Pressure strain correlation modelling for turbulent flows
Jyoti Prakash Panda

TL;DR
This paper introduces an extended tensor basis for pressure strain correlation models in Reynolds Stress Models, leading to improved accuracy and robustness in turbulent flow simulations, validated through experiments and comparisons with established models.
Contribution
It develops a new pressure strain correlation model using additional physics-based tensors, enhancing prediction accuracy over existing models.
Findings
Significant improvement in prediction accuracy of turbulence models.
Enhanced robustness of pressure strain correlation models.
Experimental validation confirms model improvements.
Abstract
Accurate and robust models for the pressure strain correlation are an essential component for the success of Reynolds Stress Models in turbulent flow simulations. However replicating the non-local action of pressure using only local tensors places a large limitation on potential model performance. In this thesis we outline an approach that extends the tensor basis used for pressure strain correlation modeling to formulate models with improved precision and robustness. This set of additional tensors is analyzed and justified based on physics based arguments and analysis of simulation data. Using these tensors models for the rapid and slow pressure strain correlation are developed. The resulting complete pressure strain correlation model is tested for a wide variety of turbulent flows, while being contrasted against the predictions of established models. It is shown that the new model…
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Taxonomy
TopicsWind and Air Flow Studies · Probabilistic and Robust Engineering Design · Computational Fluid Dynamics and Aerodynamics
