Mixing and evaporation analysis of a high-pressure SCR system using a hybrid LES-RANS approach

Ossi Tapani Kaario*, Ville Vuorinen, Lei Zhu, Martti Larmi, Ronghou Liu

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

28 Citations (Scopus)
357 Downloads (Pure)

Abstract

A hybrid Large Eddy Simulation (LES) - Reynolds-Averaged Navier-Stokes (RANS) method (HLR) has been applied to simulate an engine related selective catalytic reduction (SCR) system. Typical SCR systems utilize low pressure urea injection together with a mixer for vapor field homogenization. Simultaneously, it is also desirable to reduce spray-wall interaction to avoid urea crystallization. The present study considers an SCR system where a high pressure (150 bar) urea spray is injected towards hot exhaust gases in exhaust pipe. The system has been shown to work well in a previous experimental study but detailed characterization of the system is missing. The novelty of the present study rises from: 1) the creation of phase diagrams with single droplet simulations that predict the optimum operation regions for the SCR system, 2) validation of the HLR method in a high Reynolds number (Re=49,900) compressible pipe flow, 3) the use of HLR simulations in an engine SCR system for the first time, and 4) the detailed characterization of the present SCR system. As a result of the study, new non-dimensional timescale ratios are proposed to link the droplet size and liquid injection velocity to the exhaust pipe dimensions in future SCR systems.

Original languageEnglish
Pages (from-to)827-841
Number of pages15
JournalEnergy
Volume120
Early online date12 Feb 2016
DOIs
Publication statusPublished - Feb 2017
MoE publication typeA1 Journal article-refereed

Keywords

  • Computational Fluid Dynamics
  • Hybrid LES-RANS
  • NO reduction
  • SCR spray design
  • Selective Catalytic Reduction (SCR)
  • Urea mixing

Fingerprint

Dive into the research topics of 'Mixing and evaporation analysis of a high-pressure SCR system using a hybrid LES-RANS approach'. Together they form a unique fingerprint.

Cite this