Perspectives on NOX Emissions and Impacts from Ammonia Combustion Processes

S Mashruk, H Shi, L Mazzotta, CE Ustun… - Energy & …, 2024 - ACS Publications
Climate change and global warming necessitate the shift toward low-emission, carbon-free
fuels. Although hydrogen boasts zero carbon content and high performance, its utilization is …

[HTML][HTML] Probabilistic machine learning framework for chemical source term integration with Gaussian Processes: H2/air auto-ignition case

CE Üstün, A Paykani - International Journal of Hydrogen Energy, 2024 - Elsevier
The integration of chemistry poses a major bottleneck in numerical combustion modelling,
as a significant amount of simulation time is consumed in the direct integration (DI) of …

[HTML][HTML] Topologically consistent regression modeling exemplified for laminar burning velocity of ammonia-hydrogen flames

H Du, T Wang, H Wei, GYC Maceda, BR Noack, L Zhou - Energy and AI, 2024 - Elsevier
Data-driven regression models are generally calibrated by minimizing a representation
error. However, optimizing the model accuracy may create nonphysical wiggles. In this …

Towards a machine learning model to predict the laminar flame speed of fuel blends and vented gases in lithium-ion batteries

S Ogunfuye, M Perhinschi, V Akkerman - Fuel, 2024 - Elsevier
A data-driven machine learning (ML) model for predicting laminar flame speeds (LFS) of
common fuel–air mixtures is developed, with a major advantage of being convenient and …

A Model for Predicting Carbon Emission Factors of Ch4-H2-Nh3 Mixed Fuel Combustion in Gas Turbine Power Plants

C Tao, L Zhang, Y Wang, R Sun - Available at SSRN 5020463 - papers.ssrn.com
This research presents a mathematical model for predicting the carbon emission factor (EF)
of a gas turbine system, aiming to assess the carbon dioxide emissions per kilowatt-hour of …