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Investigation of flow Maldistribution in Trickle Bed Reactors Dense and Sock Loading Beds

عنوان مقاله: Investigation of flow Maldistribution in Trickle Bed Reactors Dense and Sock Loading Beds
شناسه ملی مقاله: ICHEC07_032
منتشر شده در هفتمین کنگره ملی مهندسی شیمی در سال 1390
مشخصات نویسندگان مقاله:

m Bazmi - Computational Fluid Dynamics (CFD) Research Laboratory, School of Chemical Engineering, Iran University of Science and Technology, Narmak, Tehran, ۱۶۸۴۶, Iran Research Institute of Petroleum Industry, Tehran, Iran
s.h Hashemabadi - Computational Fluid Dynamics (CFD) Research Laboratory, School of Chemical Engineering, Iran University of Science and Technology, Narmak, Tehran, ۱۶۸۴۶, Iran
m Bayat - Research Institute of Petroleum Industry, Tehran, Iran

خلاصه مقاله:
Liquid mal-distribution in catalytic Trickle bed reactor have investigated using porous alumina extrudate trilobe catalysts. Two different catalyst loading methos (dense and sock) were used toevaluate the performances of the dense and sock loaded bed in terms of liquid spreading. Theexperimental setup has capability for studying the effect of bed height on distribution of the liquid for different gas and liquid flow rates. A collector device with seven compartments has been usedin bottom of the reactor to investigate the liquid radial distribution. Furthermore, an Artificial Neural Network (ANN) algorithm has been applied to predict the effective parameters on liquid spreading in trickle bed using the obtained experimental data. was concluded that with same liquiddistributor and operating conditions, the sock packed beds distribute liquid better than dense ones.It was explaind that these results are due to the Isotropic distribution of porosity in sock loaded beds in comparison with dense beds. It was observed that any increase in gas and liquid flow rate enhances the liquid flow distribution; however, the effect of liquid flow rate is more considerable.

کلمات کلیدی:
trickle bed reactor, maldistribution, trilobe catalyst, dense and sock loading, artificial neural network

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/340786/