Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation
A propionic acid fermentation process not only provides a more sustainable approach but also opens the door to propionic acid production capacity in regions with limited petroleum supplies. With fermentation, low-cost substrates can be used, such as residual biomass; reducing their concentration in...
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| Format: | Article |
| Language: | English |
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Semnan University
2025-05-01
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| Series: | Journal of Heat and Mass Transfer Research |
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| Online Access: | https://jhmtr.semnan.ac.ir/article_8959_0d28e8bb2f17a92b9838ea52bb1696bf.pdf |
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| author | Waldecleia Queiroz Da Costa Miguel Fernando Saraiva Maia Nilton Pereira Da Silva Deibson Silva Da Costa Emerson Cardoso Rodrigues Diego Cardoso Estumano |
| author_facet | Waldecleia Queiroz Da Costa Miguel Fernando Saraiva Maia Nilton Pereira Da Silva Deibson Silva Da Costa Emerson Cardoso Rodrigues Diego Cardoso Estumano |
| author_sort | Waldecleia Queiroz Da Costa |
| collection | DOAJ |
| description | A propionic acid fermentation process not only provides a more sustainable approach but also opens the door to propionic acid production capacity in regions with limited petroleum supplies. With fermentation, low-cost substrates can be used, such as residual biomass; reducing their concentration in nature. This process becomes interesting because from it propionic acid is considered natural. Several models have already been developed to describe the dynamics of components such as: Microorganism (biomass), nutrients (substrate), metabolites (product). However, a challenge is how to define the model that best represents the kinetic term, and therefore, there are several models for this modeling. This article's novelty is the application of the Bayesian technique (Computational Bayesian Approximation) to estimate parameters and simultaneously select the best model. Model validation was carried out considering propionic fermentation regarding experimental data from the literature, which selected the Andrews model as the best to predict the dynamic of biomass, substrate and product by the following parameters estimated = 0.192, ms = 0.005, mp = 0.017. |
| format | Article |
| id | doaj-art-942b357e83fe416f8a22557046c9d47c |
| institution | Kabale University |
| issn | 2345-508X 2383-3068 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Semnan University |
| record_format | Article |
| series | Journal of Heat and Mass Transfer Research |
| spelling | doaj-art-942b357e83fe416f8a22557046c9d47c2025-01-20T11:28:50ZengSemnan UniversityJournal of Heat and Mass Transfer Research2345-508X2383-30682025-05-01121738010.22075/jhmtr.2024.31812.14788959Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic FermentationWaldecleia Queiroz Da Costa0Miguel Fernando Saraiva Maia1Nilton Pereira Da Silva2Deibson Silva Da Costa3Emerson Cardoso Rodrigues4Diego Cardoso Estumano5Simulation and Computational Biology Laboratory, High Performance Computing Center, UFPA, Belém-PA, BrazilFaculty of Chemical Engineering, Federal University of Pará, Belém, PA, 66075-110, BrazilDeparatament of Mechanical Engineering, Federal University of Amazonas, Manaus, AM, 69067-005, BrazilFaculty of Materials Engineering, Federal University of Pará, Belém, PA, 66075-110, BrazilFaculty of Chemical Engineering, Federal University of Pará, Belém, PA, 66075-110, BrazilSimulation and Computational Biology Laboratory, High Performance Computing Center, UFPA, Belém-PA, BrazilA propionic acid fermentation process not only provides a more sustainable approach but also opens the door to propionic acid production capacity in regions with limited petroleum supplies. With fermentation, low-cost substrates can be used, such as residual biomass; reducing their concentration in nature. This process becomes interesting because from it propionic acid is considered natural. Several models have already been developed to describe the dynamics of components such as: Microorganism (biomass), nutrients (substrate), metabolites (product). However, a challenge is how to define the model that best represents the kinetic term, and therefore, there are several models for this modeling. This article's novelty is the application of the Bayesian technique (Computational Bayesian Approximation) to estimate parameters and simultaneously select the best model. Model validation was carried out considering propionic fermentation regarding experimental data from the literature, which selected the Andrews model as the best to predict the dynamic of biomass, substrate and product by the following parameters estimated = 0.192, ms = 0.005, mp = 0.017.https://jhmtr.semnan.ac.ir/article_8959_0d28e8bb2f17a92b9838ea52bb1696bf.pdfparameter estimationmodel selectionabcpropionic acid |
| spellingShingle | Waldecleia Queiroz Da Costa Miguel Fernando Saraiva Maia Nilton Pereira Da Silva Deibson Silva Da Costa Emerson Cardoso Rodrigues Diego Cardoso Estumano Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation Journal of Heat and Mass Transfer Research parameter estimation model selection abc propionic acid |
| title | Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation |
| title_full | Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation |
| title_fullStr | Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation |
| title_full_unstemmed | Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation |
| title_short | Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation |
| title_sort | application of the abc algorithm in parameter estimation and kinetic model selection in propionic fermentation |
| topic | parameter estimation model selection abc propionic acid |
| url | https://jhmtr.semnan.ac.ir/article_8959_0d28e8bb2f17a92b9838ea52bb1696bf.pdf |
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