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ORCID: https://orcid.org/0000-0002-9769-8382, Díaz Moreno, Ismael
ORCID: https://orcid.org/0000-0001-6745-0960 and Rodríguez Hernández, Manuel
ORCID: https://orcid.org/0000-0003-0929-5477
(2025).
Comparative analysis of aspen plus simulation strategies for woody biomass air gasification processes.
"Biomass and Bioenergy", v. 194
;
p. 107626.
ISSN 09619534.
https://doi.org/10.1016/j.biombioe.2025.107626.
| Título: | Comparative analysis of aspen plus simulation strategies for woody biomass air gasification processes |
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| Autor/es: |
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| Tipo de Documento: | Artículo |
| Título de Revista/Publicación: | Biomass and Bioenergy |
| Fecha: | 30 Enero 2025 |
| ISSN: | 09619534 |
| Volumen: | 194 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Air gasification; Alternative energy; Aspen Plus; Biomass; Biomass air gasification; Comparative Study; Fossil Fuel; gas production; Kinetic modeling; Optimal solutions; Reaction Kinetics; Renewable Energy; Sensitivity Analysis; Syngas; thermal modeling; Thermodynamic modeling; Thermodynamics; Woody Biomass |
| Escuela: | E.T.S.I. Industriales (UPM) |
| Departamento: | Ingeniería Química Industrial y del Medio Ambiente |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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Biomass gasification is gaining attention because of its role in transition to a low-carbon chemical industry, providing a cleaner alternative to fossil fuels in energy and chemical production. However, accurate modeling remains challenging due to the variability in syngas composition across varying biomass types, gasifiers, and operating conditions. This study evaluates the performance of thermodynamic equilibrium modeling (TEM), restricted thermodynamic modeling (RTM), and kinetic modeling (KM) by Aspen Plus to model a fluidized bubbling-bed reactor. The novelty of the research lies in the comparative evaluation of these models in diverse woody biomasses and gasification conditions, addressing a significant gap in the field. Experimental data was curated and used to assess the predictive precision of each approach, focusing on syngas components such as H2, CO, CO2, and CH4. Moreover, sensitivity analysis was performed within the RTM framework to identify optimal approach temperatures for selected. On the basis of these approach temperatures, syngas predictions were carried out, which are referred to as the optimal solution (OS). RTM demonstrated the highest accuracy, with an average RMSE of 0.0793, while TEM showed the lowest accuracy with RMSE of 0.1735. KM and OS had intermediate precision, with RMSE values of 0.1593 and 0.1282, respectively. These results demonstrate that RTM is the most accurate and OS is a reliable alternative when kinetic data are unavailable. This study offers valuable information on the selection of effective modeling strategies for biomass gasification and the development of technologies based on syngas. © 2025 Elsevier Ltd
| ID de Registro: | 91072 |
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| Identificador DC: | https://oa.upm.es/91072/ |
| Identificador OAI: | oai:oa.upm.es:91072 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/10327735 |
| Identificador DOI: | 10.1016/j.biombioe.2025.107626 |
| URL Oficial: | https://www.sciencedirect.com/science/article/pii/... |
| Depositado por: | iMarina Portal Científico |
| Depositado el: | 25 Sep 2025 06:16 |
| Ultima Modificación: | 25 Sep 2025 06:16 |
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