Nucleate Boiling Regime Detection Using Digital Image Measurement Techniques

Abstract

A novel approach has been attempted to detect different sub-stages of nuclear boiling region in pool boiling on a cylindrical heating element in a sight-glass arrangement using digital image measurement. High resolution images of boiling phenomena were obtained sequentially by digital camera with high shutter speed. The images in the sequence were processed manually and analyzed by semiautomatic evaluation programs to obtain feature points data. The experiment was conducted at low pressure (<1atm) and moderately low heat fluxes in nucleate boiling region to facilitate feature detection. Data generated from feature detection by ‘Speeded Up Robust Feature’ algorithm based local interest point detector was then analyzed by statistical techniques. Manipulation of statistical distribution parameter leads to a system-specific stochastic model development. The developed model fairly predicts natural convective boiling and different sub-stages of nucleate boiling including bubbling characteristic offering qualitative information about the boiling condition in appreciably short amount of time. Such detection technique could expedite noninvasive control around Critical Heat Flux region in industrial boiling systems for transparent liquids. The context of a broader model is to be investigated.