Regression-based prediction of flow-induced dominant vibrational frequencies in two-phase flow regimes

Sohail, M. and Pao, W. and Othman, A.R. and Azam, H. and Khan, M.R. (2024) Regression-based prediction of flow-induced dominant vibrational frequencies in two-phase flow regimes. Ocean Engineering, 307.

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Abstract

An extensive spectrum of vibrational frequencies exists in two-phase Flow Induced Vibrations (FIVs) due to the presence of diverse flow patterns. The distinct behavior of flow regimes poses a significant challenge in predicting Dominant Vibrational Frequencies (DVFs) of two-phase FIVs. This research aims to develop correlations for predicting DVFs in Stratified, Slug, Wavy, Annular, Elongated bubble, and Dispersed bubble flow regimes. Numerical and experimental investigation is carried out to observe the DVFs of different flow patterns on a horizontal 90-degree bend. DVFs are extracted from the Fast Fourier Transform (FFT) response of the bend. A third-degree polynomial regression technique is adopted to identify the optimal fitting polynomials of DVFs relative to gas and liquid superficial velocities in each flow regime. This study has successfully developed third-order regression polynomials to predict DVFs across diverse two-phase flow regimes for corresponding superficial velocities of gas and liquid. The proposed polynomials for all six flow regimes demonstrated Root Means Squared Error (RMSE) below 2. Higher R-squared values affirmed the efficacy in elucidating the variance in DVFs. The findings significantly elevate the prediction of DVFs across diverse flow patterns offering a critical advancement in two-phase flow-induced vibrations. © 2024 Elsevier Ltd

Item Type: Article
Additional Information: cited By 0
Uncontrolled Keywords: Fast Fourier transforms; Flow patterns; Forecasting; Polynomials; Two phase flow; Vibration analysis, Bubble flow; Dispersed bubbles; Dominant vibrational frequency; Flow induced; Flow regimes; Flow-induced vibration; Numerical investigations; Spectra's; Two phases flow; Two-phase flow regimes, Regression analysis, error analysis; Fourier transform; prediction; regression analysis; two phase flow; vibration
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 04 Jun 2024 14:19
Last Modified: 04 Jun 2024 14:19
URI: https://khub.utp.edu.my/scholars/id/eprint/19566

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