Optimization and analysis of syngas production from methane and CO2 via Taguchi approach, response surface methodology (RSM) and analysis of variance (ANOVA)
- Authors
- Chen, Wei-Hsin; Chiu, Guo-Lun; Ong, Hwai Chyuan; Lam, Su Shiung; Lim, Steven; Ok, Yong Sik; Kwon, Eilhann E.
- Issue Date
- 15-7월-2021
- Publisher
- ELSEVIER SCI LTD
- Keywords
- Catalytic partial oxidation of methane (CPOM); Spiral Swiss-roll reactor; Taguchi method; Response surface methodology (RSM); Syngas yield; Analysis of variance (ANOVA)
- Citation
- FUEL, v.296
- Indexed
- SCIE
SCOPUS
- Journal Title
- FUEL
- Volume
- 296
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/127710
- DOI
- 10.1016/j.fuel.2021.120642
- ISSN
- 0016-2361
- Abstract
- This study aims to figure out syngas production from methane and CO2 where the catalytic partial oxidation of methane over a rhodium-based catalyst bed in a Swiss-roll reactor is explored. The syngas yield from the best combination of gas hourly space velocity (GHSV), oxygen-to-methane molar ratio (O2/C ratio), and CO2-to- O2 molar ratio (CO2/O2 ratio) is acquired by a two-stage optimization, namely, the Taguchi approach followed by response surface methodology (RSM). In the first stage, the Taguchi approach suggests that the influences of the factors on the syngas yield are ranked by O2/C ratio > CO2/O2 ratio > GHSV, and the maximum syngas yield is 2.191 mol?(mol-CH4)- 1. Thereafter, the ranges of the three operating parameters are narrowed, and RSM and analysis of variance are used in the second stage to obtain a more precise optimization. In this stage, the significance of the regression coefficients indicating that GHSV and the combination of GHSV and O2/C ratio are pronounced. Based on the Box-Behnken experimental design, RSM analysis leads to the maximum syngas yield of 2.304 mol?(mol CH4)-1, lifting the syngas yield by 5.15% in the second stage. These results reveal that the syngas yield from the two-stage optimization (Taguchi + RSM) is more efficient than from the single-stage.
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Collections - College of Life Sciences and Biotechnology > Division of Environmental Science and Ecological Engineering > 1. Journal Articles
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