Learning reduced-order models for dynamic CO2 methanation using operator inference
The efficient modeling of dynamic systems in process engineering is becoming increasingly important in the modern industrial landscape. Our study addresses this challenge by employing reduced-order modeling and model order reduction techniques, with a focus on the non-intrusive operator inference me...
Saved in:
Published in | Computer Aided Chemical Engineering Vol. 53; pp. 3319 - 3324 |
---|---|
Main Authors | , , , , , |
Format | Book Chapter |
Language | English |
Published |
2024
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Be the first to leave a comment!