Non-Contact State Assessment of Falling-Film Flow over Horizontal Tube Bundles Using High-Speed Imaging

Area of Science:

• Fluid Dynamics
• Heat Transfer
• Optical Measurement Techniques

Background:

• High-speed imaging is valuable for monitoring falling-film flows over tube bundles.
• Quantifying reflective images is challenging due to factors like film geometry and viewing angle.
• Existing methods may lack interpretability for comparative flow state assessment.

Purpose of the Study:

• To develop an interpretable visual-proxy sensing framework for comparative state assessment of falling-film flows.
• To establish a method for quantifying flow characteristics from high-speed imaging data.
• To provide a low-calibration tool for analyzing falling-film dynamics.

Main Methods:

• Conducted isothermal water experiments on a five-row horizontal tube bundle (ReΓ=184-960).
• Acquired 2000 grayscale frames at 2000 fps, analyzing row-wise regions of interest.
• Processed image sequences using temporal-median background subtraction, spatiotemporal mapping, detrending, and normalization to generate a normalized map (Mn) and dynamic renewal field (G).
• Extracted four scalar descriptors: noise-corrected apparent renewal intensity (IR), high-frequency fraction (RHF), spectral peak frequency (fp), and burst-event rate (FB).

Main Results:

• The normalized map (Mn) and dynamic renewal field (G) successfully captured the transition from sparse column flow to continuous sheet flow.
• Identified row-dependent organization of flow activity.
• The extracted descriptors provided complementary information on renewal intensity, frequency composition, dominant time scale, and intermittent events.
• Validated the framework through zero-response, noise-correction, and sensitivity tests, confirming avoidance of pseudo-waves and stable comparisons.

Conclusions:

• The proposed visual-proxy sensing framework offers an interpretable and effective method for assessing falling-film flow states.
• The extracted scalar descriptors provide quantitative insights into flow dynamics.
• The framework serves as a low-calibration tool for relative falling-film state assessment in engineering applications.