Artificial Neural Networks model for predicting wall temperature of supercritical boilers

• Published in: Applied thermal engineering Vol. 90; pp. 749 - 753
• Main Authors: Dhanuskodi, R., Kaliappan, R., Suresh, S., Anantharaman, N., Arunagiri, A., Krishnaiah, J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2015
• Subjects: ANN; Boiler design; Computational fluid dynamics; Fluid flow; Inner-wall temperature; Learning theory; Mathematical models; Neural networks; Supercritical; Turbulence; Turbulent flow; Wall temperature; ANN; Supercritical; Inner-wall temperature; Boiler design

Prediction of wall temperature for the range of operating conditions and selecting appropriate material for water-wall tubes, cooled by turbulent water/steam with drastic changes in property, is important in boiler design. An analytical route of predicting the wall temperature for such flow conditio...