Flow Regime Recognition and Pressure Drop Simulation in Vertical Air-Water Flow By Means of Neural Networks and Fuzzy Logic

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Ghanbarzadeh, Soheil | 2010

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 41141 (08)
University: Sharif University of Technology
Department: Mechanical Engineering
Advisor(s): Saeedi, Mohammad Hassan
Abstract:
In order to safe design and optimize performance of industrial systems which work under two phase flow conditions, it’s often needed to categorize flow into different regimes. In present work the experiments of two phase flow were done in a large scale test facility with length of 6m and 5cm diameter. Four main flow regimes were observed in vertical air-water two phase flows at moderate superficial velocities of gas and water: Bubbly, Slug, Churn and Annular. Some image processing techniques were used to extract information from each picture. This information includes number of bubbles or objects, area, perimeter, height and width of objects (second phase). Also a texture feature extraction procedure was applied to images of different regimes. Some features which were adequate for regime identification were extracted such as Contrast, Energy, Entropy and etc. To identify flow regimes a fuzzy interface was introduced using characteristic of second phase in picture. Also an Adaptive Neuro Fuzzy (ANFIS) was used to identify flow patterns using textural features of images. The experimental results show that these methods can accurately identify the flow patterns in a vertical pipe
Keywords:
Two Phase Flow ; Flow Regime ; Neural Network ; Fuzzy Logic