Heat Transfer Prediction of Supercritical R134a in Horizontal Pipe by Artificial Neural Network
Author:
Affiliation:
1. School of Chemical Engineering, Fuzhou University,Fuzhou,Fujian,China
2. School of Machine Engineering and Automation, Fuzhou University,Fuzhou,Fujian,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10351781/10351782/10351921.pdf?arnumber=10351921
Reference17 articles.
1. Systematic optimization of subcritical and transcritical organic Rankine cycles (ORCs) constrained by technical parameters in multiple applications
2. Heat transfer prediction of supercritical water with artificial neural networks
3. Modeling convective heat transfer of supercritical carbon dioxide using an artificial neural network
4. Thermal characteristics of in-tube upward supercritical CO2 flows and a new heat transfer prediction model based on artificial neural networks (ANN)
5. An artificial-neural-network based prediction of heat transfer behaviors for in-tube supercritical CO2 flow
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