Evaporation and clustering of ammonia droplets in a hot environment

Lorenzo Angelilli, Francisco Hernandez Perez, Hong G. Im, Pietro P. Ciottoli, Mauro Valorani

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Recent developments in the transition to zero-carbon fuels show that ammonia is a valid candidate for combustion. However, liquid ammonia combustion is difficult to stabilize due to a large latent heat of evaporation, which generates a strong cooling effect that adversely affects the flame stabilization and combustion efficiency. In addition, the slow burning rate of ammonia enhances the undesired production of NOx and N2O. To increase the flame speed, ammonia must be blended with a gaseous fuel having a high burning rate. In this context, a deeper understanding of the droplet dynamics is required to optimize the combustor design. To provide reliable physical insights into diluted ammonia sprays blended with gaseous methane, direct numerical simulations are employed. Three numerical experiments were performed with cold, standard, and hot ambient in nonreactive conditions. The droplet radius and velocity distribution, as well as the mass and heat coupling source terms are compared to study the effects on the evaporation. Since the cooling effect is stronger than the heat convection between the droplet and the environment in each case, ammonia droplets do not experience boiling. On the other hand, the entrainment of dry air into the ammonia-methane mixture moves the saturation level beyond 100% and droplets condense. The aforementioned phenomena are found to strongly affect the droplet evolution. Finally, a three-dimensional Voronoi analysis is performed to characterize the dispersive or clustering behavior of droplets by means of the definition of a clustering index.
Original languageEnglish (US)
JournalPhysical Review Fluids
Volume7
Issue number11
DOIs
StatePublished - Nov 9 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-11-14
Acknowledgements: The authors acknowledge the support of the Italian Ministry of University and Research (MIUR) and King Abdullah University of Science and Technology (KAUST). Computational resources were provided by the KAUST Supercomputing Laboratory (KSL).

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