A framework for model-based optimization of bioprocesses under uncertainty: Identifying critical parameters and operating variables
Publication: Research - peer-review › Article in proceedings – Annual report year: 2011
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.
|Title||21st European Symposium on Computer Aided Process Engineering|
|Conference||21st European Symposium on Computer Aided Process Engineering|
|Period||29/05/11 → 01/06/11|
|Name||Computer Aided Chemical Engineering|
|Citations||Web of Science® Times Cited: No match on DOI|
- Critical process parameters, Sensitivity analysis, Bioethanol production, Monte-Carlo, Uncertainty analysis
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