Machine learning based prediction of heat transfer deterioration of supercritical fluid in upward vertical tubes
Authors:
- Runfeng XiaoRXRunfeng Xiao
- Pingtao ZhangPZPingtao Zhang
- Liang ChenLCLiang Chen
- Yu HouYHYu Hou
- 26 March 2023
- journal article
- research article
- Published by Elsevier in Applied Thermal Engineering
- Vol. 228
Abstract
No abstract availableKeywords
Funding Information
- Education Department of Shaanxi Province
- Xi’an Jiaotong University (xzy022022030)
- National Natural Science Foundation of China (52176020)
This publication has 48 references indexed in Scilit:
- Experimental study of the effects of flow acceleration and buoyancy on heat transfer in a supercritical fluid flow in a circular tubeNuclear Engineering and Design, 2010
- Investigation of forced convection heat transfer of supercritical pressure water in a vertically upward internally ribbed tubeNuclear Engineering and Design, 2009
- A simplified method for heat transfer prediction of supercritical fluids in circular tubesAnnals of Nuclear Energy, 2009
- Heat transfer characteristics of a supercritical fluid flow in a vertical pipeThe Journal of Supercritical Fluids, 2008
- Wall temperature measurement and heat transfer correlation of turbulent supercritical carbon dioxide flow in vertical circular/non-circular tubesNuclear Engineering and Design, 2007
- Numerical analysis of heat transfer in supercritical water cooled flow channelsNuclear Engineering and Design, 2007
- Heat transfer under supercritical pressures and heat transfer deterioration boundariesThermal Engineering, 2006
- Where did the Dittus and Boelter equation come from?International Journal of Heat and Mass Transfer, 1998
- Numerical analysis of deterioration phenomena in heat transfer to supercritical waterInternational Journal of Heat and Mass Transfer, 1995
- Forced convective heat transfer to supercritical water flowing in tubesInternational Journal of Heat and Mass Transfer, 1972