Python-based deep learning for optimizing thermal performance of Prandtl-Eyring hybrid nanofluids in solar systems
Improved heat transfer efficiency is greatly needed for the advancement of sustainable solar energy systems. Hybrid nanofluids could present strong options for maximizing thermal performance due to improved thermophysical properties. This study presents a Python-based hybrid framework integrating th...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25009773 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|