Da Costa, Waldecleia Queiroz, Maia, Miguel Fernando Saraiva, Da Silva, Nilton Pereira, Da Costa, Deibson Silva, Rodrigues, Emerson Cardoso, Estumano, Diego Cardoso. (1404). Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation. هنرهای کاربردی, 12(1), 73-80. doi: 10.22075/jhmtr.2024.31812.1478
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". هنرهای کاربردی, 12, 1, 1404, 73-80. doi: 10.22075/jhmtr.2024.31812.1478
Da Costa, Waldecleia Queiroz, Maia, Miguel Fernando Saraiva, Da Silva, Nilton Pereira, Da Costa, Deibson Silva, Rodrigues, Emerson Cardoso, Estumano, Diego Cardoso. (1404). 'Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation', هنرهای کاربردی, 12(1), pp. 73-80. doi: 10.22075/jhmtr.2024.31812.1478
Da Costa, Waldecleia Queiroz, Maia, Miguel Fernando Saraiva, Da Silva, Nilton Pereira, Da Costa, Deibson Silva, Rodrigues, Emerson Cardoso, Estumano, Diego Cardoso. Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation. هنرهای کاربردی, 1404; 12(1): 73-80. doi: 10.22075/jhmtr.2024.31812.1478

Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation

Journal of Heat and Mass Transfer Research
دوره 12، شماره 1 - شماره پیاپی 23، مرداد 2025، صفحه 73-80    اصل مقاله (553.58 K)
نوع مقاله: Full Length Research Article
شناسه دیجیتال (DOI): 10.22075/jhmtr.2024.31812.1478
نویسندگان
Waldecleia Queiroz Da Costa1؛ Miguel Fernando Saraiva Maia2؛ Nilton Pereira Da Silva3؛ Deibson Silva Da Costa4؛ Emerson Cardoso Rodrigues2؛ Diego Cardoso Estumano* 1
1Simulation and Computational Biology Laboratory, High Performance Computing Center, UFPA, Belém-PA, Brazil
2Faculty of Chemical Engineering, Federal University of Pará, Belém, PA, 66075-110, Brazil
3Deparatament of Mechanical Engineering, Federal University of Amazonas, Manaus, AM, 69067-005, Brazil
4Faculty of Materials Engineering, Federal University of Pará, Belém, PA, 66075-110, Brazil
چکیده
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.
کلیدواژه‌ها
Parameter estimation؛ Model selection؛ ABC؛ Propionic acid
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