Andreia Amaral

Position
PhD Student
Research background

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.

Research objective

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.

Research methodology
  1. Set up laboratory experiments using a bubble column to understand bubble size dynamics and gas  hold-up of fine-bubble aeration systems and the effect of the liquid’s viscosity;
  2. Define, calibrate and validate a PBM for bubble size dynamics that accounts for the effect of hydrostatic pressure and  coalescence and breakages processes;
  3. Investigate how the knowledge obtained through the PBM model can be incorporated in the currently used models and to what extent they improve their predictions (applied to multiple WWTP)
  4. Incorporate the PBM into CFD to simulate bubble size dynamics coupled with hydrodynamics to get a detailed insight into how the process is working and understand why efficiency is reduced
  5. Calibrate and validate the PBM-CFD aeration model using fieldwork data
  6. Run different scenarios for the aeration compartmental model in order to optimize oxygen transfer within the process
  7. Set up a compartmental aeration model taking into account the results from the PBM-CFD model (in case the model prediction of part 3 is not sufficient)
  8. Define control strategies and design of fine-bubbles aeration systems
Key publications