Levenberg–marquardt based ANN solution for MHD nanofluid flow and heat transportation over a thin needle with thermophoresis effects
Haider Ali, Aaqib Majeed, Taoufik Saidani, Parvez Ali · 2026
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Description
Haider Ali, Aaqib Majeed, Taoufik Saidani, and Parvez Ali model heat and flow of a nanofluid past a thin needle with a neural network, in work from twenty twenty-six. The fluid holds tiny particles and flows under a magnetic field. Such flows matter in cooling and in heat transfer design.
The team first solved the flow equations with a classic numeric method. They then trained a network with a fast learning rule to match those answers. A stronger magnetic field slowed the fluid and raised its heat, while some factors cooled it or thinned its mix. The network output sat very close to the numeric output. The authors present the network as a sound, fast tool for such flow problems.
Catalog record
| CREATOR | Haider Ali, Aaqib Majeed, Taoufik Saidani, Parvez Ali |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 42 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |