CFD predictive simulations of miniature bioreactor mixing dynamics coupled with photo-bioreaction kinetics in transitional flow regime

Abstract

High-throughput systems using miniaturised stirred bioreactors accelerate bioprocess development due to their simplicity and low cost. However, fluctuating hydrodynamics pose numerical challenges for coupling (bio)reaction kinetics, critical for optimisation and scale-up/down in chemical and bioprocess industries. To address this, hydrodynamic convergence was achieved by time-averaging instantaneous RANS solutions of the transitional SST model over a sufficiently long period to achieve statistical significance in step one. Subsequently, photo-bioreaction transport models, accounting for the photobioreactor’s directional illumination and curvature, were solved based on these converged fields, overcoming two-step coupling challenges in an approach not previously reported. Applied to a 0.7 L Schott bottle photobioreactor mechanically mixed by a magnetic stirrer (100–500 rpm), the model accurately predicted swirly vortex fields at 500 rpm, with a 7 % error margin for simulated tracer diffusion, and aligned biomass growth profiles with literature data on Rhodopseudomonas palustris. However, parallel computing efficiency did not scale linearly with processor count, making time-averaging computationally expensive. Also, improved bioreactor mixing enhanced biomass productivity, but rpms over 300 required increased incident light intensity (>100 Wm−2) due to observed light limitation. Hence, this model facilitates optimising stirring speeds and refining operational parameters for scale-up and scale-down processes.