Reactor modelling assessment for urea-SNCR applications

Abstract

Purpose

This work aims to investigate the effects of neglecting, modelling or partly resolving turbulent fluctuations of velocity, temperature and concentrations on the predicted turbulence-chemistry interaction in urea-selective non-catalytic reduction (SNCR) systems.

Design/methodology/approach

Numerical predictions of the NO conversion efficiency in an industrial urea-SNCR system are compared to experimental data. Reactor models of varying complexity are assessed, ranging from one-dimensional ideal reactor models to state-of-the-art computational fluid dynamics simulations based on the detached-eddy simulation (DES) approach. The models use the same reaction mechanism but differ in the degree to which they resolve the turbulent fluctuations of the gas phase. A methodology for handling of unknown experimental data with regard to providing adequate boundary conditions is also proposed.

Findings

One-dimensional reactor models may be useful for a first quick assessment of urea-SNCR system performance. It is critical to account for heat losses, if present, due to the significant sensitivity of the overall process to temperature. The most comprehensive DES setup evaluated is associated with approximately two orders of magnitude higher computational cost than the conventional Reynolds-averaged Navier–Stokes-based simulations. For studies that require a large number of simulations (e.g. optimizations or handling of incomplete experimental data), the less costly approaches may be favored with a tolerable loss of accuracy.

Originality/value

Novel numerical and experimental results are presented to elucidate the role of turbulent fluctuations on the performance of a complex, turbulent, reacting multiphase flow.

Citation

Finnerman, O., Razmjoo, N., Guo, N., Strand, M. and Ström, H. (2017), "Reactor modelling assessment for urea-SNCR applications", International Journal of Numerical Methods for Heat & Fluid Flow, Vol. 27 No. 7, pp. 1395-1411. https://doi.org/10.1108/HFF-03-2016-0135