Diesel Exhaust Fluid (DEF) Associated Corrosion Risk Prediction for Aftertreatment System

Topic Name: Diesel Exhaust Fluid (DEF) Associated Corrosion Risk Prediction for Aftertreatment System. Authors: Tushar S Udhane, Enoch Nanduru, Michael J Warwick, Donald E Willey, Tanishq Parikh, Nikhil Giri. Abstract: 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 critical component in Selective Catalytic Reduction (SCR) systems, where it chemically reacts with NOx emissions 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 risks associated with DEF usage in Diesel aftertreatment system by employing a multi-faceted approach that includes physical testing and computational modelling. Specifically, we focus on predicting corrosion locations from unsteady DEF spray analysis without modelling detail corrosion chemistry mechanism using computational fluid dynamics (CFD). This unsteady DEF spray analysis involves understanding the spray behavior, its wall interactions and finding the factors which provide the idea on possible corrosion locations in decomposition reactor tube (DRT) for aftertreatment system. These factors include temperature fluctuations, velocity, DEF concentration and DEF spray impingement zone. The criteria and the ranges of these factors are studied, and relationship is established among these factors to provide insight into potential corrosion hotspots in DRT. This paper also discusses the approaches to speed the simulation turnaround time to help making 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 potential corrosion locations.