title: On-line identification of fermentation processes for ethanol production.
abstract: A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. This new tool provides a great support for decision-making and opens a new range of opportunities for industrial optimization.
authors.affiliation: Programa de Engenharia Química / COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, CP 68502, CEP 21941-972, Rio de Janeiro, RJ, Brazil.
authors.forename: M M
authors.initials: MM
authors.lastname: Câmara
authors.affiliation: Programa de Engenharia Química / COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, CP 68502, CEP 21941-972, Rio de Janeiro, RJ, Brazil.|OptimaTech, Rio de Janeiro, RJ, Brazil.
authors.forename: R M
authors.initials: RM
authors.lastname: Soares
authors.affiliation: Programa de Engenharia Química / COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, CP 68502, CEP 21941-972, Rio de Janeiro, RJ, Brazil.|OptimaTech, Rio de Janeiro, RJ, Brazil.
authors.forename: T
authors.initials: T
authors.lastname: Feital
authors.affiliation: Global Yeast, Rio de Janeiro, RJ, Brazil.
authors.forename: P
authors.initials: P
authors.lastname: Naomi
authors.affiliation: Global Yeast, Rio de Janeiro, RJ, Brazil.
authors.forename: S
authors.initials: S
authors.lastname: Oki
authors.affiliation: Global Yeast, Rio de Janeiro, RJ, Brazil.|Department of Molecular Microbiology, VIB, Kasteelpark Arenberg 31, 3001, Leuven-Heverlee, Flanders, Belgium.
authors.forename: J M
authors.initials: JM
authors.lastname: Thevelein
authors.affiliation: Global Yeast, Rio de Janeiro, RJ, Brazil.
authors.forename: M
authors.initials: M
authors.lastname: Amaral
authors.affiliation: Programa de Engenharia Química / COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, CP 68502, CEP 21941-972, Rio de Janeiro, RJ, Brazil. pinto@peq.coppe.ufrj.br.
authors.forename: J C
authors.initials: JC
authors.lastname: Pinto
mesh_terms: D018533:Biomass; D002241:Carbohydrates; D000431:Ethanol; D005285:Fermentation; D012441:Saccharomyces cerevisiae; D003313:Zea mays
chemical_list: D002241:Carbohydrates; D000431:Ethanol
keywords: Dry grind corn ethanol; Ethanol fermentation; Process monitoring; SSF process; Soft sensor