Inhomogeneities in key cultivation variables (e.g., substrate and oxygen concentrations) have been shown to affect key process metrics in large-scale bioreactors. Being able to understand these gradients is hence of key interest from both an industrial and academic perspective. One of the main shortcomings of current modelling approaches is that volume change is not considered. Volume increase is a key feature of fed-batch fermentation processes. Existing models are restricted to simulating snapshots (hundreds of seconds) of industrial processes, which can last several weeks. This study presents a novel methodology that overcomes this limitation by constructing dynamic compartment models for the simulation of fed-batch fermentation processes. This strategy is applied to an industrial aerobic fed-batch fermentation process (40–90 m3) with Saccharomyces cerevisiae. First, it has been validated numerically that the compartmentalization strategy used captures the mixing performance and fluid dynamics. This was done by comparing the mixing times and the local concentration profiles of snapshot fermentation process simulations calculated with both CFD and compartment models. Subsequently, simulations of the entire process have been performed using the dynamic compartment model with kinetics. The simulation allows the spatio-temporal characterization of all process variables (e.g., glucose and DO concentrations), as well as the quantification of the metabolic regimes that the cells experience over time. This strategy enables the rapid characterization and assessment of the impact of gradients on process performance in industrial (aerobic) fed-batch fermentation processes and can be readily generalized to any type of bioreactor and microorganism.Technical University of Denmark; Novozymes A/S
