Open-Source Modeling of Syngas Production from Biomass: A Code-Driven Approach
[EN] Plasma gasification is a promising thermochemical technology for converting municipal solid waste into syngas with a reduced environmental impact. However, research in this field is limited to the use of black-box software, which impedes methodological innovation and is key to advanced research...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/231641 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/231641 |
| Access Level: | acceso abierto |
| Palabra clave: | Biomass Gasification Modeling Open-source Plasma Syngas 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos |
| Sumario: | [EN] Plasma gasification is a promising thermochemical technology for converting municipal solid waste into syngas with a reduced environmental impact. However, research in this field is limited to the use of black-box software, which impedes methodological innovation and is key to advanced research into gasification processes. This study proposes a fully open-source and modular simulation model for plasma gasification of municipal solid waste developed in Python. The model consists of three interconnected modules: (1) decomposition of biomass into its elemental constituents, (2) simulation of the plasma gasifying stream, and (3) kinetic modeling of chemical reactions in a plug-flow reactor (PFR). Thermodynamic properties and reaction kinetics are implemented by using scientific Python libraries (Pyromat, CoolProp, Pint, NumPy, and SciPy).The model was validated against commercial Aspen Plus simulations by using experimental data. It achieved low mean absolute percentage errors (MAPEs) of 1.04% for Modules 1 and 2 and 14.19% for the reactor model. The predicted syngas composition at the reactor outlet was 44.3% hydrogen, 18.2% carbon monoxide, 12.7% carbon dioxide, and 14.8% water vapor (on a molar basis). Sensitivity analysis showed that increasing the air equivalence ratio from 0.04 to 0.16 reduced hydrogen and carbon monoxide concentrations by 25.7% and 42.4%, respectively. The optimal steam-to-fuel ratio was 0.08, which maximized hydrogen production to up to 45.5%. This open-source framework enables reproducible research and can be expanded with optimization algorithms and environmental or techno-economic assessments in future studies. |
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