Sensitivity mapping of TBL wall-pressure spectra with CFD turbulence models for wind tunnel test result prediction

TL;DR

This study evaluates how different turbulence models and spectrum models in CFD simulations influence the accuracy of wind tunnel wall-pressure spectrum predictions for turbulent boundary layers.

Contribution

It systematically maps the sensitivity of wall-pressure spectrum models to various RANS turbulence models and boundary layer parameters, aiding model selection for accurate wind tunnel result prediction.

Findings

Best spectrum models identified through wind tunnel data comparison.

Errors in RANS data estimated using experimental TBL parameters.

Sensitivity maps created between spectrum models and RANS models at different wall-normal distances.

Abstract

In the present work, an attempt is made to map the sensitivity of the existing zero pressure gradient (ZPG) turbulent boundary layer (TBL) wall-pressure spectrum models with different TBL parameters, and eventually, with different Reynolds Averaged Navier Stokes (RANS) turbulence models, simulated in OpenFOAM and ANSYS Fluent solvers. This study will help future researchers to choose a particular RANS turbulence model vis-\`a-vis a particular wall-spectrum model in order to obtain a reasonably accurate wind tunnel result predicting capability. First, the best-predicting pressure spectrum models are selected by comparing them with wind tunnel test data. Next, considering the experimental TBL parameters as benchmarks, errors in RANS-produced data are estimated. Furthermore, wall-pressure spectra are calculated following semi-empirical spectrum models using TBL parameter feed obtained from experiments and computational fluid dynamics (CFD) simulations. Finally, sensitivity mapping is performed between spectrum models and the RANS models, with different normalized wall-normal distances (y+).