Session: 31-07 Compressor Stability and Loss Mechanisms

Paper Number: 154144

A Multiscale Representation of Turbulence Generation in Compressor Flows 

Turbomachinery flows exhibit strong unsteadiness, characterized by periodic wake-related disturbances superimposed on background turbulence. The turbulence generation mechanisms in these flows involve multiple interacting scales, making accurate modeling challenging. Developing robust transition models capable of capturing the multi-modal nature of these processes is crucial for accurately predicting the overall performance of turbomachinery components.

In our previous work (GT2024-128738) we employed a turbulent event recognition technique that was used on high-fidelity data of a compressor cascade under steady inflow conditions to classify individual flow features as “laminar” and “turbulent” depending on their role in transition. This allowed us to characterize features such as streaks and Kelvin-Helmholtz roll-ups in a manner that is consistent and data-driven. In this work we consider other high-fidelity scale-resolving datasets of compressor blades (CDA and NACA65) under unsteady inflow conditions.

The objective of this work is to test whether “laminar” and “turbulent” classification is appropriate for this class of problems. For that purpose a multi scale analysis of the turbulence generation mechanisms is adopted. This is achieved by clustering flow scales using an unsupervised data-driven method. The procedure provides the spatio-temporal distribution of the boundary layer intermittency that is then used as reference for the identification of flow scales that drive the transition process. Following that, turbulence production for different scale clusters and the energy exchange between them are examined. Data reported in the paper shows that a low dimensional multi-scale representation of turbulence generation mechanisms can be achieved for compressor flows. The approach discussed here has potential to extend the concept of two-scale laminar-turbulent kinetic energy models, especially with regards to incorporating the impact of incoming wakes into the RANS framework.

Presenting Author: Matteo Dellacasagrande University of Genoa

Presenting Author Biography: Matteo Dellacasagrande is a research fellow at the University of Genoa in the Department of Mechanical, Energy, Management, and Transportation Engineering (DIME). His current research focuses on boundary layer separation and transition processes through numerical simulations and experiments, as well as the experimental study of the aeroacoustics of axial fans

Authors:

Matteo Dellacasagrande University of Genoa
Pawel Przytarski University of Genoa