This study presents the development and application of a systematic model-based framework for bioprocess optimization, evaluated on a cellulosic ethanol production case study. The implementation of the framework involves the use of dynamic simulations, sophisticated uncertainty analysis (Monte-Carlo technique) and sensitivity analysis (such as global techniques). The results of the case study point towards the enzyme loading as the most significant variable influencing the operational cost of additives in the conversion of lignocellulose to ethanol. Moreover, the results also show that there is an opportunity for further process optimization of bioethanol production from lignocellulose.
Computer-aided Chemical Engineering, 2011, p. 1455-1459
Sensitivity and uncertainty analysis; Bioethanol production; Monte Carlo; Critical variables and parameters; Critical process parameters; Sensitivity analysis; Monte-Carlo; Uncertainty analysis
Main Research Area:
Computer - Aided Chemical Engineering
21st European Symposium on Computer Aided Process Engineering, 2011