eprintid: 16546
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/65/46
datestamp: 2023-12-19 03:23:03
lastmod: 2023-12-19 03:23:03
status_changed: 2023-12-19 03:06:27
type: article
metadata_visibility: show
creators_name: Sayani, J.K.S.
creators_name: Sivabalan, V.
creators_name: Foo, K.S.
creators_name: Pedapati, S.R.
creators_name: Lal, B.
title: Development of a Prediction Model for Gas Hydrate Formation in Multiphase Pipelines by Artificial Intelligence
ispublished: pub
keywords: Forecasting; Gas hydrates; Gases; Hydration; Pipelines; Reaction kinetics, Flow behaviours; Formation kinetics; Gas hydrates formation; Multi phase systems; Multilayers perceptrons; Multiphase flow behavior; Multiphase gas; Multiphase pipelines; Prediction modelling; Single-layer perceptrons, Neural networks
note: cited By 5
abstract: A prediction model is developed by means of artificial neural networks (ANNs) to determine the gas hydrate formation kinetics in multiphase gas dominant pipelines with crude oil. Experiments are conducted to determine the rate of formation and reaction kinetics of hydrates formation in multiphase systems. Based on the results, an artificial intelligence model is proposed to predict the gas hydrate formation rate in multiphase transmission pipelines. Two ANN models are suggested with single-layer perceptron (SLP) and multilayer perceptron (MLP). The MLP shows more accurate prediction when compared to SLP. The models were predicted accurately with high prediction accuracy both for the pure and multiphase systems. © 2022 Wiley-VCH GmbH.
date: 2022
publisher: John Wiley and Sons Inc
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131558344&doi=10.1002%2fceat.202100359&partnerID=40&md5=b819ba87c634114e0372e4f1bdea8f1a
id_number: 10.1002/ceat.202100359
full_text_status: none
publication: Chemical Engineering and Technology
volume: 45
number: 8
pagerange: 1482-1488
refereed: TRUE
issn: 09307516
citation:   Sayani, J.K.S. and Sivabalan, V. and Foo, K.S. and Pedapati, S.R. and Lal, B.  (2022) Development of a Prediction Model for Gas Hydrate Formation in Multiphase Pipelines by Artificial Intelligence.  Chemical Engineering and Technology, 45 (8).  pp. 1482-1488.  ISSN 09307516