CFD simulation of a packed-bed solid-state fermentation bioreactor

Abstract

In recent years, Solid-State Fermentation (SSF) has shown much promise for the development of bioprocesses and products. SSF involves the growth of microorganisms within a bed of moist solid particles permeated by a continuous gas phase and a minimum of visible water. SSF offers potential advantages over submerged culture: since the concentrations of products are often higher, smaller bioreactors can be used, reducing operational costs. However, there is a major challenge in obtaining adequate heat and mass transfer when this fermentation method is used at large scales. Mathematical models and computer simulations are useful tools for designing strategies to overcome this challenge; use of these tools can reduce costs of experimental development programs at pilot-scale and production scale, by reducing the number of fermentation experiments required. In the current work, we used the commercial CFD software ANSYS FLUENT® 16.0 to develop a mathematical model for heat and mass transfer in a pilot-scale packed-bed bioreactor. The model was used to simulate two different experiments that had been carried out previously in the bioreactor: first, the cooling of a bed of soybeans and, second, the heating of a bed composed of a mixture of wheat bran and sugarcane bagasse. The simulations considered the dynamics of airflow in the porous substrate bed and the non-equilibrium transfer of heat and moisture between the solid and gas phases. The second simulation considered a heterogeneous distribution of porosity within the substrate bed. Even though the two experiments were quite different, the same mathematical model was able to represent the temperature profiles observed experimentally. In the second simulation, the average temperature difference between the experimental and predicted values was 0.07°C. A third simulation was done for the growth of the filamentous fungus Aspergillus niger in SSF, with the predictions being compared to the results of a traditional mathematical model based on differential equations. Our work provides the basis for the development of a suitable and reliable mathematical model for testing operating conditions and control strategies for large-scale cultivation of microorganisms in SSF bioreactors.