Degassing Dissolved Oxygen through Bubbling: The Contribution and Control of Vapor Bubbles

Abstract

An innovative yet sustainable approach for industrial deaeration is proposed, with demonstrated results and analyses, to contribute to finding solutions to improve energy efficiency in this field. Vacuum bubbling deaeration, sharing the same working principles of solubility control and the mass diffusion through vapor (or steam) with conventional thermal deaeration processes, works, however, at lower vacuum pressures. It neither resorts to heating nor requires any third-party materials such as membranes or gases, achieving orders of magnitude of reduction in the expected energy consumption in a simple and concrete way. In this study, the mechanisms of vapor bubble generation and retention were discussed by employing a vacuum bubbling model based on the experimental apparatus at Kongju National University, which uses a venturi-nozzle bubbler. The four parameters influencing vapor bubble generation and retention were identified as vessel pressure p1, nozzle depth Δh, nozzle performance p4−p3, and water temperature Tw. A series of deaeration experiments using the present approach for a tap water sample of 360~400 L were conducted under four different conditions to investigate the effects of the water temperature, vessel pressure, and bubbler nozzle depth. Final dissolved oxygen (DO) concentrations close to zero could be achieved with a vessel pressure of p1=1 kPa, with different bubbling times to reach a zero mg/L reading of DO concentration (case 2 and 3), which demonstrates the vital roles of the vapor bubble generation condition of (psat−p3)  and retention condition of (p4−psat) in achieving the lowest DO concentration. Analysis of the test results, based on the discrete-bubble model with the measured DO concentrations and degassing rates, showed promising results in reproducing the experimental data. Though the potential of vacuum bubbling deaeration is demonstrated, for the first time, to its full extent, further research efforts are encouraged in many areas, including more case-specific validation test cases with optimum operating conditions along with the study of more detailed modeling for performance prediction, including energy analysis.