Oxygen transfer is a crucial process in wastewater treatment as it requires substantial energy. Its optimization is hampered by lack of detailed process understanding. Oxygen transfer is influenced by bubble size dynamics, governed by micro-scale hydrodynamics. The proposed study builds fundamental process knowledge through an integrated CFD-PBM model and dedicated measurements. It forms the basis for system design/operational optimization.
This study aims to build fundamental knowledge and optimize oxygen transfer in fine-bubble aeration systems contributing to improving the energy efficiency of full-scale WWTPs and producing economic and environmental advantages. To reach this major objective, an aeration model for fine-bubble aeration systems will be developed to improve the prediction of oxygen transfer based on Population Balance Model (PBM) and Computational Fluid Dynamics (CFD). This aeration model will be calibrated and validated using experimental data (laboratory and full-scale) collected during this doctoral research project. Having a robust aeration model that is thoroughly developed, calibrated and validated on multiple full-scale plants allows for building better whole-plant models. The latter allows for better design of fine-bubble aeration systems as well as process control, which will, in turn, contribute to much-needed energy savings in this important industrial sector.