کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1757871 1523020 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modeling of microreactor for methane dry reforming: Comparison of Langmuir–Hinshelwood kinetic and microkinetic models
ترجمه فارسی عنوان
مدل سازی میکروسکوپ الکترونی برای رفنت کردن خشکی متان: مقایسه مدل های جنبشی و میکروکینتیک لانگمیورا هینشلوود
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علوم زمین و سیاره ای (عمومی)
چکیده انگلیسی


• Synthesis gas (hydrogen and carbon monoxide) production was investigated by a two-dimensional numerical model of single microchannel.
• Computational fluid dynamic (CFD) modeling with detailed chemistry (MK model) and LHK model was conducted to understand the DR on rhodium (Rh) catalyst.
• Langmuir–Hinshelwood kinetic (LHK) and microkinetic (MK) models for dry reforming (DR) process in a micro-reactor are compared.

Synthesis gas production via CO2 (dry reforming) of natural gas (mostly CH4) has attracted increasing since both are greenhouse gases. The aim of this work is the comparison of Langmuir–Hinshelwood kinetic (LHK) and microkinetic (MK) models for dry reforming (DR) process in a micro-reactor. In this paper, synthesis gas (hydrogen and carbon monoxide) production was investigated by a two-dimensional numerical model of single microchannel. Computational fluid dynamic (CFD) modeling with detailed chemistry (MK model) and LHK model was conducted to understand the DR on rhodium (Rh) catalyst. Microchannel wall temperature, pressure, CH4/CO2, hydrogen, carbon monoxide, and steam concentrations in feed stream are selected as the effective parameters on microchannel performance. Study results show that increasing wall temperature in LHK model, CO concentration and pressure in MK model have positive effect on methane conversion of microreactor. Also, decreasing CH4/CO, steam concentration in LHK model and wall temperature, CH4/CO, hydrogen composition in MK model have same behavior. Finally, results present LHK model is more suitable than current MK model for predicting DR process behavior.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Natural Gas Science and Engineering - Volume 20, September 2014, Pages 99–108
نویسندگان
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