TY  - JOUR
SN  - 09307516
PB  - John Wiley and Sons Inc
EP  - 1488
AV  - none
N1  - cited By 5
TI  - Development of a Prediction Model for Gas Hydrate Formation in Multiphase Pipelines by Artificial Intelligence
SP  - 1482
Y1  - 2022///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131558344&doi=10.1002%2fceat.202100359&partnerID=40&md5=b819ba87c634114e0372e4f1bdea8f1a
A1  - Sayani, J.K.S.
A1  - Sivabalan, V.
A1  - Foo, K.S.
A1  - Pedapati, S.R.
A1  - Lal, B.
JF  - Chemical Engineering and Technology
VL  - 45
N2  - 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.
IS  - 8
KW  - Forecasting; Gas hydrates; Gases; Hydration; Pipelines; Reaction kinetics
KW  -  Flow behaviours; Formation kinetics; Gas hydrates formation; Multi phase systems; Multilayers perceptrons; Multiphase flow behavior; Multiphase gas; Multiphase pipelines; Prediction modelling; Single-layer perceptrons
KW  -  Neural networks
ID  - scholars16546
ER  -