• 文献标题:   Comprehensive investigation of reduced graphene oxide (rGO) in the base fluid: thermal analysis and ANN modeling
  • 文献类型:   Article
  • 作  者:   ALKANHAL TA
  • 作者关键词:   nanofluid, thermal conductivity, artificial neural network, heat transfer, correlation
  • 出版物名称:   JOURNAL OF THERMAL ANALYSIS CALORIMETRY
  • ISSN:   1388-6150 EI 1588-2926
  • 通讯作者地址:  
  • 被引频次:   8
  • DOI:   10.1007/s10973-020-10433-3 EA JAN 2021
  • 出版年:   2021

▎ 摘  要

This study aims to examine the thermal conductivity of reduced Graphene Oxide solid dispersed in the Water fluid. For this mono-nanofluid, thermal conductivity was examined in particular temperatures (25-50 degrees C) and mass fractions (1-5 mg mL(-1)). Field emission scanning electron microscope test was done to observe the microstructure of the solid. The results showed the highest thermal conductivity enhancement (31.19%) in 5 mass%-50 degrees C. A novel correlation including 1.25% utmost deviation was predicted via curve-fitting on the 3D-output to tally the thermal conductivity of the nanofluid. Then, an artificial neural network with R-2 = 0.99 was trained. Endmost, rGO/Water has satisfactory heat transfer capacity in thermal industries.