Machine learning based modeling of pollutant and heat transfer in ternary nanofluid flow through porous media

Ali Haider, Assad Ayub, Zhanbin Yuan, Yufeng Nie, M.S. Anwar, Taoufik Saidani and Taseer Muhammad

Chaos, Solitons & Fractals, 2025, vol. 199, issue P3

Abstract: Significance: This study provides a novel approach to optimizing thermal and mass transfer in magnetically controlled ternary hybrid nanofluids using an Artificial Neural Network (ANN) framework. The ANN-based predictive model improves computational efficiency, and it makes the findings highly relevant for applications in environmental pollution control, industrial heat exchangers, and advanced cooling systems.

Keywords: Heat and mass transfer; Artificial Neural Network; Porous media; Inclined magnetic field; Cross fluid; Ternary hybrid nanofluid; Pollutants source parameters (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:199:y:2025:i:p3:s0960077925009038

DOI: 10.1016/j.chaos.2025.116890

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