Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods

Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods

Background: Because of their enhanced thermophysical characteristics, namely greater thermal conductivity, viscosity control, and long-term stability than traditional nanofluids, hybrid nanofluids drew interest. Such properties make them suitable candidates for many industrial applications such as s...

Full description

Saved in:
Bibliographic Details
Main Authors: Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein, Narinderjit Singh Sawaran Singh, Barno Abdullaeva, Zubair Ahmad, Soheil Salahshour, Mohammadreza Baghoolizadeh, Mostafa Pirmoradian
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Case Studies in Thermal Engineering
Subjects:
Thermophysical properties
Hybrid nanofluids
Machine learning methods
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X25002989
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items