Scaling up method of stirred bioreactor

For microbial reaction systems, due to the characteristics of biological cell growth, adaptation, delay, degradation, variation, and sensitivity to shear, bioreactors are more complex than ordinary chemical reactors, and their amplification process is more difficult.

① Conduct experiments on the biological cells used under a wide range of cultivation conditions to understand the characteristics of cell growth kinetics and product generation kinetics;

② Based on the above series of experiments, determine the optimal medium formula and culture conditions for the biological reaction;

③ Solve the micro balance equations related to mass transfer, heat transfer, momentum transfer, etc., and derive a relationship model that can express the environmental conditions inside the reactor and the main operating variables (stirring speed IV, ventilation rate Q, stirring power, substrate flow acceleration rate v, etc.). 

Then apply this mathematical model to calculate the values of the main variables under optimized conditions.

However, due to the complexity of biological reaction processes, the dynamic equations that can fully describe biological reaction processes are exceptionally complex, making it still very difficult to solve certain differential balance equations. 

It is difficult to fully follow the above ideal process to complete the design and scaling up of bioreactors.

In addition to the theoretical methods mentioned above, commonly used methods for scaling up bioreactors include semi theoretical methods, dimensional analysis methods, and empirical scaling up methods.  

The so-called theoretical amplification method is to establish and solve the momentum, mass, and energy balance equations of the reaction system. 

As mentioned earlier, this amplification method is very complex and currently difficult to apply in practice. But this method is the most systematic and based on scientific theory.

In theory, the biological reaction rate is independent of the size and shape of the reaction vessel. 

However, in reality, the reaction rate is affected by physical processes such as mass transfer, momentum transfer, and heat transfer, so biological reactions are inevitably influenced by the type of reactor and three-dimensional structure. 

The basic theoretical basis of amplification is similarity theory, and the fundamental characteristic of similarity theory is that two reaction systems can be described by the same differential equation, and there are synchronous dynamics, heat and mass transfer, and biochemical reactions in one system.

The theoretical amplification method is difficult to solve the momentum balance equation. 

To solve this contradiction, the momentum equation can be simplified. There have been many research advances in flow models for stirred tank reactors, but their commonality is that they only consider the flow of the main body of the liquid flow and ignore complex flows near local areas such as the stirring impeller or reactor wall. 

There are three types of flow patterns: piston flow, piston flow with dispersed liquid elements, and fully mixed flow.

The so-called factor analysis amplification method is to maintain the dimensionless number group (also known as the quasi number) composed of biological reaction system parameters constant during the amplification process. 

Although the application of factor analysis method has strict limitations, this method is still very useful. 

If the momentum, mass, and heat balance of the reaction system, as well as the relevant boundary and initial conditions, are written in dimensionless form for the amplification process, it is called the dimensional analysis amplification method.

Currently, the most widely used method is still based on experience design. Based on experience amplification, it is generally only possible to ensure that individual criteria are equal after amplification. 

Therefore, it is necessary to consider whether changes in other criteria will cause changes in flow patterns or damage to microorganisms, and make modifications accordingly.

Although the structure of stirred reactors is relatively simple, the fluid flow and mixing processes inside different stirred reactors are quite complex due to the involvement of both biochemical reactions and physical processes.

At present, the design and scaling up of stirred reactors mainly rely on empirical methods to solve problems such as long design cycles and large deviations, which have brought huge economic losses. 

How to accurately describe and simulate the mixing process and flow conditions in stirred reactors, and provide theoretical guidance for their optimization design and scaling up, is an important development direction in bioreactor technology research.