Table of Contents
Fetching ...

Flamelet Model with Epsilon Tracking in a Turbine Stator

Sylvain L. Walsh, Yalu Zhu, Feng Liu, William A. Sirignano

TL;DR

This work investigates combustion in a turbine stator using a Reynolds-averaged framework coupled to an epsilon-based flamelet model to link resolved turbulence with subgrid flamelet dynamics. The epsilon-based approach uses flamelet libraries generated for CH4 and JP-5/vitiated air, with JP-5 enabled by the HyChem A3 mechanism, enabling finite-rate chemistry in a turbine-relevant geometry. Compared with a traditional one-step kinetics baseline for methane, the flamelet model predicts lower peak temperatures due to dissociation and a flame stand-off that broadens reaction zones, reducing net energy addition by about 50%. For JP-5, endothermic pyrolysis and exothermic oxidation produce vertically displaced reaction zones and higher near-wall temperatures, with shorter stand-off and larger resolved reaction regions, yielding greater but still reduced energy addition relative to OSK methane. The results highlight the importance of strain-rate based quenching and flammability limits in turbine-burner designs and demonstrate the potential for JP-5 operation within this flamelet framework, with implications for multi-stage combustion strategies.

Abstract

Combustion within a two-dimensional turbine stator passage is numerically investigated in the context of the turbine-burner concept using a Reynolds-Averaged Navier-Stokes framework coupled with a novel flamelet model. The formulation links resolved-scale turbulence quantities with subgrid flamelet dynamics through the local turbulent kinetic energy dissipation rate, $ε$, which determines the flamelet inflow strain rate. For the first time, combustion of JP-5 is considered in a turbine stator passage as a practical fuel. This is achieved by solving transport equations for 14 major species on the resolved scale, while chemical source terms are obtained from precomputed flamelet libraries based on the HyChem A3 mechanism comprising 119 species and 841 elementary reactions. Model performance is assessed against methane combustion using both a one-step kinetics model and an $ε$-based flamelet formulation employing a 13-species skeletal mechanism. The $ε$-based formulation predicts lower peak flame temperatures due to dissociation effects and approximately 50\% lower net chemical energy addition per unit mass compared with the one-step model, as a result of flame stand-off and downstream strain-rate-induced quenching. For JP-5, the simulations capture combined endothermic pyrolysis and exothermic oxidation processes, leading to vertically displaced reaction zones, increased near-wall temperatures, and larger resolved-scale reaction regions due to the higher flamelet flammability limit relative to methane.

Flamelet Model with Epsilon Tracking in a Turbine Stator

TL;DR

This work investigates combustion in a turbine stator using a Reynolds-averaged framework coupled to an epsilon-based flamelet model to link resolved turbulence with subgrid flamelet dynamics. The epsilon-based approach uses flamelet libraries generated for CH4 and JP-5/vitiated air, with JP-5 enabled by the HyChem A3 mechanism, enabling finite-rate chemistry in a turbine-relevant geometry. Compared with a traditional one-step kinetics baseline for methane, the flamelet model predicts lower peak temperatures due to dissociation and a flame stand-off that broadens reaction zones, reducing net energy addition by about 50%. For JP-5, endothermic pyrolysis and exothermic oxidation produce vertically displaced reaction zones and higher near-wall temperatures, with shorter stand-off and larger resolved reaction regions, yielding greater but still reduced energy addition relative to OSK methane. The results highlight the importance of strain-rate based quenching and flammability limits in turbine-burner designs and demonstrate the potential for JP-5 operation within this flamelet framework, with implications for multi-stage combustion strategies.

Abstract

Combustion within a two-dimensional turbine stator passage is numerically investigated in the context of the turbine-burner concept using a Reynolds-Averaged Navier-Stokes framework coupled with a novel flamelet model. The formulation links resolved-scale turbulence quantities with subgrid flamelet dynamics through the local turbulent kinetic energy dissipation rate, , which determines the flamelet inflow strain rate. For the first time, combustion of JP-5 is considered in a turbine stator passage as a practical fuel. This is achieved by solving transport equations for 14 major species on the resolved scale, while chemical source terms are obtained from precomputed flamelet libraries based on the HyChem A3 mechanism comprising 119 species and 841 elementary reactions. Model performance is assessed against methane combustion using both a one-step kinetics model and an -based flamelet formulation employing a 13-species skeletal mechanism. The -based formulation predicts lower peak flame temperatures due to dissociation effects and approximately 50\% lower net chemical energy addition per unit mass compared with the one-step model, as a result of flame stand-off and downstream strain-rate-induced quenching. For JP-5, the simulations capture combined endothermic pyrolysis and exothermic oxidation processes, leading to vertically displaced reaction zones, increased near-wall temperatures, and larger resolved-scale reaction regions due to the higher flamelet flammability limit relative to methane.

Paper Structure

This paper contains 17 sections, 29 equations, 11 figures, 1 table.

Figures (11)

  • Figure 1: Maximum flamelet temperatures in terms of $\mathbf{S^*}$.
  • Figure 2: Tabulated quantities for the JP-5 case for a $\mathbf{\widetilde{Z"^2}_{\mathrm{norm}}=10^{-8}}$ and $\mathbf{\bar{p}=30}$ bar.
  • Figure 3: Flow configuration and grid.
  • Figure 4: $\mathbf{\widetilde{T}}$ fields for the $\boldsymbol{{\mathrm{CH_4}}}$ configuration.
  • Figure 5: $\boldsymbol{\widetilde{\dot{Q}}}$ fields for the $\boldsymbol{{\mathrm{CH_4}}}$ configuration.
  • ...and 6 more figures