Open AccessOperability of Continuous Bioprocesses: Static Behavior of a Large Class of Unstructured Models
Author(s) -
Ajbar A.
Publication year - 2001
Publication title -
engineering in life sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 57
eISSN - 1618-2863
pISSN - 1618-0240
DOI - 10.1002/1618-2863(200111)1:5<187::aid-elsc187>3.0.co;2-c
Subject(s) - multistability , operability , stability (learning theory) , limiting , biochemical engineering , class (philosophy) , singularity theory , substrate (aquarium) , computer science , biological system , mathematical optimization , singularity , control theory (sociology) , mathematics , control (management) , engineering , nonlinear system , ecology , physics , mechanical engineering , mathematical analysis , software engineering , quantum mechanics , machine learning , artificial intelligence , biology
The complete static behavior of a large class of unstructured models of continuous bioprocesses is classified using elementary concepts of the singularity theory and continuation techniques. The class consists of models for which the cell growth rate is proportional to the rate of utilization of limiting substrate while the kinetics of cell growth, utilization of limiting substrate and synthesis of the desired non‐biomass product are allowed to assume general forms of substrate and product. This class of models was used extensively in the literature to model fermentation processes. Global analytical conditions are derived that allow the construction of a practical picture in the multidimensional parameter space delineating the different static behavior these models can predict, including unique steady states, coexistence of wash‐out conditions with non‐trivial steady states and multistability resulting from hysteresis. These general results are applied to a number of experimentally validated models of fermentation processes, and allow the study of the effect of kinetic and operating parameters on the stability characteristics of these models. Practical criteria are also derived for the safe operation of the bioprocesses.