Modelling a lab-scale continuous flow aerobic granular sludge reactor: optimisation pathways for scale-up

Abstract

Wastewater treatment plants (WWTPs) face increasing pressure to handle higher volumes of water due to climate change causing storm surges, which current infrastructure cannot handle. Aerobic granular sludge (AGS) is a promising alternative to activated sludge systems due to their improved settleability property, lowering the land footprint and improving efficiency. This research investigates the optimisation of a lab-scale sequencing batch reactor (SBR) into a continuous flow reactor through mathematical modelling, sensitivity analysis, and a computational fluid dynamic model. This is all applied for the future goal of scaling up the model designed to a full-scale continuous flow reactor. The mathematical model developed analyses microbial kinetics, COD degradation, and mixing flows using Reynolds and Froude numbers. To perform a sensitivity analysis, a Python code was developed to investigate the stability when influent concentrations and flow rates vary. Finally, CFD simulations on ANSYS Fluent evaluated the mixing within the reactor. An 82% COD removal efficiency was derived from the model and validated against the SBR data and other configurations. The sensitivity analysis highlighted the reactor’s inefficiency in handling high-concentration influents and fast flow rates. CFD simulations revealed good mixing within the reactor; however, they did show issues where biomass washout would be highly likely if applied in continuous flow operation. All of these results were taken under deep consideration to provide a new reactor configuration to be studied that may resolve all these downfalls.

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Identifiers

ORCID for Mohamed G. Hassan: orcid.org/0000-0003-3729-4543

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