Multi-objective Optimization of Butanol Production During ABE Fermentation
Liquid biofuels produced from biomass have the potential to partly replace gasoline. One of the most promising biofuels is butanol which is produced in acetone-butanol-ethanol (ABE) fermentation. The ABE fermentation is characterized by its low butanol concentration in the final fermentation broth....
Main Author: | |
---|---|
Language: | en |
Published: |
2013
|
Subjects: | |
Online Access: | http://hdl.handle.net/10393/30296 |
id |
ndltd-LACETR-oai-collectionscanada.gc.ca-OOU.#10393-30296 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-LACETR-oai-collectionscanada.gc.ca-OOU.#10393-302962014-06-14T03:50:34ZMulti-objective Optimization of Butanol Production During ABE FermentationSharif Rohani, AidaABE fermentationButanolMulti-objective optimizationIn-situ solvent recoveryIntegrated fermentationNet Flow MethodLiquid biofuels produced from biomass have the potential to partly replace gasoline. One of the most promising biofuels is butanol which is produced in acetone-butanol-ethanol (ABE) fermentation. The ABE fermentation is characterized by its low butanol concentration in the final fermentation broth. In this research, the simulation of three in situ recovery methods, namely, vacuum fermentation, gas stripping and pervaporation, were performed in order to increase the efficiency of the continuous ABE fermentation by decreasing the effect of butanol toxicity. The non-integrated and integrated butanol production systems were simulated and optimized based on a number of objectives such as maximizing the butanol productivity, butanol concentration, and butanol yield. In the optimization of complex industrial processes, where objectives are often conflicting, there exist numerous potentially-optimal solutions which are best obtained using multi-objective optimization (MOO). In this investigation, MOO was used to generate a set of alternative solutions, known as the Pareto domain. The Pareto domain allows to view very clearly the trade-offs existing between the various objective functions. In general, an increase in the butanol productivity resulted in a decrease of butanol yield and sugar conversion. To find the best solution within the Pareto domain, a ranking algorithm (Net Flow Method) was used to rank the solutions based on a set of relative weights and three preference thresholds. Comparing the best optimal solutions in each case study, it was clearly shown that integrating a recovery method with the ABE fermentation significantly increases the overall butanol concentration, butanol productivity, and sugar conversion, whereas butanol yield being microorganism-dependent, remains relatively constant.2013-12-05T19:02:37Z2013-12-05T19:02:37Z20132013-12-05Thèse / Thesishttp://hdl.handle.net/10393/30296en |
collection |
NDLTD |
language |
en |
sources |
NDLTD |
topic |
ABE fermentation Butanol Multi-objective optimization In-situ solvent recovery Integrated fermentation Net Flow Method |
spellingShingle |
ABE fermentation Butanol Multi-objective optimization In-situ solvent recovery Integrated fermentation Net Flow Method Sharif Rohani, Aida Multi-objective Optimization of Butanol Production During ABE Fermentation |
description |
Liquid biofuels produced from biomass have the potential to partly replace gasoline. One of the most promising biofuels is butanol which is produced in acetone-butanol-ethanol (ABE) fermentation. The ABE fermentation is characterized by its low butanol concentration in the final fermentation broth. In this research, the simulation of three in situ recovery methods, namely, vacuum fermentation, gas stripping and pervaporation, were performed in order to increase the efficiency of the continuous ABE fermentation by decreasing the effect of butanol toxicity. The non-integrated and integrated butanol production systems were simulated and optimized based on a number of objectives such as maximizing the butanol productivity, butanol concentration, and butanol yield. In the optimization of complex industrial processes, where objectives are often conflicting, there exist numerous potentially-optimal solutions which are best obtained using multi-objective optimization (MOO). In this investigation, MOO was used to generate a set of alternative solutions, known as the Pareto domain. The Pareto domain allows to view very clearly the trade-offs existing between the various objective functions. In general, an increase in the butanol productivity resulted in a decrease of butanol yield and sugar conversion. To find the best solution within the Pareto domain, a ranking algorithm (Net Flow Method) was used to rank the solutions based on a set of relative weights and three preference thresholds. Comparing the best optimal solutions in each case study, it was clearly shown that integrating a recovery method with the ABE fermentation significantly increases the overall butanol concentration, butanol productivity, and sugar conversion, whereas butanol yield being microorganism-dependent, remains relatively constant. |
author |
Sharif Rohani, Aida |
author_facet |
Sharif Rohani, Aida |
author_sort |
Sharif Rohani, Aida |
title |
Multi-objective Optimization of Butanol Production During ABE Fermentation |
title_short |
Multi-objective Optimization of Butanol Production During ABE Fermentation |
title_full |
Multi-objective Optimization of Butanol Production During ABE Fermentation |
title_fullStr |
Multi-objective Optimization of Butanol Production During ABE Fermentation |
title_full_unstemmed |
Multi-objective Optimization of Butanol Production During ABE Fermentation |
title_sort |
multi-objective optimization of butanol production during abe fermentation |
publishDate |
2013 |
url |
http://hdl.handle.net/10393/30296 |
work_keys_str_mv |
AT sharifrohaniaida multiobjectiveoptimizationofbutanolproductionduringabefermentation |
_version_ |
1716669703033716736 |