Synthesis, stability, thermophysical properties and heat transfer applications of nanofluid–A review

B Mehta, D Subhedar, H Panchal, Z Said - Journal of Molecular Liquids, 2022 - Elsevier
Nanofluid has been found exceptionally suitable in several heat transfer applications as a
working fluid due to its excellent thermophysical properties. Enhancement in thermophysical …

A critical review of specific heat capacity of hybrid nanofluids for thermal energy applications

H Adun, I Wole-Osho, EC Okonkwo, D Kavaz… - Journal of Molecular …, 2021 - Elsevier
Nanofluids have gained tremendous research interests in diverse fields of study due to their
improved properties, especially as heat transfer fluids. Numerous studies have revealed the …

Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system

P Sharma, Z Said, A Kumar, S Nizetic, A Pandey… - Energy & …, 2022 - ACS Publications
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 …

Viscosity and rheological behavior of Al2O3-Fe2O3/water-EG based hybrid nanofluid: a new correlation based on mixture ratio

VV Wanatasanappan, PK Kanti, P Sharma… - Journal of Molecular …, 2023 - Elsevier
The present study is a pure experimental investigation of the viscosity and rheological
properties of the Al 2 O 3-Fe 2 O 3 hybrid nanofluid and the development of a new …

Exploring the specific heat capacity of water-based hybrid nanofluids for solar energy applications: A comparative evaluation of modern ensemble machine learning …

Z Said, P Sharma, RM Elavarasan, AK Tiwari… - Journal of Energy …, 2022 - Elsevier
The current study aims to give insight into the usefulness of three underutilized yet
exceptionally efficient machine learning approaches in estimating the specific heat capacity …

Experimental analysis of novel ionic liquid-MXene hybrid nanofluid's energy storage properties: Model-prediction using modern ensemble machine learning methods

Z Said, P Sharma, N Aslfattahi, M Ghodbane - Journal of Energy Storage, 2022 - Elsevier
Abstracts The current work employs two modern ensemble machine learning algorithms,
Matern 5/2 Gaussian process regression (GPR) and quadratic support vector regression …

Optimized ANFIS models based on grid partitioning, subtractive clustering, and fuzzy C-means to precise prediction of thermophysical properties of hybrid nanofluids

Z Zhang, M Al-Bahrani, B Ruhani… - Chemical Engineering …, 2023 - Elsevier
Applying machine learning algorithms in the prediction of nanofluids' thermophysical
properties such as density, viscosity, thermal conductivity (TC), and specific heat capacity …

Comparative evaluation of AI‐based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe3O4‐coated MWCNT hybrid nanofluids for …

P Sharma, Z Said, S Memon… - … Journal of Energy …, 2022 - Wiley Online Library
Hybrid nanofluids are gaining popularity owing to the synergistic effects of nanoparticles,
which provide them with better heat transfer capabilities than base fluids and normal …

Estimating the density of hybrid nanofluids for thermal energy application: Application of non-parametric and evolutionary polynomial regression data-intelligent …

M Jamei, M Karbasi, M Mosharaf-Dehkordi… - Measurement, 2022 - Elsevier
There is no doubt that density is one of the most crucial thermophysical properties of hybrid
nanofluids in thermal energy applications. Various research papers have been devoted to …

[HTML][HTML] Radiation effect on unsteady MHD mixed convection of kerosene oil-based CNT nanofluid using finite element analysis

R Hossain, AK Azad, MJ Hasan, MM Rahman - Alexandria Engineering …, 2022 - Elsevier
This work conducts a numerical analysis of thermal radiation with a semicircular heater on
the middle part of the bottom wall and a sliding lid on the top in a square enclosure …