Deep reinforcement learning-CFD framework for optimising NOx emissions in combustion systems
This paper presents a novel Deep Reinforcement Learning (DRL) framework integrated with Computational Fluid Dynamics (CFD) simulations to optimise NOx emissions in natural gas burners. Unlike conventional static models, the proposed DRL-CFD framework employs a multi-layered neural network architectu...
Gorde:
| Egile Nagusiak: | , , , , |
|---|---|
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Taylor & Francis Group
2026-12-01
|
| Saila: | Engineering Applications of Computational Fluid Mechanics |
| Gaiak: | |
| Sarrera elektronikoa: | https://www.tandfonline.com/doi/10.1080/19942060.2026.2632237 |
| Etiketak: |
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
|