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Modeling of syngas composition obtained from fixed bed gasifiers using Kuhn–Tucker multipliers

Amaro, Jordan ; Rosado, Diego Jhovanny Mariños ; Mendiburu, Andrés Z. ; dos Santos, Leila Ribeiro ; de Carvalho Jr, João A.

Fuel (Guildford), 2021-03, Vol.287, p.119068, Article 119068 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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  • Título:
    Modeling of syngas composition obtained from fixed bed gasifiers using Kuhn–Tucker multipliers
  • Autor: Amaro, Jordan ; Rosado, Diego Jhovanny Mariños ; Mendiburu, Andrés Z. ; dos Santos, Leila Ribeiro ; de Carvalho Jr, João A.
  • Assuntos: Biomass ; Carbon ; Chemical equilibrium model ; Cold gas ; Composition ; Efficiency ; Fixed bed ; Fixed beds ; Gasification ; Multipliers ; Optimization ; Prediction models ; Root-mean-square errors ; Syngas ; Synthesis gas ; Temperature
  • É parte de: Fuel (Guildford), 2021-03, Vol.287, p.119068, Article 119068
  • Descrição: •The AOM is an excellent tool to establish PMs for the syngas composition obtained from the gasification of biomass in a fixed bed.•The AOM allows analytical calculation of the correction factors for the chemical equilibrium constants.•A PM is developed to estimate the syngas compositions.•The PM is a realistic model.•The PM was validated with six experimental compositions, yielding RMSE values smaller than or equal to 2.25. This work consists of developing a predictive model (PM) for syngas composition obtained from biomass gasification in fixed bed gasifiers. The PM is composed of three correlations which are made for carbon conversion efficiency, gasification temperature and the correction factor for the equilibrium constant of the water-gas homogeneous reaction. Such correlations were established using results obtained from the application of an optimization method (AOM) that uses Kuhn–Tucker multipliers. Syngas compositions determined through AOM were compared with experimental compositions and those estimated by other models, resulting that the AOM always determines the best estimates with respect to the root mean square error (RMSE). For syngas compositions estimated by AOM, the RMSE interval is [0.21, 4.11]. The PM was validated with six experimental compositions. From the predicted syngas compositions it was found that the ranges for LHV, cold gas efficiency, carbon conversion efficiency and gasification temperature were [4.594, 5.116 MJ/Nm3], [55.74, 68.18%], [74.20, 88.40%] and [749, 918 °C], respectively. Additionally, for the predicted syngas compositions the RMSE interval was determined as [0.68, 2.25]. Therefore, the PM was considered to be effective in estimating syngas compositions.
  • Editor: Kidlington: Elsevier Ltd
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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