TY - JOUR
T1 - Modeling of syngas composition obtained from fixed bed gasifiers using Kuhn–Tucker multipliers
AU - Amaro, Jordan
AU - Rosado, Diego Jhovanny Mariños
AU - Mendiburu, Andrés Z.
AU - dos Santos, Leila Ribeiro
AU - de Carvalho., João A.
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2021/3/1
Y1 - 2021/3/1
N2 - 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.
AB - 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.
KW - Biomass
KW - Chemical equilibrium model
KW - Fixed bed
KW - Gasification
KW - Syngas
UR - https://www.scopus.com/pages/publications/85097767649
U2 - 10.1016/j.fuel.2020.119068
DO - 10.1016/j.fuel.2020.119068
M3 - Article
AN - SCOPUS:85097767649
SN - 0016-2361
VL - 287
JO - Fuel
JF - Fuel
M1 - 119068
ER -