عنوان :
بررسي راكتور كاتاليستي هيدروژن زدائي ايزوبوتان و شبيه سازي توسط شبكه هاي عصبي مصنوعي
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
مهندسي شيمي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مهندسي شيمي
صفحه شمار :
سيزده،91ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
محمدرضا احساني، احمد محب
توصيفگر ها :
د هيدروژناسيون , راكتور بستر ثابت , الگوريتم ژنتيك
تاريخ نمايه سازي :
13/7/89
استاد داور :
ارجمند مهرباني، حميد زيلويي
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Investigation of Dehydrogenation of Iso Butane Catalytic Reactor Simulation with Artificial Neural Networks Anis Bakhshi anisb62@yahoo com Department of Chemical Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiMohammad Reza Ehsani ehsanimr@cc iut ac irAhmad Moheb ahmad@cc iut ac irAbstractDehydrogenation of isobutane to isobutene has recently received considerable attention because of the increasingdemand for Methyl tert butyle ether MTBE and Ethyl tertiary butyl ether ETBE which is used as additives forgasoline to increase the octane number and to substitute Lead In this research by using bench scale fixed bedreactor existing in BIPC conversion of isobutane and the effective parameters on it such as pressure temperature concentrations of feed has experimentally investigated Due to simple geometry and small reactordiameter with respect to its length one dimensional model was developed to simulate fixed bed reactor fordehydrogenation of isobutane by using mass and energy conservation laws Inter and intraparticle resistance wasbeing neglected due to small diameter of catalyst particle The 4th Rung Kutta approach was used to solvegoverning equation including the feed and production concentration gas temperature and pressure drop Theseset of equations have been solved by programming in MATLAB In the next step artificial neural network isused to predict conversion of isobutane in fixed bed reactor The experimental data have been used to create aGA ANN model 2 neurons for the hidden layers have been achieved by trial and error method and acceptableresults are obtained In order to increase the efficiency of neural networks genetic algorithm is used to optimizethe parameters of neural network By increasing 150 degrees of centigrade in temperature in both experimentaland mathematical model results observed that conversion of isobutane increased about 80 Also by decreasingof pressure and increasing in hydrocarbon to hydrogen fraction conversion of isobutane increased The resultsfrom the model are in good agreement with the experimental data Finally comparison of the results of the GAoptimized ANN model with analytical model and experimental data have been done Keywords Isobutane Dehydrogenation Fixed Bed Reactor Neural Network Genetic Algorithm
استاد راهنما :
محمدرضا احساني، احمد محب
استاد داور :
ارجمند مهرباني، حميد زيلويي
