Optimising bioreactor processes with in-situ product removal using mathematical programming: A case study for propionate production
| Autor: | Lucas Van der Hauwaert, Alberte Regueira, Ludwig Selder, An-Ping Zeng, Miguel Mauricio-Iglesias |
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| Přispěvatelé: | Universidade de Santiago de Compostela. Departamento de Enxeñaría Química, Universidade de Santiago de Compostela. Instituto Interdisciplinar de Tecnoloxías Ambientais (CRETUS) |
| Rok vydání: | 2022 |
| Předmět: |
RECOVERY ISPR
Technology and Engineering Design FERMENTATION IDENTIFIABILITY General Chemical Engineering Biowissenschaften Biologie [570] UNCERTAINTY Product inhibition Computer Science Applications Kinetic modelling Downstream processing ddc:570 ACID under uncertainty Design under uncertainty Operational design ddc:600 Technik [600] Biotechnology |
| Zdroj: | COMPUTERS & CHEMICAL ENGINEERING Computers and Chemical Engineering 168: 108059 (2022-12-01) |
| ISSN: | 0098-1354 1873-4375 |
| Popis: | Designing and operating bioreactors with in-situ product removal (ISPR) can be challenging, particularly in discontinuous systems, where the ISPR and substrate feeding need to be effectively scheduled. Mathematical models can help assess different scheduling regimes in the fermentation medium and provide a means to optimise the process. Focusing on a propionate production case study, a model of a co-culture batch fermentation with electrodialysis (the ISPR system), was developed. Using this model, the product yield and/or the productivity were maximised by 1) single objective optimisation maximising the product yield (0.49 gpropionate /gglucose) or productivity (0.75 gpropionate/L/h), 2) multi objective optimisation to pursue trade-off solutions between the yield and productivity and 3) a stochastic optimisation maximising the productivity robustly (0.64 gpropionate/L/h) to account for uncertainties associated to the model parameters. With this contribution it is demonstrated that, through mathematical models, ISPR can be implemented and adapted to the user's objectives This work was supported by project ALQUIMIA (PID2019-110993RJ-I00) funded by the Agencia Estatal de Investigación Alquimia: Proyecto de I- d-i Programa Retos de la sociedad modalidad Jovenes investigadores convocatoria. A. Regueira would like to acknowledge the support of the Xunta de Galicia through a postdoctoral fellowship (ED481B-2021-012) SI |
| Databáze: | OpenAIRE |
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