Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method
Anaerobic digestion is a promising method of organic waste valorisation, particularly for fish farm waste, which has experienced a high growth rate in recent years. The literature contains predictive mathematical models that have been developed by various authors, allowing the prediction of the comp...
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MDPI AG
2022-07-01
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author | Andres Martinez Lamiae Vernieres-Hassimi Lokmane Abdelouahed Bechara Taouk Chetna Mohabeer Lionel Estel |
author_facet | Andres Martinez Lamiae Vernieres-Hassimi Lokmane Abdelouahed Bechara Taouk Chetna Mohabeer Lionel Estel |
author_sort | Andres Martinez |
collection | DOAJ |
description | Anaerobic digestion is a promising method of organic waste valorisation, particularly for fish farm waste, which has experienced a high growth rate in recent years. The literature contains predictive mathematical models that have been developed by various authors, allowing the prediction of the composition of bio-gas production from organic waste. In general, Monod’s kinetic expression is the basis for describing the enzymatic reaction rates for anaerobic digestion. In this work, several parameters are taken into account, such as temperature, cell growth inhibition, and other operating parameters, and systems of differential equations coupling the kinetics and stoichiometry for bio-reactions are applied to better describe the dynamics. Because of the high number of initial parameters that need to be defined for the anaerobic digester, the use of this model requires significant resources and a long calculation time. For this reason, a global sensitivity analysis (GSA) is applied to this predictive model based on the Sobol index method, in order to identify the most influential key parameters and the interactions between them. For the digestion of fish waste, it is observed that the key parameters influencing methane production are the lipid concentration of the waste, temperature, and hydraulic retention time (HRT). |
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issn | 2673-3994 |
language | English |
last_indexed | 2024-03-09T23:58:48Z |
publishDate | 2022-07-01 |
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spelling | doaj.art-d5754437c11d43e5ad08ed03e6ee86cc2023-11-23T16:20:21ZengMDPI AGFuels2673-39942022-07-013343644810.3390/fuels3030027Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol MethodAndres Martinez0Lamiae Vernieres-Hassimi1Lokmane Abdelouahed2Bechara Taouk3Chetna Mohabeer4Lionel Estel5Laboratoire de Sécurité des Procédés Chimiques, INSA Rouen Normandie, Normandie Université, UNIVROUEN, LSPC-EA 4704, 76000 Rouen, FranceLaboratoire de Sécurité des Procédés Chimiques, INSA Rouen Normandie, Normandie Université, UNIVROUEN, LSPC-EA 4704, 76000 Rouen, FranceLaboratoire de Sécurité des Procédés Chimiques, INSA Rouen Normandie, Normandie Université, UNIVROUEN, LSPC-EA 4704, 76000 Rouen, FranceLaboratoire de Sécurité des Procédés Chimiques, INSA Rouen Normandie, Normandie Université, UNIVROUEN, LSPC-EA 4704, 76000 Rouen, FranceLaboratoire de Sécurité des Procédés Chimiques, INSA Rouen Normandie, Normandie Université, UNIVROUEN, LSPC-EA 4704, 76000 Rouen, FranceLaboratoire de Sécurité des Procédés Chimiques, INSA Rouen Normandie, Normandie Université, UNIVROUEN, LSPC-EA 4704, 76000 Rouen, FranceAnaerobic digestion is a promising method of organic waste valorisation, particularly for fish farm waste, which has experienced a high growth rate in recent years. The literature contains predictive mathematical models that have been developed by various authors, allowing the prediction of the composition of bio-gas production from organic waste. In general, Monod’s kinetic expression is the basis for describing the enzymatic reaction rates for anaerobic digestion. In this work, several parameters are taken into account, such as temperature, cell growth inhibition, and other operating parameters, and systems of differential equations coupling the kinetics and stoichiometry for bio-reactions are applied to better describe the dynamics. Because of the high number of initial parameters that need to be defined for the anaerobic digester, the use of this model requires significant resources and a long calculation time. For this reason, a global sensitivity analysis (GSA) is applied to this predictive model based on the Sobol index method, in order to identify the most influential key parameters and the interactions between them. For the digestion of fish waste, it is observed that the key parameters influencing methane production are the lipid concentration of the waste, temperature, and hydraulic retention time (HRT).https://www.mdpi.com/2673-3994/3/3/27anaerobic digestionwastebiogasSobol index method |
spellingShingle | Andres Martinez Lamiae Vernieres-Hassimi Lokmane Abdelouahed Bechara Taouk Chetna Mohabeer Lionel Estel Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method Fuels anaerobic digestion waste biogas Sobol index method |
title | Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method |
title_full | Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method |
title_fullStr | Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method |
title_full_unstemmed | Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method |
title_short | Modelling of an Anaerobic Digester: Identification of the Main Parameters Influencing the Production of Methane Using the Sobol Method |
title_sort | modelling of an anaerobic digester identification of the main parameters influencing the production of methane using the sobol method |
topic | anaerobic digestion waste biogas Sobol index method |
url | https://www.mdpi.com/2673-3994/3/3/27 |
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