Numerical Analysis of the Injection Angle of Urea-Water Sprays for the Ammonia Generation in Realistic Test Conditions

2022-01-0584

03/29/2022

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
During the past decades, the Nitrogen Oxides (NOx) emission limitations have become stricter, promoting the development of after-treatment systems like Selective Catalytic Reduction (SCR) for emission reduction purposes. The Urea-Water Solution (UWS) spray characteristics can directly have an effect on the SCR efficiency. To understand the droplet breakup and mixing of the UWS with the surrounding air under different operating conditions, a computational campaign has been set up. The main objective of the present study is to recreate the spray injection process, as well as the chemical processes that the UWS spray undergoes, and to analyze the optimal injection angle to maximize the amount of ammonia generated during the injection process by means of Computational Fluid Dynamics (CFD). A Eulerian-Lagrangian framework has been employed to track the evolution of the injected droplets within a Reynolds-Averaged Navier-Stokes (RANS) turbulence formulation. Typical injection pressures have been tested and realistic exhaust velocities have been applied. The results obtained comprise from the amount of ammonia generated for the seven injection angles tested, to the rate of reaction of the UWS spray. Additionally, a regression analysis on the dataset has been performed to assess the influence of each one of the boundary conditions on the ammonia generation. The optimal injection angle resides close to 80o with respect to the direction of the incoming exhaust gases if compared to the original injection angle, which was set to 90o originally.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-01-0584
Pages
15
Citation
Payri, R., Marti-Aldaravi, P., Bracho, G., and Marco, J., "Numerical Analysis of the Injection Angle of Urea-Water Sprays for the Ammonia Generation in Realistic Test Conditions," SAE Technical Paper 2022-01-0584, 2022, https://doi.org/10.4271/2022-01-0584.
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-0584
Content Type
Technical Paper
Language
English