Optimization of Hydrogen Sulfide Reactive Absorption in Spray Column by Response Surface Methodology
Publish place: International Conference on Engineering, Art and Environment
Publish Year: 1393
نوع سند: مقاله کنفرانسی
زبان: English
View: 800
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
CEAE01_126
تاریخ نمایه سازی: 14 مرداد 1394
Abstract:
In the current study, hydrogen sulfide (H2S) removal from gas streams containing light hydrocarbons was performed in a spray column by reactive absorption into sodium hydroxide solution. The influence of operating variables such as solution pH, solution temperature and liquid-to-gas volumetric ratio was investigated on the H2S removal efficiency. Response surface methodology (RSM) was applied to investigate the individual and interactive effects of the independent operating variables on the H2S removal efficiency as the response. RSM was employed to optimize the operating variables which were effective on the response. In the experiments, the operating variables of solution pH, solution temperature and liquid-to-gas volumetric ratio were varied in the range of 12-14, 40-60°C and 15×10-3-30×10-3, respectively. The maximum of removal efficiency was obtained 99.4±0.1% with employing optimal operating variables of pH 13.6, 42.3 °C and 21.8×10-3 of liquid-to-gas volumetric ratio predicted by RSM polynomial model. A very satisfactory compatibility is observed in the comparison of experimental data and second-order response surface modeling predictions.
Keywords:
Authors
Fatemeh Bashipour
Ph. D. Student of Department of Chemical Engineering, Isfahan University of Technology, Isfahan ۸۴۱۵۶-۸۳۱۱۱, Iran
Amir Rahimi
Associate Professor of Department of Chemical Engineering, College of Engineering, University of Isfahan, Isfahan ۸۱۷۴۶–۷۳۴۴۱, Iran.
Saied Nouri Khorasani
Associate Professor of Department of Chemical Engineering, Isfahan University of Technology, Isfahan ۸۴۱۵۶-۸۳۱۱۱, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :