A methodology for the design of scale-down bioreactors by the use of mixing and circulation stochastic models

Scale-up is traduced in practice by an increase of the dimensions of the bioreactors, leading to a modification of the time scale and thus of the process dynamics. In the present work, a methodology to study the effect of scale-up on bioreactors hydrodynamics and to put in place scale-down reactors representative of the flow properties encountered in real scales bioreactors is detailed.In order to simplify the analysis, we have proposed the use of a stochastic model which is directly affected by the time scale. Indeed, to run simulations with such models, we have to specify the time taken to achieve a transition Δt. Stochastic models are thus reliable to study scale-up effect on stirred reactors hydrodynamics. In addition, these models permit to have an insight on the internal dynamic of the process.In the case of the circulation process, qualitative aspects have to be taken into account and induce a modification of the flow regions arrangement of the model. The stochastic analysis of large-scale bioreactors permits to propose a translating methodology into a scale-down context. Optimised scale-down reactors can be used further to carry out fermentation tests with the hydrodynamic conditions of the industrial scale. In a general rule, the performances of stochastic model allow to facilitate greatly the analysis of the scale-up effect and the hydrodynamic characteristics of both large-scale and scale-down reactors.