123 / 2021-06-16 16:16:39
PERFORMANCE PREDICTION FOR DRY REFORMING OF METHANE IN A NS PULSED COAXIAL DIELECTRIC BARRIER DISCHARGE REACTOR USING ARTIFICIAL NEURAL NETWORK APPROACH
Abstract Accepted
ZhangPeng / Nanjing Tech University;College of Electrical Engineering and Control Science
DuanGehui / Nanjing Tech University;College of Electrical Engineering and Control Science
MeiDanhua / Nanjing Tech University;College of Electrical Engineering and Control Science
LiuShiyun / Nanjing Tech University;College of Electrical Engineering and Control Science
FangZhi / Nanjing Tech University;College of Electrical Engineering and Control Science
Dry reforming of methane has received great attention in the past three decades due to its high potential in resource utilization and environmental protection. This reaction can provide a practical method for conversion of the two major greenhouse gases simultaneously for the production of value-added fuels and chemicals. However, this process requires extreme reaction conditions with high temperature to obtain reasonable yield of value-added chemicals, which leads to carbon deposition on the catalyst surface and the deactivation of the catalyst. Therefore, several techniques have been proposed to improve the efficiency of the process of dry reforming of CH4, and non-thermal plasma has been investigated as an alternative method to the conventional chemical and/or catalytic processes. Among the non-thermal plasma techniques, DBD could be a suitable source for the plasma processes for dry reforming of CH4, due to its successful experience in ozone generation and gas cleaning on an industrial scale. In this study, an ns pulsed coaxial dielectric barrier discharge (DBD) reactor has been developed for plasma dry reforming of methane at ambient conditions. The effects of applied voltage, feed flow rate, discharge length, and CH4/CO2 molar ratio on the performance of the plasma was investigated. An artificial neural network (ANN) model was developed to simulate and predict the plasma reaction in terms of reactant conversion, selectivity to major products and energy efficiency of the process. The relative importance of the plasma processing parameters on the reaction performance was also evaluated. The simulated results obtained from the established ANN model agreed well with the experimental results. The CH4/CO2 molar ratio was found to be the most influential parameter with a relative weight of 52-59% for the plasma dry reforming of methane, while the discharge length was the least important parameter affecting the plasma process.

 
Important Date
  • Conference Date

    Jul 16

    2021

    to

    Jul 18

    2021

  • Jun 05 2021

    Draft paper submission deadline

Sponsored By
Electrical Contact and Arc Committee of China Electrotechnical Society
Power Transmission and Transformation Equipment Committee of China Electrotechnical Society
Engineering Dielectric Committee of China Electrotechnical Society
Power Transformation Committee of Chinese Society for Electrical Engineering
Plasmas and their Applications Committee of China Electrotechnical Society
Switchgear Committee of IEEE PES
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