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Modeling, Simulation and Optimization of Dry Reforming ofMethane Process by Using Artificial Neural Network and GeneticAlgorithm

عنوان مقاله: Modeling, Simulation and Optimization of Dry Reforming ofMethane Process by Using Artificial Neural Network and GeneticAlgorithm
شناسه ملی مقاله: CBGCONF03_034
منتشر شده در سومین کنفرانس ملی و اولین کنفرانس بین المللی پژوهش های کاربردی در علوم شیمی و مهندسی شیمی و سومین کنفرانس ملی و اولین کنفرانس بین المللی پژوهش های کاربردی در زیست شناسی در سال 1395
مشخصات نویسندگان مقاله:

H. R. Khaledian - Department of Chemical and Petroleum Engineering, Faculty of Science, University of Tab, Tabriz,Iran
A Farzi
S Bahrami
S S

خلاصه مقاله:
Dry reforming of methane is one of the main ways to produce syngas. A proper Kinetic model was employed for modeling of dry reforming reaction over Ni/Al2O3 in a fixed-bed catalytic reactor. In the simulation of the reactor, a one dimensional model is applied. After modeling and simulation, more than 100 data were obtained, these data used in Artificial Neural Network then a net was made and finally the optimization of H2/CO ratio by Genetic Algorithm was done. The flow rates which optimized by GA was used in the modeling that causes H2/CO ratio about one.

کلمات کلیدی:
DRM, ANN, GA, optimization, simulation, modeling

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/517129/