Deep convolutional surrogates and freedom in thermal design
A deep learning approach is presented for heat transfer and pressure drop prediction of complex fin geometries generated using composite Bézier curves. Thermal design process includes iterative high fidelity simulation which is complex, computationally expensive, and time-consuming. With the advance...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-07-01
|
Series: | Energy and AI |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546823000204 |