Bayesian Analysis of Combustion Kinetic Models for Ammonia-Hydrogen Fuel Blends Using Artificial Neural Networks
Uncertainty quantification (UQ) plays a crucial role in predictive modeling in combustion chemistry, as it improves the accuracy of predictions and the reliability. To accurately predict ignition delay times and nitrogen oxides (NOx) emissions of ammonia (NH3) and hydrogen (H2) fuel blends, minimizi...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
|
| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2025/08/epjconf_cim2025_05002.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|