Highly accurate heat release rate marker detection in NH3–CH4 cofiring through machine learning and domain knowledge-based selection integration-Reference-Cited by-同舟云学术

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Highly accurate heat release rate marker detection in NH3–CH4 cofiring through machine learning and domain knowledge-based selection integration

Published:2024-08 Issue: Volume:80 Page:1223-1233
ISSN:0360-3199
Container-title:International Journal of Hydrogen Energy
language:en
Short-container-title:International Journal of Hydrogen Energy

Author:

Ghadi Ariyan Zare,Syauqi Ahmad,Gu Boram^ORCID,Lim Hankwon^ORCID

Funder

KETEP

Publisher

Elsevier BV

Reference72 articles.

1. Net zero by 2050: a roadmap for the global energy sector;Bouckaert,2021

2. Experimental and numerical study of the laminar burning velocity of CH4–NH3–air premixed flames;Okafor;Combust Flame,2018

3. Towards the development of an efficient low-NOx ammonia combustor for a micro gas turbine;Okafor;Proc Combust Inst,2019

4. Measurement and modelling of the laminar burning velocity of methane-ammonia-air flames at high pressures using a reduced reaction mechanism;Okafor;Combust Flame,2019

5. Oxidizer effects on ammonia combustion using a generated non-premixed burner;Ilbas;Int J Hydrogen Energy,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Numerical investigation of ammonia-propane cofiring characteristics utilizing air and hydrogen peroxide as oxidizers;Journal of the Energy Institute;2024-12

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