Visualization experiment and machine learning modeling for falling-film systems
Published in Chemical Engineering Research and Design, 2023
This paper presents an experimental study on liquid film behavior in falling-film systems using high-speed imaging and machine learning techniques. It illustrates how parameters like Reynolds number and tube spacing affect flow characteristics such as jet diameter and film thickness, developing image analysis and machine learning models to quantify and predict these flow parameters for improved system design.
Recommended citation: Kandukuri, Prudviraj, Ramesh Kaki, Sandip Deshmukh, and Supradeepan Katiresan. "Visualization experiment and machine learning modeling for falling-film systems." Chemical Engineering Research and Design 199 (2023): 399-412.
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