Evaluation of two plumes jet plasma reactor for plasmolysis of H2O vapor and CO2 combinations – Optimization study

Wameath S. Abdul-Majeed, Qazi Nasir, Muzna H. Alajmi, Khaloud A. Almaqbali
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Abstract

A custom design multi-flying jet plasma torches (MFJPT) reactor was tested for plasmolysis of water vapor and mixtures of water vapor-carbon dioxide in a series of experimental investigations at various reactor operational parameters. Experimentation plans were applied within the range of induced power (100–300 watts) and various vapor/gas throughputs. The produced gases were analyzed through online gas chromatography. The results of water vapor plasmolysis in two schemes demonstrated the production of 1337 ppm of hydrogen from water vapor/argon and 1665 ppm from applying a water vapor/argon/CO2 combination. Valuable hydrocarbon gases (e.g., Ethane, Ethylene/Acetylene) were generated and detected at higher conversions upon introducing H2O vapor, argon, and CO2 mixtures. The experimental data were trained through machine learning and a Gaussian Process Regression (GPR) model has fitted the data quite well. Ultimately, optimization study outcomes are presented through a color heat-map for system scaling-up purposes.

Abstract Image

用于H2 O蒸汽和CO2组合等离子体裂解的双羽流喷射等离子体反应器的评估——优化研究
采用定制设计的多飞射流等离子体炬(MFJPT)反应器,在各种反应器运行参数下进行了水蒸气和水蒸气-二氧化碳混合物的等离子体裂解实验。实验计划在感应功率(100-300瓦)和各种蒸汽/气体吞吐量范围内应用。产生的气体通过在线气相色谱分析。两种方案的水蒸气等离子体裂解结果表明,水蒸气/氩气产生1337 ppm的氢,水蒸气/氩气/CO2组合产生1665 ppm的氢。有价值的碳氢化合物气体(如乙烷、乙烯/乙炔)在引入H2O蒸气、氩气和CO2混合物后,在更高的转化率下产生并检测到。实验数据通过机器学习进行训练,高斯过程回归(GPR)模型拟合效果较好。最后,优化研究结果通过彩色热图呈现,用于系统扩展目的。
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