2021 Nashville AISTech

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Gas Bubble Digital Data Generation by Image Analysis Using Reduced-Scale Water Modeling of a Slab Continuous Caster Mold (Room Virtual)

Gas bubbles inside continuous caster molds have a strong influence on inclusion entrapment, affecting slab surface and internal quality. Mold water models at the University of Toronto were utilized to record bubble characteristics at various casting conditions using a high-resolution-speed sense camera and shadowgraphy techniques. Image processing algorithms viz. Watershed, Ellipse-split and Circular Hough Transformation were then used to analyze bubbles with both ImageJ software and Python OpenCV code. Thus, digital data (bubble number density, size distribution, area percentage and coalescence frequency) with respect to gas fraction in the mold are generated. Possible mechanisms of bubble collisions and coalescence are discussed.