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Analysis of forced convection heat transfer to supercritical carbon dioxide inside tubes using neural networks.

Author(s) : SCALABRIN G., PIAZZA L.

Type of article: Article

Summary

The modelling of forced convection heat transfer for carbon dioxide flowing inside a heated tube under supercritical conditions was studied. The conventional models in the literature tend to modify a constant property correlation by including thermodynamic property terms that follow the heat flux trends. An innovative heuristic method is assumed for the first time to draw the case-specific heat transfer coefficient correlation from the experimental data based on quantity alone.

Details

  • Original title: Analysis of forced convection heat transfer to supercritical carbon dioxide inside tubes using neural networks.
  • Record ID : 2003-1725
  • Languages: English
  • Source: International Journal of Heat and Mass Transfer - vol. 46 - n. 7
  • Publication date: 2003/03

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