(301b) Empirical Study of Fluid Dynamics in Large Scale Fermentations Via Flow-Following Sensor Technology

Biomanufacturing has shown the potential to replace or enhance products in a diverse set of traditional industries in the food, fuels, chemical and materials sectors with sustainable alternatives. Scaling up bioreactors promises economy of scale by amortizing CAPEX and OPEX over greater production volumes, and the need to deploy sustainable, scalable and innovative biomanufacturing solutions is becoming increasingly important. Cargill has a wide diverse line of fermentation products that are constantly expanding to meet demands in these sectors.

Remaining competitive in large-scale fermentation relies on the continuous development of innovative technologies to better monitor, understand and enhance the performance of our microorganisms in their highly complex bioreactor environments. Such developments reside with R&D as technology providers of our fermentation processes, leveraging deep scientific knowledge and pilot scale models. Despite the development of computational capacity, CFD simulations of large-scale aerobic fermentations remain a huge challenge due to the complex phenomena occurring at this scale. Fluid properties can change significantly during the fermentation, sometimes changing from Newtonian to non-Newtonian fluid. Many industrial bioreactors use state-of-the-art fixed sensors to measure physiochemical parameters, like pH, dissolved oxygen, conductivity, temperature, pressure etc., but acquisition of spatially distributed parameters is still very complex.

We have leveraged the flow-following sensors in Cargill pilot and industrial scale bioreactors to gather unprecedented empirical data on hydrodynamic behavior and gradients in pH, dissolved oxygen and temperature across the whole bioreactor. The measurement frequencies of these flow-following sensors are in the range of microseconds, which enable tracking fluid flow by analyzing the positional data along with the accurate representation of homogeneity of key parameters. Using this data, we have been able to measure hydrodynamic parameters like mixing time, circulation time and axial-velocities with spatial and temporal resolution in aerobic fermentation systems where the matrix is constantly changing. This has facilitated the development of data driven hydrodynamic compartment models that require much less computing power than CFD and can explain the mixing behavior inside pilot and industrial scale aerobic reactors.

Application of such emerging technologies has allowed Cargill to understand and draw conclusions on the impact of reactor design elements on the hydrodynamic characteristics and physiochemical gradients from a novel and alternative approach. These empirical models have the potential to improve mixing and aeration designs that will not only satisfy the oxygen transfer requirements but will also minimize energy input, identify & prevent dead zones, and reduce mixing time. All of these are major drivers in commodity fermentation economics.