Method for Determining Optimum Operational Conditions of Microbubble Scrubber Using Image Processing

This paper presents an image-processing-based model for calculating the interfacial-area concentration (IAC) of a low-pressure microbubble (LPMB) scrubber, which facilitates determination operational conditions scrubber via flow-pattern analysis. The LPMB maximizes interfacial area two-phase systems using bubbly flow. Microbubbles have received attention due to their microscopic sizes, high residence time, and mass-transfer efficiency. maintains negative outlet pressure generate gas flow, in turn generates microbubbles interrupting flow with three blocking plates atomizer. flux different bubble sizes. To obtain characteristics, we analyzed 20 atomizer images where this complex occurs. Bubble size, number bubbles, void fraction, IAC were calculated Open-CV Python algorithm. validate most appropriate patterns, case studies conducted at difference 240, 360, 450 mmAq. 360 mmAq condition had lowest percentage bubbles smaller than 50 µm, but total highest. results obtained study confirm that oxidizing solution reductions 92.6, 93.9, 99.9% NOX, SOX, dust, respectively. These could be used reactivity other intended commercial practical applications.