Towards Effective SCR System Optimization: A 3D-CFD and Experimental Study Enabling Faster Deposit Formation Risk Assessment

Selective Catalytic Reduction (SCR) is a key technology for reducing nitrogen oxides (NOx) emissions in diesel engines. In this process, a urea-water solution (UWS) is injected upstream of the catalyst to generate ammonia, which reacts with NOx to form nitrogen. However, liquid urea can adhere to system walls, undergoing secondary reactions that lead to the formation of solid deposits. These deposits must be minimized to ensure the long-term durability and efficiency of the system. Computer-Aided Engineering (CAE) simulations play a crucial role in optimizing SCR performance during the design phase. However, accurately predicting deposit formation requires detailed chemical modelling, which is computationally expensive and introduces uncertainties related to reaction mechanisms definition. To address this challenge, simplified CAE approaches are needed to assess deposit formation risks while maintaining computational efficiency. This study presents an improved Deposit Risk Index (DRI) integrated into a 3D-CFD model of an off-road vehicle equipped with an SCR exhaust system. The enhanced DRI leverages film and near-wall gas properties to estimate deposit formation risks up to 350°C, eliminating the need for detailed chemical reactions and minimizing computational effort. Additionally, an updated Bai-Gosman droplet impingement model is used to improve liquid film formation prediction across a wider temperature range. To further enhance efficiency, a thermal transient acceleration technique was implemented, enabling the prediction of realistic solid temperatures within a few seconds of simulation. The proposed methodology was validated through experimental testing at challenging part-load operating conditions. Optical imaging of deposits was used to calibrate the DRI function and validate the 3D-CFD model. Simulation results demonstrated good agreement with experimental data, accurately capturing deposit locations and trends across various engine operating conditions. The proposed approach provides valuable insights for optimizing SCR system design and mitigating deposit-related issues while significantly reducing simulation time.