پیش بینی شرایط ترمودینامیکی تشکیل هیدرات های شبه کلاتریت برای سیستم های (متان / کربن دی اکسید / نیتروژن) + TBAC + آب با ستفاده از شبکه های عصبی مصنوعی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشکده فنی و مهندسی، دانشگاه بجنورد، ایران

2 دانشکده علوم پایه، دانشگاه بجنورد، ایران

3 دانشکده فنی و مهندسی، دانشگاه شهرکرد، ایران

چکیده

شبه‏کلاتریت‏ها ساختارهایی جدید از هیدرات‏های گازی هستند که شرایط ترمودینامیکی تشکیل هیدرات گازی در آنها از هیدرات‏های کلاتریت بسیار راحت‏تر است. مدل‏های ارایه‏شده برای پیش‏بینی شرایط ترمودینامیکی شبه‏کلاتریت‏ها انگشت‏شماراند. در کار حاضر از ابزار شبکه عصبی مصنوعی با ساختار پرسپترون چندلایه برای پیش‏بینی شرایط ترمودینامیکی تشکیل هیدرات شبه‏کلاتریت برای سیستم‏های آب + تترا ان- بوتیل آمونیوم کلراید(TBAC) + متان/ کربن‏دی‏اکسید/ نیتروژن استفاده شده است. محدوده‏ای وسیع از داده‏های ترمودینامیکی موجود در مقالات، شامل 195 داده آزمایشگاهی، برای توسعه این مدل ترمودینامیکی و از TBAC با غلظت‌های 0 تا 18/36% وزنی برای آموزش شبکه استفاده شد. 85% از داده‏های آزمایشگاهی استفاده‏شده در این مقاله برای آموزش شبکه عصبی مصنوعی توسعه‏داده‏شده به کار گرفته شد. برای آزمودن شبکه توسعه‏داده‏شده، تعدادی داده آزمایشگاهی مستقل که در آموزش شبکه از آنها استفاده نشده است به کار رفت. نتایج پیش‏بینی‏های شبکه عصبی توسعه‏داده‏شده نشان دادند که این پیش‏بینی‏ها و داده‌های آزمایشگاهی تطابقی خوب دارند.
 

کلیدواژه‌ها


عنوان مقاله [English]

The Prediction of Semiclathrate Hydrate Dissociation Conditions by Artificial Neural Network Tools for the Systems of (Methane / Carbon Dioxide / Nitrogen) + TBAC + Water

نویسندگان [English]

  • Abolfazl Mohammadi 1
  • Zeinab Arabasadi 2
  • Alireza Jahangiri 3
  • Ali Asghar Yarifard 1
1 Faculty of Engineering, University of Bojnord, Iran
2 Faculty of Science, University of Bojnord, Iran
3 Faculty of Engineering, Shahrekord University, Iran
چکیده [English]

Semiclathrate hydrates are new structure of gas hydrates that dramatically promote the gas hydrate dissociation conditions, but there are few thermodynamic models to predict the semiclathrate hydrate dissociation conditions. In this research, the multi-layer perceptron artificial neural network tools were employed to predict the semiclathrate hydrate dissociation conditions for the systems of methane + TBAC + water, carbon dioxide + TBAC + water, and nitrogen + TBAC + water. A wide range of experimental data which was reported in the literature was used to develop this algorithm. Mass fraction (0 - 0.3618) TBAC aqueous solution data were utilized to train the artificial neural network. %85 of literature data points were used to train and develop the network and 15% of literature data points were used to examine the developed artificial neural networks. The predicted data by the developed artificial neural network (for the systems of methane + TBAC + water, carbon dioxide + TBAC + water, and nitrogen + TBAC + water) showed an acceptable agreement with experimental data.
 

کلیدواژه‌ها [English]

  • Semiclathrate Hydrates, Gas Hydrate, TBAC
  • Neural Network, Artificial Intelligence

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