The effectiveness of a biopharmaceutical manufacturing process depends to a large extent on the efficiency of the bioreactor, especially in the field of generic drugs. The improvement of the productivity of industrial size bioreactors is, up to now, mainly driven by empirical knowledge. Computer simulation would help to understand the processes inside the reactor and hence lay the foundation for new reactor designs. However, despite the recent improvement of computational capabilities, only a few seconds of real time operation of an industrial scale reactor takes months to simulate.
Thus, the goal of this study is to use graphic cards to speed up this simulation. To take full advantage of the processor’s parallelism, localized calculation algorithms are used, like the lattice Boltzmann method for modelling the fluid flow field. The calculation of the bubble movement is done by solving the Newton’s equation of motion. For coalescence and breakup stochastic models are used. The phases are coupled with a two way approach.
To simulate large reactors, the code has a multi GPU functionality, hence it can distribute the workload of the simulation on several graphic processors. Validation is done with literature data as well as with results from holdup measurements of a 150l laboratory reactor. To show the usefulness of this code for scale up studies, a 40 m³ reactor was simulated.
To mimic the behavior of real fermentation broth a non-Newtonian viscosity model was added using the power law model. An important process within the reactor is the transport of species (dissolved oxygen, nutrients, carbon dioxide, etc.) by the fluid flow field. To model the distribution of the species a particle based solver was implemented.
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