Journal of Thermal Analysis and Calorimetry, ( ISI ), Volume (140), No (6), Year (2019-11) , Pages (2765-2778)

Title : ( Machine learning methods for precise calculation of temperature drop during a throttling process )

Authors: Mahmood Farzaneh-Gord , mohammad reza Rahbari , B. Mohseni Gharyehsafa , A. Toikka , I. Zvereva ,

Citation: BibTeX | EndNote

Abstract

It is vital for the designers of the throttling facilities to predict natural gas temperature drop along a throttling valve exactly. Generally, direct prediction of the temperature drop is not possible even by employing equations of states. In this work, artificial neural network method, specifically multilayer perceptron, is utilized to predict the physical properties of natural gas. Then, the method is employed for direct calculation of the temperature drop along a throttling process. To train, validate and test the network, a large database of natural gas fields of Iran plus some experimental data (30,000 random datasets) are gathered from the literature. In addition, according to complexity of the multilayer perceptron model, a group method of data handling approach is used to simplify the major trained network. For the first time, an equation is developed for calculating natural gas temperature drop as a function of molecular weight as well as pressure drop. The results show that the multilayer perceptron and group method of data handling methods have the error R2 = 0.998 and R2 = 0.997, respectively. In addition, the results indicate that both developed machine learning methods present a high accuracy in the calculations over a wide range of gas mixtures and input properties ranges.

Keywords

Throttling process; Artificial neural network Multilayer perceptron; Group method of data handling; Natural gas temperature drop; Natural gas compositions effects
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

@article{paperid:1077074,
author = {Farzaneh-Gord, Mahmood and Rahbari, Mohammad Reza and B. Mohseni Gharyehsafa and A. Toikka and I. Zvereva},
title = {Machine learning methods for precise calculation of temperature drop during a throttling process},
journal = {Journal of Thermal Analysis and Calorimetry},
year = {2019},
volume = {140},
number = {6},
month = {November},
issn = {1388-6150},
pages = {2765--2778},
numpages = {13},
keywords = {Throttling process; Artificial neural network Multilayer perceptron; Group method of data handling; Natural gas temperature drop; Natural gas compositions effects},
}

[Download]

%0 Journal Article
%T Machine learning methods for precise calculation of temperature drop during a throttling process
%A Farzaneh-Gord, Mahmood
%A Rahbari, Mohammad Reza
%A B. Mohseni Gharyehsafa
%A A. Toikka
%A I. Zvereva
%J Journal of Thermal Analysis and Calorimetry
%@ 1388-6150
%D 2019

[Download]