Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System
Delhi Skill and Entrepreneurship University · University of Sharjah · +12 more institutions
Abstract
Nanofluids have gained significant popularity in the field of sustainable and renewable energy systems. The heat transfer capacity of the working fluid has a huge impact on the efficiency of the renewable energy system. The addition of a small amount of high thermal conductivity solid nanoparticles to a base fluid improves heat transfer. Even though a large amount of research data is available in the literature, some results are contradictory. Many influencing factors, as well as nonlinearity and refutations, make nanofluid research highly challenging and obstruct its potentially valuable uses. On the other hand, data-driven machine learning techniques would be very useful in nanofluid research for forecasting…
Citation impact
- FWCI
- 13.73
- Percentile
- 100%
- References
- 333
Authors
12- PSPrabhakar SharmaCorresponding
Delhi Skill and Entrepreneurship University
- ZSZafar SaidCorresponding
University of Sharjah, National University of Sciences and Technology
- AKAnurag Kumar
Delhi Skill and Entrepreneurship University
- SNSandro Nižetić
University of Split
- APAshok Pandey
University of Petroleum and Energy Studies, Centre for Science and Environment, Indian Institute of Toxicology Research
Topics & keywords
- Nanofluid
- Computer science
- Renewable energy
- Artificial intelligence
- Machine learning
- Artificial neural network
- Heat transfer
- Process engineering