Marco Jose .
FLOW MEASUREMENT AND INSTRUMENTATION, 2022, 83
[8]   Pattern recognition of two-phase liquid-gas flow by discriminant analysis applied to accelerometric signals [J].
Amoresano, A. ;
Langella, G. ;
Iodice, P. ;
Quaremba, G. .
PHYSICS OF FLUIDS, 2023, 35 (09)
[9]   Dynamic behavior of pipes conveying gas-liquid two-phase flow [J].
An, Chen ;
Su, Jian .
NUCLEAR ENGINEERING AND DESIGN, 2015, 292 :204-212
[10]  
[Anonymous], 1968, Unsteady Momentum Fluxes in Two-phase Flow and the Vibration of Nuclear Reactor Components