SPLEEN - High Speed Turbine Cascade – Test Case Database - PIV Measurements

This is an open-access database of Particle Image Velocimetry (PIV) measurements of the flow in the high-speed low-pressure turbine cascade SPLEEN C1.  This database complements aerodynamics measurements reported in the database "SPLEEN - High Speed Turbine Cascade – Test Case Database" which can be found at 10.5281/zenodo.7264761.   The data have been collected at the von Karman Institute for Fluid Dynamics during 2022 within the H2020 Clean Sky 2 project SPLEEN – Secondary and Leakage Flow Effects in High-Speed Low-Pressure Turbines. This database contains documents that describe the experimental setup, instrumentation, measurement uncertainties, geometries, and the dataset structure related to the SPLEEN C1 PIV measurements. The database contains experimental data of the test campaign conducted on the linear cascade codenamed SPLEEN C1 in the VKI high-speed wind tunnel S1/C. PIV measurements were performed on the upstream blade-to-blade plane at cascade midspan, passage blade-to-blade plane at cascade midspan, and on a cascade outlet axial plane located 50% of the airfoil axial chord downstream the cascade trailing edge, near the cascade endwall (0-18% of the cascade span). The turbine cascade geometry is representative of designs of high-speed low-pressure turbines for next-generation geared turbofan engines. The measurement datasets describe the flow through the turbine cascade tested at on- and off-design conditions (cascade exit Reynolds and Mach numbers), with and without a turbulence grid located upstream of the cascade. The database includes measurements of flow velocity, flow angles, Mach numbers, and turbulence quantities. The PIV measurements were performed on the SPLEEN C1 turbine cascade equipped WITH a REFERENCE CAVITY ENDWALL (Cavity Aref), WITHOUT WAKE GENERATOR (steady inlet flow), WITH and WITHOUT TURBULENCE GRID (different inlet turbulence level). The project has received Funding from the Clean Sky 2 Joint Undertaking under the European Union's Horizon 2020 research and innovation program under the grant agreement 820883.