With emission regulations becoming increasingly stringent, the integration of Diesel Exhaust Fluid (DEF) in aftertreatment systems has become essential for reducing nitrogen oxide (NOx) emissions in compliance with these evolving standards. DEF dosing is a very critical component in Selective Catalytic Reduction (SCR) systems, where it chemically reacts with NOx in the exhaust stream to form harmless nitrogen and water vapor, thus significantly reducing the environmental impact of diesel engines. However, the introduction of DEF presents a challenge of corrosion risk within the aftertreatment system components.
This study aims to predict the location of corrosion, and its risk associated with DEF usage in Diesel aftertreatment system, by employing a multi-faceted approach that includes physical testing and computational modelling. Specifically, the focus of this paper is on predicting corrosion locations from unsteady DEF spray analysis without modelling detailed corrosion chemistry mechanism using computational fluid dynamics (CFD). This unsteady DEF spray analysis focuses on characterizing the spray behavior, its interactions with the reactor walls, and identifying key factors in DEF spray dynamics that can predict potential corrosion locations within the decomposition reactor tube (DRT). The DRT is a critical component in the aftertreatment system, serving as the conduit through which DEF spray is injected and transported to the SCR section. The key factors for prediction of corrosion locations include temperature of solids, film velocity, DEF concentration and direct DEF spray impingement zones. The criteria of these factors are studied, and relationships are established among these factors to provide insight into potential corrosion risk locations in DRT. This paper also discusses the approaches to speed the simulation and reduce the turnaround time to help make the design-development decision faster.
The validation of simulation methodology through physical testing has shown a good correlation. This good agreement between simulation and experimental results underscores the effectiveness of simulation methodology in accurately identifying the potential corrosion locations.