(312f) A Parameterized Iron-Zeolite SCR Model Calibrated to Reactor Data | AIChE

(312f) A Parameterized Iron-Zeolite SCR Model Calibrated to Reactor Data

Authors 

DeLand, S. - Presenter, Michigan Technological University
Parker, G. - Presenter, Michigan Technological University
Johnson, J. - Presenter, Michigan Technological University


A numerical model was developed to capture the behavior of the SCR catalyst for varying inlet conditions.  The model form was developed based on analysis of reactor data, and simulated over a temperature range reflective of typical exhaust gas temperatures.  The experimental protocol was designed to capture the effects of different NH3/NOx ratios and different NOx compositions, as well as ammonia storage and oxidation.  Feedback from the modeling effort was used to modify portions of the protocol in order to further investigate key areas.  Two different types of storage sites were used to represent the adsorption and desorption of ammonia.  An adsorption equation that includes ammonia inhibition was used to capture the slow approach of the catalyst to steady state storage.  Two different states were used to represent the gas distribution in the catalyst: a bulk-gas concentration and a surface concentration.  Species move between the bulk-gas and surface states via mass transport.  Initially, the model used only the Standard (NH3-NO), Fast (NH3-NO-NO2), and Slow (NH3-NO2) reactions to capture the reduction of NOx by stored ammonia.  Based on experimental data, reactions were added to extend the model beyond the typical SCR reactions.  The single-channel, isothermal model was discretized axially to form a system of ordinary differential equations that could be numerically integrated.  An optimization routine was used to determine the reaction rate parameters that provided the best fit to the reactor data, and the resulting model is presented.  We discuss changes that were made to the original model form, which allowed the model to capture the dynamics seen in the experimental data.