Comparative analysis of aspen plus simulation strategies for woody biomass air gasification processes

Khan Jadoon, Usman 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.

Descripción

Título: Comparative analysis of aspen plus simulation strategies for woody biomass air gasification processes
Autor/es:
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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Resumen

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

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Horizonte 2020
945139
Sin especificar
Sin especificar
Programme under the Marie Skłodowska-Curie

Más información

ID de Registro: 91072
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