Experimental characterization and predictive modelling of Al2O3/MWCNT hybrid nanofluid thermophysical properties using ANN, ANFIS, FCM and hybrid techniques

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Momin_Experimental_2026.pdf (3.74 MB)
Momin_Experimental_2026.pdf (3.74 MB)

Date

2026-07

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Publisher

Springer

Abstract

Please read abstract in the article.

Description

DATA AVAILABILITY : The data can be made available upon request from the corresponding author.

Keywords

Correlation development, Thermophysical properties, Machine learning modelling, Hybrid nanofluids, Energy systems

Sustainable Development Goals

SDG-07: Affordable and clean energy
SDG-09: Industry, innovation and infrastructure

Citation

Momin, M., Atofarati, E.O., Oladipo, S. et al. Experimental characterization and predictive modelling of Al2O3/MWCNT hybrid nanofluid thermophysical properties using ANN, ANFIS, FCM and hybrid techniques. Journal of Thermal Analysis and Calorimetry 151, 11041–11071 (2026). https://doi.org/10.1007/s10973-026-15698-8.

URI

http://hdl.handle.net/2263/111171

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Research Articles (Mechanical and Aeronautical Engineering)
Research Articles (University of Pretoria)
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