The availability of high fidelity Computational Fluid Dynamics (CFD) suitable for turbomachinery design offers a powerful tool to define an effective experimental measurement campaign. This paper describes approaches to integrate Reynolds-Averaged Navier-Stokes simulations into experiment design. CFD simulations are used to a priori estimate the measurement errors induced by the finite spatial sampling and inherent limited sensor bandwidth for space-resolved and time-resolved turbine aerothermal measurements. The CFD predictions are employed to optimize the probe placement and traversing while minimizing the measurement errors associated with the finite spatial sampling. Additionally, time-resolved CFD traces serve to quantify the measurement errors as a function of the measurement chain bandwidth.
This approach was applied to a recent turbine test program, focused on the aerothermal characterization of the turbine over-tip casing endwall and downstream flow field. Based on the 3D simulations of the different rotor geometries, the discrete radial positions of the aerothermal probes located downstream of the stage were optimized to minimize the uncertainty on the individual aerodynamic quantities, as well as to mitigate the propagated uncertainty on the turbine loss coefficient. Furthermore, the effect of the implicit time-averaging of all sensors, due to the limited frequency response, was quantified.
This manuscript illustrates the benefits of CFD in the design and planning of a turbine experimental campaign. Based on the proposed procedure, the experimentalist can find the best compromise between measurement precision and instrumentation costs by establishing the minimum sensor performance requirements to obtain the target accuracies.
