Ferrofluid bend channel flows for multi-parameter tunable heat transfer enhancement Part 2 Deep Learning and Neural Network Modeling
Abstract
This work is the second in a series focused on ferrofluid bend channel flows. Here, ferrofluid flows in bend channels are modeled using machine learning methods, based on data generated from the CFD simulation discussed in the first work in this series. Predicting convective heat transfer in ferrofluid flows influenced by magnetic fields is key to advancing thermal management in microscale and energy-intensive systems.
Fields of Study & Subjects
Nanofluid Flow and Heat Transfer
Heat Transfer and Optimization
Heat Transfer and Numerical Methods
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 9 February 2026
- Language
- EN
- Document type
- Preprint