Modeling and validation of the iodine-sulfur hydrogen production process

The iodine‐sulfur thermochemical water‐splitting cycle (I‐S process) is one of the highly efficient, CO2‐free, massive hydrogen production methods. We simulated the I‐S process through commercial software programs Aspen Plus and OLI database with the aid of self‐developed models to analyze the overa...

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Veröffentlicht in:AIChE journal 2014-02, Vol.60 (2), p.546-558
Hauptverfasser: Guo, Hanfei, Zhang, Ping, Chen, Songzhe, Wang, Laijun, Xu, Jingming
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Sprache:eng
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Zusammenfassung:The iodine‐sulfur thermochemical water‐splitting cycle (I‐S process) is one of the highly efficient, CO2‐free, massive hydrogen production methods. We simulated the I‐S process through commercial software programs Aspen Plus and OLI database with the aid of self‐developed models to analyze the overall running status of the process and to decrease the investment and time consumption of experiments. A two‐phase separator model operating at 353 K and an electro‐electrodialysis (EED) cell model working at 338 K were built on the basis of experimental data. The entire flow sheet of the I‐S process was modeled based on the two self‐developed models. The simulation models were validated through the experimental results obtained from the closed cycle I‐S facility (IS‐10) in our laboratory. By employing the simulation program, sensitivity analyses of the important parameters in the process were carried out, including the ratio of the distillate to the feed rate of the H2SO4 distillation column, reflux ratio of the H2SO4 column, H2SO4 conversion ratio, HI molality in the EED cathode outlet stream, and HI mole fraction in the liquid and vapor distillates of the HI distillation column. The key parameters significantly affecting the input duty were determined; that is, the ratio of the distillate to the feed rate of the H2SO4 distillation column and the HI molality in the EED cathode outlet stream. The optimal values of the analyzed parameters were also discussed. The simulation program we developed is a useful tool that can evaluate and optimize the I‐S process. © 2013 American Institute of Chemical Engineers AIChE J 60: 546–558, 2014
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.14285