Experimental Study on Evaporation Characteristics of Ammonium Formate–Urea–Water Solution Droplet for Selective Catalytic Reduction Applications

2011 ◽  
Vol 50 (13) ◽  
pp. 8285-8294 ◽  
Author(s):  
Seung Yeol Lee ◽  
Seung Wook Baek
2018 ◽  
Vol 46 (10) ◽  
pp. 1231-1239 ◽  
Author(s):  
Shi-lin DONG ◽  
Ya-xin SU ◽  
Xin LIU ◽  
Qian-cheng LI ◽  
Min-hao YUAN ◽  
...  

2013 ◽  
Vol 66 (2) ◽  
pp. 153-158
Author(s):  
Claudine Miraval ◽  
Saghi Saedlou ◽  
Romain Evrard ◽  
Pierre-Olivier Santacreu ◽  
Johan Leseux

Stainless steel is largely used in the car exhaust market and will be applied now for truck and off-road vehicles. In that field of application, designs are more and more complex with the integration of a catalytic converter and particle filter, consequence of more and more severe diesel depollution regulations. In particular, due to the necessity of reducing NOx emission established by Euro 5 standard (2009), Euro 6 (2014) and American Tier 4 (2014), new equipment were developed for diesel vehicles (truck as well as car). The most promising technology is called Selective Catalytic Reduction (SCR) and takes advantage of the reduction feature of ammonia (NH3) on NOx. As NH3 cannot be stored directly within the vehicle for safety reasons (toxicity & flammability of ammonia) urea in water solution was selected to initiate the reaction by means of a spraying nozzle. To get a better understanding of the involved hot corrosion mechanisms and afterward to improve material selection, a dedicated laboratory test was developed at Isbergues Research Center. The simulated test consists of spraying urea solution on cyclic heated stainless steel in a range from 200ºC to 600ºC. We evidenced a nitriding mechanism due to the urea decomposition on the surface of stainless steel at high temperature, and also the very different behaviours between austenitic and ferritic grades. The last one, in particular K41X (1.4509-441) and K33X (1.4513-molybdenum stabilized ferritic) grades show the best performance in particular when compared to the standard 304 austenitic grade. The paper will review the test set-up, the result obtained and will discuss the stainless steel grade selection for the SCR application.


Author(s):  
Zhaoyu Luo ◽  
Parvez Sukheswalla ◽  
Scott A. Drennan ◽  
Mingjie Wang ◽  
P. K. Senecal

Environmental regulations have put stringent requirements on NOx emissions in the transportation industry, essentially requiring the use of exhaust after-treatment on diesel fueled light and heavy-duty vehicles. Urea-Water-Solution (UWS) based Selective Catalytic Reduction (SCR) for NOx is one the most widely adopted methods for achieving these NOx emissions requirements. Improved understanding and optimization of SCR after-treatment systems is therefore vital, and numerical investigations can be employed to facilitate this process. For this purpose, detailed and numerically accurate models are desired for in-cylinder combustion and exhaust after-treatment. The present paper reports on 3-D numerical modeling of the Urea-Water-Solution SCR system using Computational Fluid Dynamics (CFD). The entire process of Urea injection, evaporation, NH3 formation and NOx reduction is numerically investigated. The simulation makes use of a detailed kinetic surface chemistry mechanism to describe the catalytic reactions. A multi-component spray model is applied to account for the urea evaporation and decomposition process. The CFD approach also employs an automatic meshing technique using Adaptive Mesh Refinement (AMR) to refine the mesh in regions of high gradients. The detailed surface chemistry NOx reduction mechanism validated by Olsson et al. (2008) is applied in the SCR region. The simulations are run using both transient and steady-state CFD solvers. While transient simulations are necessary to reveal sufficient details to simulate catalytic oxidation during transient engine processes or under cyclic variations, the steady-state solver offers fast and accurate emission solutions. The simulation results are compared to available experimental data, and good agreement between experimental data and model results is observed.


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