In this work, we present a transient LES approach using the Euler-Lagrange methodology and the Lattice-Boltzmann method, to successfully model and simulate interlinked bioreactor physics describing free surface hydrodynamics, multiphase mixing and mass transport in non-reacting and reacting systems. It is shown that the presence of reactions can result in a non-uniform spatially varying species concentration field, the magnitude and extent of which is directly related to the reaction rates and the underlying variations in the local volumetric mass transfer coefficient. Furthermore, we present a Gluconic acid optimization case study, which provides insights into the growth rates and process optimization over several hours of production. The computational approach presented in this work runs orders-of-magnitude faster than the conventional modeling tools and provides a unified framework for better understanding of free surface hydrodynamics, mixing, oxygen mass transfer and reaction kinetics to help with scale-up/scale-down decisions across a range of lengthscales.

The droplet size distribution in liquid-liquid dispersions is a complex convolution of impeller speed, impeller type, fluid properties, and flow conditions. In this work, we present three a priori modeling approaches for predicting the droplet diameter distributions as a function of system operating conditions. In the first approach, called the two-fluid approach, we use high-resolution solutions to the Navier-Stokes equations to directly model the flow of each phase and the corresponding droplet breakup/coalescence events. In the second approach, based on an Eulerian-Lagrangian model, we describe the dispersed fluid as individual spheres undergoing ongoing breakup and coalescence events per user-defined interaction kernels. In the third approach, called the Eulerian-Parcel model, we model a sub-set of the droplets in the Eulerian-Lagrangian model to estimate the overall behavior of the entire droplet population. We discuss output from each model within the context of predictions from first principles turbulence theory and measured data.