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Research Papers: Gas Turbines: Turbomachinery

Computational Fluid Dynamic Simulation of a Supercritical CO2 Compressor Performance Map

[+] Author and Article Information
Enrico Rinaldi

Process and Energy Department,
Delft University of Technology,
Leeghwaterstraat 39,
Delft 2628 CB, The Netherlands
e-mail: e.rinaldi@tudelft.nl

Rene Pecnik

Assistant Professor
Process and Energy Department,
Delft University of Technology,
Leeghwaterstraat 39,
Delft 2628 CB, The Netherlands
e-mail: r.pecnik@tudelft.nl

Piero Colonna

Professor
Aerodynamics, Wind Energy,
Flight Performance and Propulsion Department,
Delft University of Technology,
Kluyverweg 1,
Delft 2629 HS, The Netherlands
e-mail: p.colonna@tudelft.nl

1Corresponding author.

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received October 6, 2014; final manuscript received October 22, 2014; published online December 17, 2014. Editor: David Wisler.

J. Eng. Gas Turbines Power 137(7), 072602 (Jul 01, 2015) (7 pages) Paper No: GTP-14-1571; doi: 10.1115/1.4029121 History: Received October 06, 2014; Revised October 22, 2014; Online December 17, 2014

The performance map of a radial compressor operating with supercritical CO2 is computed by means of three-dimensional steady state Reynolds-averaged Navier–Stokes simulations. The geometry investigated is part of a 250 kW prototype which was tested at Sandia National Laboratories (SNL). An in-house fluid dynamic solver is coupled with a lookup table algorithm to evaluate the fluid properties. Tables are generated using a multiparameter equation of state, which ensures high accuracy in the fluid characterization. The compressor map is calculated considering three different rotational speeds (45 krpm, 50 krpm, and 55 krpm). For each speed-line, several mass flow rates are simulated. Numerical results are compared to experimental data from SNL to prove the potential of the methodology.

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References

Figures

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Fig. 1

Impeller and diffuser geometry [11]

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Fig. 2

Three-dimensional view of the computational mesh used to model the rotor and the diffuser vanes. The grid counts approximately 8 × 105 cells, which are clustered at the walls to ensure y+≈ 1. Hexahedral cells were used for the blades boundary layers and at the inlet of the rotor, while wedge cells were placed elsewhere. Detailed views are shown for the surface mesh of the rotor main blade, diffuser wedge, and the interface between rotor and diffuser.

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Fig. 3

Average inlet and outlet states. Symbols correspond to 45 krpm (squares), 50 krpm (diamonds), and 55 krpm (triangles).

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Fig. 4

Compressor performance map

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Fig. 5

Contours of pressure at 50% of the span and 55 krpm

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Fig. 6

Main blade leading edge: control volumes where the thermodynamic state is in the VLE region

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Fig. 7

Main and splitter blade trailing edge: control volumes where the thermodynamic state is in the VLE region

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