سال انتشار: ۱۳۸۶

محل انتشار: پنجمین کنگره بین المللی مهندسی شیمی

تعداد صفحات: ۸

نویسنده(ها):

Mohsen Bashiri – Simulation and AI research center, Dept. of Chemical Engineering, Razi University, Kermanshah, Iran.
Gholamreza Zahedi – Simulation and AI research center, Dept. of Chemical Engineering, Razi University, Kermanshah, Iran.
Yazdan Shirvany – Dept. of Electronic Engineering, Razi University, Kermanshah, Iran.

چکیده:

In this paper a new method based an Artificial Neural Network (ANN) for prediction of natural gas mixture water content is presented. The dehydration of natural gas is very important in the gas processing industry, for design of facilities of the production, transmission, and processing of natural gas. It is necessary to remove water vapor present in the gas stream that may cause hydrate formation at lowtemperature conditions that may plug the valves and fittings in gas pipelines. In this study the available data for mixtures and available methods for predicting the water content of sour gas have been studied. Based on obtained results from ANN simulation , our methods is more accurate than current used methods and can be used in gas engineering studies.