RANS Capabilities for Transonic Axial Compressor: A Perspective From GPPS Computational Fluid Dynamics Workshop

Abstract Reynolds-averaged Navier–Stokes (RANS) simulations currently serve as the prevailing industrial method for simulating axial compressor flows, and this status is expected to persist in the foreseeable future. To evaluate the capabilities of contemporary RANS solvers for compressors, this article presents a statistical analysis of RANS simulation results submitted to the first and the second Global Power and Propulsion Society (GPPS) computational fluid dynamics (CFD) workshops, where blind tests on the TUDa-GLR-OpenStage transonic axial compressor were performed. The workshops were held online in December 2021 and in a hybrid format at Chania, Greece, in September 2022, which are the first primary turbomachinery CFD workshops following the 1994 International Gas Turbine Institute (IGTI) CFD blind test event on NASA Rotor 37. A total of 35 submissions were received from 12 distinct RANS solvers, contributed by 14 participants affiliated with 11 organizations across 5 countries. Participants include academic researchers, engineers from the turbomachinery industry, and developers of commercial CFD solvers. First, the grid convergence behavior exhibited by various solvers employing different turbulence models is examined. Afterward, the prediction accuracy of the ensemble of the simulation results is evaluated, and the representative simulation results are compared and analyzed in detail. The key factors that improve the prediction accuracy are identified. These results foster improved usage and further development of turbomachinery RANS solvers.

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Publication Details

Journal
Journal of Turbomachinery
Published
2024-09-03
DOI
https://doi.org/10.1115/1.4066431
Citations
9
Primary Topic
Turbomachinery Performance and Optimization
Type
article
Field-Weighted Citation Impact
11.69

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article

RANS Capabilities for Transonic Axial Compressor: A Perspective From GPPS Computational Fluid Dynamics Workshop

Fabian Klausmann, Xiao He
9 citations
Journal of Turbomachinery
Turbomachinery Performance and Optimization
11.69
article

RANS Capabilities for Transonic Axial Compressor: A Perspective From GPPS Computational Fluid Dynamics Workshop

Fabian Klausmann, Xiao He
article en
9 citations

Abstract

Abstract Reynolds-averaged Navier–Stokes (RANS) simulations currently serve as the prevailing industrial method for simulating axial compressor flows, and this status is expected to persist in the foreseeable future. To evaluate the capabilities of contemporary RANS solvers for compressors, this article presents a statistical analysis of RANS simulation results submitted to the first and the second Global Power and Propulsion Society (GPPS) computational fluid dynamics (CFD) workshops, where blind tests on the TUDa-GLR-OpenStage transonic axial compressor were performed. The workshops were held online in December 2021 and in a hybrid format at Chania, Greece, in September 2022, which are the first primary turbomachinery CFD workshops following the 1994 International Gas Turbine Institute (IGTI) CFD blind test event on NASA Rotor 37. A total of 35 submissions were received from 12 distinct RANS solvers, contributed by 14 participants affiliated with 11 organizations across 5 countries. Participants include academic researchers, engineers from the turbomachinery industry, and developers of commercial CFD solvers. First, the grid convergence behavior exhibited by various solvers employing different turbulence models is examined. Afterward, the prediction accuracy of the ensemble of the simulation results is evaluated, and the representative simulation results are compared and analyzed in detail. The key factors that improve the prediction accuracy are identified. These results foster improved usage and further development of turbomachinery RANS solvers.

Journal of TurbomachineryVol. 147(2)
Vaughn College of Aeronautics and Technology (US), Technische Universität Darmstadt (DE), Imperial College London (GB), City & Guilds Group (GB)
Directorate-General for Research and Innovation
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Turbomachinery Performance and Optimization
11.69
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