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Optimal design of selective catalyst reduction denitrification system using numerical simulation.

Xiang Gao1, Ben Wang1, Xudong Yuan2

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Improving selective catalytic reduction (SCR) systems requires better ammonia (NH3) and nitrogen oxide (NOx) mixing. This study uses computational fluid dynamics to optimize SCR components for enhanced flow uniformity and performance in heat recovery steam generators.

Keywords:
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Area of Science:

  • Chemical Engineering
  • Environmental Engineering
  • Fluid Dynamics

Background:

  • Selective Catalytic Reduction (SCR) system performance relies on uniform flow and effective NH3-NOx mixing.
  • Parameters like gate leafs, hybrid grids, straighteners, and ammonia injection methods influence SCR efficiency.
  • Optimizing these parameters is crucial for reducing NOx emissions in industrial applications.

Purpose of the Study:

  • To investigate the impact of various components on flow uniformity and NH3-NOx mixing in SCR systems.
  • To optimize the design of a hybrid grid and ammonia injection method for enhanced SCR performance.
  • To validate simulation results with experimental data.

Main Methods:

  • Computational Fluid Dynamics (CFD) simulations were employed to analyze flow dynamics.
  • Evaluated the performance of gate leafs and a novel hybrid grid design.
  • Optimized the hybrid grid structure and ammonia injection strategy.

Main Results:

  • Gate leafs significantly improved velocity distribution uniformity (RSD from 19.6% to 5.4%).
  • The hybrid grid enhanced concentration distribution uniformity (RSD from 70% to 12.7%).
  • A 30° crossed angle for the hybrid grid optimized NH3-NOx mixing with minimal pressure drop.

Conclusions:

  • CFD is a reliable tool for optimizing SCR system components.
  • The optimized hybrid grid and injection method improve NH3-NOx mixing and flow uniformity.
  • Findings contribute to more efficient NOx reduction technologies in heat recovery steam generators.