سال انتشار: ۱۳۸۴

محل انتشار: دهمین کنگره ملی مهندسی شیمی ایران

تعداد صفحات: ۱۴

نویسنده(ها):

ZAHEDI – Department of Chemical Engineering, University of Razi, Kermanshah, Iran

چکیده:

In this paper an Artificial Neural Network (ANN) model for the simulation of an industrial Hydrotreater Unit (HU) is presented. HU is one of the important oil refinery processes. Due to its complexity, the modeling poses a great challenge. The proposed model predicts hydrogen demand,
outlet API and sulfur weight percent as a function of inlet API and sulfur weight percent for seven different feedstocks. This study determines the optimum architecture of ANN, in order to achieve good generalization. The results show ANN capability to predict the measured data. The ANN
model is also compared to those of an existing simulator available at a local refinery. The comparison confirms the superiority of ANN model.