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Partially Premixed Combustion in a Co-axial Combustor

Simulation of Partially Premixed Combustion in a Co-axial Combustor

Introduction

The purpose of this tutorial is to provide guidelines and recommendations for setting up and solving a reacting flow using the partially premixed combustion model. This tutorial demonstrates how to do the following:

  • Create a probability density function (PDF) file for a combustion system.
  • Define ANSYS Fluent inputs for PDF chemistry modeling.
  • Use the partially premixed Zimont turbulent flame speed model to simulate the combustion system.
  • Solve the case with appropriate solver settings.
  • Postprocess the results to investigate the premixed and non-premixed properties.

Problem Description

The coaxial combustor considered is shown in the following figure. A swirler at the center of the combustor introduces the lean methane/air mixture (equivalence ratio=0.8) of temperature 300 K with an axial velocity of 50 m/s and swirl velocity of 30 m/s. Pure air at an axial velocity of 10 m/s and temperature 650 K is introduced from the outer tube to stabilize the flame. The major species involved in the combustion process are CH4, O2, CO2, CO, H2O, and N2.

The key to the premixed combustion model is the prediction of the turbulent flame speed, the turbulent flame speed normal to the mean surface of the flame. The turbulent flame speed is influenced by the following:

  • Laminar flame speed, which is, in turn, determined by the fuel concentration, temperature, and molecular diffusion properties, as well as the detailed chemical kinetics
  • Flame front wrinkling and stretching by large eddies, and flame thickening by small eddies

Numerous turbulent flame speed models have been derived. You will be using the Zimont Turbulent Flame Speed Model (for details refer to section 9.4.1 of the ANSYS Fluent 14.5 Theory Guide).

Result

The partially premixed model in ANSYS Fluent can be used to simulate a combustion system, where the combustion process is neither purely premixed nor purely non-premixed. Both premixed and non-premixed properties can be investigated using the postprocessing results.

 

Summary

This tutorial demonstrated the application of the partially premixed model, based on both non-premixed (mixture-fraction based) and premixed (mean progress variable based) models.

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