Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors
In many applications, complex biological phenomena can be reproduced via structured mathematical models, which depend on numerous biotic and abiotic input parameters, whose effect on model outputs can be of paramount importance. The calibration of model parameters is crucial to obtain the best fit b...
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AIMS Press
2024-09-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2024316 |
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| author | Daniele Bernardo Panaro Andrea Trucchia Vincenzo Luongo Maria Rosaria Mattei Luigi Frunzo |
| author_facet | Daniele Bernardo Panaro Andrea Trucchia Vincenzo Luongo Maria Rosaria Mattei Luigi Frunzo |
| author_sort | Daniele Bernardo Panaro |
| collection | DOAJ |
| description | In many applications, complex biological phenomena can be reproduced via structured mathematical models, which depend on numerous biotic and abiotic input parameters, whose effect on model outputs can be of paramount importance. The calibration of model parameters is crucial to obtain the best fit between simulated and experimental data. Sensitivity analysis and uncertainty quantification constitute essential tools in the field of biological systems modeling. Despite the significant number of applications of sensitivity analysis in wet anaerobic digestion, there are no examples of global sensitivity analysis for mathematical models describing the dry anaerobic digestion in plug-flow reactors. For the first time, the present study explores the global sensitivity analysis and uncertainty quantification for a plug-flow reactor model. The investigated model accounts for the mass$ / $volume variation that takes place in these systems as a result of solid waste conversion in gaseous value-added compounds. A preliminary screening based on the Morris' method allowed for the definition of three different groups of parameters. A surrogate model was constructed to investigate the relation between input and output parameters without running demanding simulations from scratch. The obtained Sobol' indices allowed to perform the quantitative global sensitivity analysis. Finally, the uncertainty quantification results led to the definition of the probability density function related to the investigated quantity of interest. The study showed that the net methane production is mostly sensitive to the values of the conversion parameter related to the particulate biodegradable volatile solids in acetic acid $ k_1 $ and to the kinetic parameter describing the acetic acid uptake $ k_2 $. The application of these techniques led to helpful information for model calibration and validation. |
| format | Article |
| id | doaj-art-0921b640e3c34be385567ab31a7b37d3 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-0921b640e3c34be385567ab31a7b37d32025-01-23T07:47:53ZengAIMS PressMathematical Biosciences and Engineering1551-00182024-09-012197139716410.3934/mbe.2024316Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactorsDaniele Bernardo Panaro0Andrea Trucchia1Vincenzo Luongo2Maria Rosaria Mattei3Luigi Frunzo4Department of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, via Cintia Monte S. Angelo, Naples 80126, ItalyCIMA Research Foundation, via A. Magliotto 2, Savona 17100, ItalyDepartment of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, via Cintia Monte S. Angelo, Naples 80126, ItalyDepartment of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, via Cintia Monte S. Angelo, Naples 80126, ItalyDepartment of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, via Cintia Monte S. Angelo, Naples 80126, ItalyIn many applications, complex biological phenomena can be reproduced via structured mathematical models, which depend on numerous biotic and abiotic input parameters, whose effect on model outputs can be of paramount importance. The calibration of model parameters is crucial to obtain the best fit between simulated and experimental data. Sensitivity analysis and uncertainty quantification constitute essential tools in the field of biological systems modeling. Despite the significant number of applications of sensitivity analysis in wet anaerobic digestion, there are no examples of global sensitivity analysis for mathematical models describing the dry anaerobic digestion in plug-flow reactors. For the first time, the present study explores the global sensitivity analysis and uncertainty quantification for a plug-flow reactor model. The investigated model accounts for the mass$ / $volume variation that takes place in these systems as a result of solid waste conversion in gaseous value-added compounds. A preliminary screening based on the Morris' method allowed for the definition of three different groups of parameters. A surrogate model was constructed to investigate the relation between input and output parameters without running demanding simulations from scratch. The obtained Sobol' indices allowed to perform the quantitative global sensitivity analysis. Finally, the uncertainty quantification results led to the definition of the probability density function related to the investigated quantity of interest. The study showed that the net methane production is mostly sensitive to the values of the conversion parameter related to the particulate biodegradable volatile solids in acetic acid $ k_1 $ and to the kinetic parameter describing the acetic acid uptake $ k_2 $. The application of these techniques led to helpful information for model calibration and validation.https://www.aimspress.com/article/doi/10.3934/mbe.2024316anaerobic digestionglobal sensitivity analysisuncertainty quantificationplug-flow reactor modelingpartial differential equations |
| spellingShingle | Daniele Bernardo Panaro Andrea Trucchia Vincenzo Luongo Maria Rosaria Mattei Luigi Frunzo Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors Mathematical Biosciences and Engineering anaerobic digestion global sensitivity analysis uncertainty quantification plug-flow reactor modeling partial differential equations |
| title | Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors |
| title_full | Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors |
| title_fullStr | Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors |
| title_full_unstemmed | Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors |
| title_short | Global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug-flow reactors |
| title_sort | global sensitivity analysis and uncertainty quantification for a mathematical model of dry anaerobic digestion in plug flow reactors |
| topic | anaerobic digestion global sensitivity analysis uncertainty quantification plug-flow reactor modeling partial differential equations |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2024316 |
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