Feed Strategy Optimization of an Algae Fed-Batch Bioreactor
Héctor De la Hoz Siegler , PhD student in Chemical Engineering
Supervisor - Dr. Amos Ben-Zvi and Dr. William McCaffrey
Optimization of the feed strategy in fed-batch bioprocesses has great potential to reduce bioprocessing costs. As a biological system, micro-algae have a great potential for the production of high-value products. In this work, the optimal feed strategy for a micro-algae fed-batch bioreactor based on Droop's two steps kinetic model is calculated by using several optimization methods. Droop's model assumes that the limiting substrate is first absorbed and stored by the cells and, in subsequent stage, used for growth.
Steepest Descent, Broyden-Fletcher-Goldfarb-Shanno (BFGS), Generalized Pattern Search (GPS), and Mesh Adaptive Direct Search (MADS) methods are implemented, and their performance compared. BFGS proves to be an efficient and robust method for finding the local optima. Among the direct search methods, MADS shows to be more robust than GPS. The algorithms are tested for both constrained and unconstrained problems. |
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