A coupled Lagrangian Monte Carlo Probability Density Function (PDF)–Eulerian Computational Fluid Dynamics (CFD) technique is presented for calculating steady three–dimensional (3–D) turbulent reacting flow in a gas turbine combustor. PDF transport methods model turbulence–combustion interactions more accurately than conventional turbulence models with an assumed shape PDF. The PDF transport equation was solved using a Lagrangian particle tracking Monte Carlo (MC) method. The PDF modeled was over composition only. This MC module has been coupled with CONCERT, which is a fully elliptic 3–D body–fitted CFD code based on pressure correction techniques. In an earlier paper [Tolpadi et al, 1995], this computational approach was described but only fast chemistry calculations were presented in a typical aircraft engine combustor. In the present paper, reduced chemistry schemes were incorporated into the MC module that enabled the modeling of finite rate effects in gas turbine flames and therefore the prediction of CO and NOx emissions. With the inclusion of these finite rate effects, the gas temperatures obtained were also more realistic. Initially, a two scalar scheme was implemented that allowed validation against Raman data taken in a recirculating bluff body stabilized CO/H2/N2–air flame. Good agreement of the temperature and major species were obtained. Next, finite rate computations were performed in a single annular aircraft engine combustor by incorporating a simple three scalar reduced chemistry scheme for Jet A fuel. This three scalar scheme was an extension of the two scalar scheme for CO/H2/N2 fuel. The solutions obtained using the present approach were compared with those obtained using the fast chemistry PDF transport approach [Tolpadi et al, 1995] as well as the presumed shape PDF method. The calculated exhaust gas temperatures using the finite rate model showed the best agreement with measurements made by a thermocouple rake. In addition, the CO and NOx emission indices were also computed and compared with corresponding data.

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