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Simulation of a Flow in a Gas Turbine Exhaust Diffuser with Advanced Turbulence Models

In: High Performance Computing in Science and Engineering ‘14

Author

Listed:
  • S. Brouwer (née Volkmer)

    (University of Stuttgart, Institute of Thermal Turbomachinery and Machinery Laboratory)

  • D. M. Vogt

    (University of Stuttgart, Institute of Thermal Turbomachinery and Machinery Laboratory)

Abstract

The prediction of the flow in a gas turbine exhaust diffuser of a combined cycle power plant is particularly difficult as maximum performance is obtained with highly loaded diffusers, which operate close to boundary layer separation. Computational fluid dynamics (CFD) simulations then need to cope with complex phenomena such as smooth wall separation, recirculation, reattachment and free shear layer mixing. Recent studies based on the Reynolds-Averaged-Navier-Stokes (RANS) approach demonstrate the challenge for two-equation turbulence models to predict separation and mixing of the flow correctly and identify that more accurate methods are needed. In the present study the flow in an exhaust diffuser (Reynolds number 1. 5 × 106 with twice the channel height and the mean inlet velocity resulting in an inlet Mach number 0.6) is examined with unsteady RANS (URANS) simulations with the hybrid Scale Adaptive Simulation (SAS) model. The SAS model switches from URANS to a Large Eddy Simulation (LES)-like mode in unsteady flow regions to resolve various scales of detached eddies. This is achieved by decreasing the turbulent viscosity, which is generally over-predicted by common two-equation models leading to a highly dissipative behavior in terms of resolving unsteady fluctuations unless the flow instabilities are dominant. For validation, experimental data is obtained from a test rig at the Institute of Thermal Turbomachinery of the University of Stuttgart and Machinery Laboratory (ITSM).

Suggested Citation

  • S. Brouwer (née Volkmer) & D. M. Vogt, 2015. "Simulation of a Flow in a Gas Turbine Exhaust Diffuser with Advanced Turbulence Models," Springer Books, in: Wolfgang E. Nagel & Dietmar H. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering ‘14, edition 127, pages 463-477, Springer.
  • Handle: RePEc:spr:sprchp:978-3-319-10810-0_31
    DOI: 10.1007/978-3-319-10810-0_31
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