Optimum parameter design for performance of methanol steam reformer combining Taguchi method with artificial neural network and genetic algorithm

Kwan Ouyang, Horng-Wen Wu, Shun Chieh Huang, Sheng Ju Wu

研究成果: Article

7 引文 (Scopus)

摘要

The fuel cell is powered by H 2 widely provided by reforming processes. A promising reforming process is methanol steam reforming which has received much attention. This study then attempts to acquire high hydrogen concentration, high methanol conversion efficiency and low CO concentration of methanol steam reforming. Three operating parameters were investigated: reacting temperature (T = 220–280 ° C), steam-to-carbonate ratio (S/C = 0.9 to 1.1), and the volume flow rate for nitrogen (N 2 ) carrier gas (Q=40 to 100cm 3 /min) as the flow rate of aqueous methanol solution was set as 3.1 cm 3 /min. The integrated approach of combining the Taguchi method with radial basis function neural network (RBFNN) was proposed in this study to demand an optimum parameter design. The results showed that the optimum parameter design was: T = 267 ° C, S/C = 1.1, and Q=40cm 3 /min. The averaged percentage reduction of quality loss (PRQL) of 3.31% was obtained as optimum condition was implemented, in comparison with the starting condition (the largest reacting temperature, steam-to-carbonate ratio, and N 2 volume flow rate). In addition, principal component analysis (PCA) is also investigated. The results obtained by PCA were compared with the ones by the integrated approach.

原文English
頁(從 - 到)446-458
頁數13
期刊Energy
138
DOIs
出版狀態Published - 2017 一月 1

指紋

Taguchi methods
Methanol
Steam
Genetic algorithms
Neural networks
Steam reforming
Flow rate
Reforming reactions
Principal component analysis
Carbonates
Conversion efficiency
Fuel cells
Nitrogen
Hydrogen
Temperature
Gases

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Pollution
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

引用此文

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title = "Optimum parameter design for performance of methanol steam reformer combining Taguchi method with artificial neural network and genetic algorithm",
abstract = "The fuel cell is powered by H 2 widely provided by reforming processes. A promising reforming process is methanol steam reforming which has received much attention. This study then attempts to acquire high hydrogen concentration, high methanol conversion efficiency and low CO concentration of methanol steam reforming. Three operating parameters were investigated: reacting temperature (T = 220–280 ° C), steam-to-carbonate ratio (S/C = 0.9 to 1.1), and the volume flow rate for nitrogen (N 2 ) carrier gas (Q=40 to 100cm 3 /min) as the flow rate of aqueous methanol solution was set as 3.1 cm 3 /min. The integrated approach of combining the Taguchi method with radial basis function neural network (RBFNN) was proposed in this study to demand an optimum parameter design. The results showed that the optimum parameter design was: T = 267 ° C, S/C = 1.1, and Q=40cm 3 /min. The averaged percentage reduction of quality loss (PRQL) of 3.31{\%} was obtained as optimum condition was implemented, in comparison with the starting condition (the largest reacting temperature, steam-to-carbonate ratio, and N 2 volume flow rate). In addition, principal component analysis (PCA) is also investigated. The results obtained by PCA were compared with the ones by the integrated approach.",
author = "Kwan Ouyang and Horng-Wen Wu and Huang, {Shun Chieh} and Wu, {Sheng Ju}",
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AU - Ouyang, Kwan

AU - Wu, Horng-Wen

AU - Huang, Shun Chieh

AU - Wu, Sheng Ju

PY - 2017/1/1

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AB - The fuel cell is powered by H 2 widely provided by reforming processes. A promising reforming process is methanol steam reforming which has received much attention. This study then attempts to acquire high hydrogen concentration, high methanol conversion efficiency and low CO concentration of methanol steam reforming. Three operating parameters were investigated: reacting temperature (T = 220–280 ° C), steam-to-carbonate ratio (S/C = 0.9 to 1.1), and the volume flow rate for nitrogen (N 2 ) carrier gas (Q=40 to 100cm 3 /min) as the flow rate of aqueous methanol solution was set as 3.1 cm 3 /min. The integrated approach of combining the Taguchi method with radial basis function neural network (RBFNN) was proposed in this study to demand an optimum parameter design. The results showed that the optimum parameter design was: T = 267 ° C, S/C = 1.1, and Q=40cm 3 /min. The averaged percentage reduction of quality loss (PRQL) of 3.31% was obtained as optimum condition was implemented, in comparison with the starting condition (the largest reacting temperature, steam-to-carbonate ratio, and N 2 volume flow rate). In addition, principal component analysis (PCA) is also investigated. The results obtained by PCA were compared with the ones by the integrated approach.

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