Operating Condition Optimization on Mass Transfer in Aerated Stirred Tank Fermentors

Oxygen is a critical component of aerobic fermentations and is sparingly soluble in aqueous solutions. Due to the slow mass transfer of oxygen from the bubbles into the liquid the rate of cell metabolism depends on the rate of oxygen supply from the gas phase. Mass transfer across gas-liquid interfaces plays also a vital role in many other reaction systems. The mass transfer is a function of the gas-liquid surface area which is increased with high agitation rates. The shear rates are increased resulting in bubble brake-up. With the agitation rate the power consumption is increased as well. Micro-organisms, such as yeast, are damageable and thus limit the shear rates, too.

Traditionally dimensionless correlations are used to improve the design of production scale stirred tank fermenters. These aid incorporating many important design variables of the materials and geometry. However, design methodologies available for stirred tank fermenters are insufficient and many times contain errors. By making assumptions on the system correlations often omit important influences on the mass transfer. Using computational fluid dynamics enables us to make fewer assumptions on the geometry and physics resulting in a better insight into the system. This enables the engineer to make meaningful decisions with fewer constraints.

In the current state of industrial engineering a typical vessel is going to be operated yielding various products. Therefore the tank geometry is not designed from scratch but instead has to be used with little alternations. In these or similar scenarios the operating conditions - such as agitation rate or mass flow rates - are a mayor leverage increasing the performance.

In this work the performance of a stirred tank fermenter is going to be optimized using CFD simulations in combination with design explorations. STAR-CCM+ as a finite volume based physics solver and HEEDS exploring the design space are the tools used. After validating the simulation a Pareto front optimization with power consumption vs. mass transfer rate will be presented.

References:

Aglave, R., & Eppinger, T. (2016, December). Influence of Bubble Size Distribution in Gas-Liquid Flows. In High Performance Computing Workshops. IEEE.

Doran, P. M. (1995). Bioprocess engineering principles. Academic press.

Sorenson, K. L. (2010). Comparative studies on oxygen mass transfer for the design and development of a single-use fermenteor. Utah State University.

Davis, R. Z. (2009). Design and scale-up of production scale stirred tank fermenteors. Utah State University.