Vibration response of a pipe subjected to two-phase flow: Analytical formulations and experiments

• Published in: Nuclear engineering and design 2017-03, Vol.313, p.214-224
• Main Authors: Ortiz-Vidal, L. Enrique, Mureithi, Njuki W., Rodriguez, Oscar M.H.
• Format: Article
• Language: English
• Subjects: Dispersion; Flow generated vibrations; Flow-induce vibration; Fluid mechanics; Formulations; Gas flow; Gas-liquid flow; Mathematical analysis; Multiphase flow; Pipe flow; Pipes; Predictions; Slug flow; Two-phase flow; Velocity; Vibration; Vibration measurement; Vibration response; Void fraction
• ISSN: 0029-5493; 1872-759X
• DOI: 10.1016/j.nucengdes.2016.12.020

•Analytical formulations for two-phase flow-induced vibration (2-FIV) are presented.•Standard deviation of acceleration pipe response is a function of the square of shear velocity.•Peak frequency is correlated to hydrodynamic mass and consequently to void fraction.•Dynamic pipe response increases with increasing mixture velocity and void fraction.•Hydrodynamic mass in 2-FIV in horizontal pipe is proportional to mixture density. This paper treats the two-phase flow-induced vibration in pipes. A broad range of two-phase flow conditions, including bubbly, dispersed and slug flow, were tested in a clamped-clamped straight horizontal pipe. The vibration response of both transversal directions for two span lengths was measured. From experimental results, an in-depth discussion on the nature of the flow excitation and flow-parameters influence is presented. The hydrodynamic mass parameter is also studied. Experimental results suggest that it is proportional to mixture density. On the other hand, two analytical formulations were developed and tested against experimental results. One formulation predicts the quadratic trend between standard deviation of acceleration and shear velocity found in experiments. The other formulation indicates that the peak-frequency of vibration response depends strongly on void fraction. It provides accurate predictions of peak-frequency, predicting 97.6% of the data within ±10% error bands.