سال انتشار: ۱۳۸۳

محل انتشار: نهمین کنگره ملی مهندسی شیمی ایران

تعداد صفحات: ۱۱

نویسنده(ها):

ZAHEDI – Department of Chemical Engineering, Oil and Gas, Shiraz University, Shiraz
JAHANMIRI – Department of Chemical Engineering, Oil and Gas, Shiraz University, Shiraz
RAHIMPOR – Department of Chemical Engineering, Oil and Gas, Shiraz University, Shiraz

چکیده:

this work an Artificial Neural Networks (ANN) pproach predicts the deactivation of the catalyst at different operating conditions as a function of time. By the aid of ANN sufficient data were generated which vary with time and agree very well with experimental data. Capability of model in generating deactivation data in different temperatures, pressures and feed compositions was excellent. The proposed method has great potential as a means to compensate for lack of the phenomenological kinetic modeling techniques.