EPTT 2020

12th Spring School on Transition and Turbulence

QUANTITATIVE ANALYSIS OF PRESSURE SIGNALS FOR GAS-LIQUID HORIZONTAL FLOW PATTERNS RECOGNITION

Submission Author: Carla Nayara Michels dos Santos , SC , Brazil
Co-Authors: Carla Nayara Michels dos Santos, Sarah Laysa Becker, Vinícius Basso de Godoy, Celso Murilo dos Santos, Christine Boos, Marcela Silva, Henry França Meier
Presenter: Carla Nayara Michels dos Santos

doi://10.26678/ABCM.EPTT2020.EPT20-0080

 

Abstract

The classification of flow distributions in various flow patterns is one of the most important parameters for understanding gas-liquid two-phase flow. Initially flow regimes were defined according to visual observations which depended on operator interpretation making the technique highly subjective. There are currently several objective and non-intrusive techniques available. An example of these techniques is the analysis of pressure signals that require simple and robust sensors. The pressure fluctuations resulting from the passage of different biphasic structures have interesting statistical characteristics for the objective determination of flow patterns. The purpose of this study is to present a way to identify the flow patterns for horizontal tubes from a classification rule. An experimental study was carried out in a tube 7 meters long and 74 mm in internal diameter. For the acquisition of pressure data, four sensors were installed along the testing section. Twelve quantitative parameters were taken from the resulting pressure signals. The flow classification was performed by simply thresholding parameter values and creating a classification. This way of identifying flow patterns proved to be a good alternative for when there is a need to blindly diagnose the flow regime based on data from pressure sensors, which are devices that are relatively easy to install, have low cost and are not are intrusive. The rule for classifying stratified and intermittent flows reached an efficiency of 91.16% in the verification and validation of data extracted from our experimental unit. The classification results with literature data were good seeing that the rule had a 95% performance using data acquired by different operators, gas-liquid velocities and at different research facilities.

Keywords

Two-phase Flow, Gas-Liquid Flow, Flow patterns classification

 

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