Overview

Selective Catalytic Reduction (SCR) technology has been used extensively to reduce nitrogen oxide emissions in commercial vehicle boilers, waste incinerators and diesel engines, including light and heavy commercial vehicles and marine applications. In the case of mobile applications, urea is the preferred source of ammonia for safety reasons and is used in the form of a eutectic urea-water solution (UWS), also known as AdBlue. Typically, UWS is injected into the hot exhaust gas stream upstream of the monolithic catalytic converter, where the dissolved urea is converted into ammonia.

The challenge here is to provide sufficient residence time and turbulence so that there is a sufficient quantity and homogeneous distribution of ammonia across the front of the catalyst while meeting the size and pressure drop limitations of the exhaust pipe design within the tight emission limits. Nevertheless, complete spray evaporation and urea degradation remain a challenge under these constraints, particularly due to transient engine load conditions that can cause droplets to impinge on the mixer blades and exhaust pipe walls, forming a liquid film. Given sufficient residence time, further evaporation of the liquid film leads to the formation of urea crystals and/or solid by-products. Consequently, a proper understanding of UWS atomization and its evaporation is key to the successful implementation of SCR technology.

At ITS, we have developed a proprietary methodology to characterize the evaporating UWS sprays under realistic operating conditions. The measurement technique combines shadowgraphy, microscopic imaging and laser diagnostics, allowing us to track the diameters and velocities of the individual droplets.

Another objective is to investigate the primary decay of the UWS at the trailing edge of the mixer blades and its relationship to deposit formation. For the numerical simulation of the transient two-phase flow, the method of Smoothed Particle Hydrodynamics (SPH) is used, where the dynamics of deposit formation is mimicked by a self-developed stochastic deposit model.