Received: 2026-01-17
Revised: 2026-02-22
Accepted: 2026-03-19
Published in Issue 2026-03-31
Copyright (c) 2026 Ahmad Esmaeeli, Mahmoudreza Khadangi Mahrood, Hossein Ghahremani (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
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Abstract
In recent decades, extensive research has been conducted on the use of nanoparticles with high thermal conductivity in automotive cooling systems. In this study, the performance of a radiator cooling system using nanofluids containing TiO₂ and Al₂O₃, in comparison with distilled water as the coolant, was investigated experimentally and through neural network modeling. The experiments were performed using different concentrations of TiO₂ and Al₂O₃ nanofluids at various engine speeds. Our results showed that the Al₂O₃ and water nanofluid with a 0.1% concentration and the TiO₂ and water nanofluid with a 0.05% concentration can improve the cooling system performance by 50% and 25%, respectively, compared to pure deionized (DI) water. The data obtained in this experiment were analyzed using the GMDH neural network algorithm, and the model showed strong agreement with the experimental results, with deviations of only 6.8% and 8.2% for TiO₂ and Al₂O₃ nanoparticles, respectively. These findings demonstrate the significant potential of low-concentration TiO₂ and Al₂O₃ nanofluids to enhance automotive cooling efficiency, highlighting their applicability as promising alternatives to conventional coolant fluids.
Keywords
- Al₂O₃,
- Car radiator,
- Nanofluid,
- Neural network,
- TiO₂
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