Intelligent prediction of thermodynamic performance in MHD Oldroyd B trihybrid nanofluids using artificial neural networks
Mamoon Aamir, Chemseddine Maatki, Aqsa Zafar Abbasi, Rajab Alsayegh, Karim Kriaa, Walid Hassen, Lioua Kolsi · 2026
Read Intelligent prediction of thermodynamic performance in MHD Oldroyd B trihybrid nanofluids using artificial neural networks by Mamoon Aamir, Chemseddine Maatki, Aqsa Zafar Abbasi, Rajab Alsayegh, Karim Kriaa, Walid Hassen, Lioua Kolsi (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13400500.txt.
Description
Mamoon Aamir and colleagues blend, in 2026, numerical physics with machine learning to predict heat and flow behavior in a complex nanofluid. The fluid carries three kinds of nanoparticles and follows an elastic model called Oldroyd-B, under a magnetic field. Such systems matter for advanced cooling, but solving their equations repeatedly is slow.
The team first solved the flow equations with a standard numerical solver and checked the mesh carefully. Those results trained a neural network, which then predicted velocity, temperature and disorder creation with very high accuracy. A stronger magnetic field slowed the flow markedly, as magnetic drag opposed motion, while added heat generation raised temperatures by about a fifth.
Catalog record
| CREATOR | Mamoon Aamir, Chemseddine Maatki, Aqsa Zafar Abbasi, Rajab Alsayegh, Karim Kriaa, Walid Hassen, Lioua Kolsi |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 143 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |