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AUSM scheme: its application to a realistic combustor configuration, the Energy Efficient Engine

  • K. MikiEmail author
  • J. Moder
  • M.-S. Liou
Original Article
  • 36 Downloads

Abstract

Highlights of work inspired by Liou and performed in the last few years with the ultimate goal of simulating combustor–turbine interactions are presented. First, we have updated the Open National Combustion Code (OpenNCC) by implementing the advection upstream splitting method (AUSM) and the extended version of the AUSM-family scheme (AUSM\(^+\)-up) and then performed a series of verification tests. The AUSM\(^+\)-up scheme and the standard Jameson–Schmidt–Turkel scheme are compared in terms of accuracy and convergence. Next, the second-order AUSM\(^+\)-up scheme is applied to model unsteady flow fields inside a combustor sector from the Energy Efficient Engine (\({\hbox {E}}^3\)) program, in conjunction with a sensitivity analysis of turbulent combustion models. Three different turbulent combustion models are considered: the eddy break-up model, the linear eddy model, and the probability density function model, as well as the laminar finite-rate chemistry model. A comprehensive comparison of the flow fields and the flame structures is provided. Our main interest here is not to select the best model out of four different models with lack of data under the exact same conditions, but to understand how different turbulent combustion models impact thermal variation along the surface of first-stage vanes (i.e., hot streaks). Considering that these models are often used in combustor/turbine communities, the intent of this study is to provide some guidelines on numerical modeling of combustor–turbine interactions and, thus, help improve future designs of the combustor and high-pressure turbine.

Keywords

Advection upstream splitting method (AUSM) Combustor–turbine interaction Hot streaks 

Notes

Acknowledgements

This work was sponsored by the National Aeronautics and Space Administration’s Transformational Tools and Technologies project. The authors would like to thank Christopher Heath, Thomas Wey, Tsan-Hsing Shih, Clarence Chang, Manthena S. Raju, Paul Giel, and Kumud Ajmani for their assistance in preparing and running the simulations. The simulations were conducted on the NASA Advanced Supercomputing (NAS) Pleiades computer cluster. Grid generation was conducted with Cubit (provided by the Sandia National Laboratories), and flow visualization was conducted with Visit (provided by the Lawrence Livermore National Laboratory).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.NASA Glenn Research CenterClevelandUSA

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