Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 91 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 29 tok/s
GPT-5 High 26 tok/s Pro
GPT-4o 98 tok/s
GPT OSS 120B 470 tok/s Pro
Kimi K2 216 tok/s Pro
2000 character limit reached

Studying propagating turbulent structures in the near wake of a sphere using Hilbert proper orthogonal decomposition (2507.19167v1)

Published 25 Jul 2025 in physics.flu-dyn

Abstract: Turbulent flows, despite their apparent randomness, exhibit coherent structures that underpin their dynamics. Proper orthogonal decomposition (POD) has been widely used to extract these structures from experimental data. While periodic features like vortex shedding can be identified using POD mode pairs when periodicity dominates the flow, detecting such structures in complex flows is more challenging. The Hilbert proper orthogonal decomposition (HPOD) addresses this by applying POD to the analytic signal of the turbulent fluctuations, yielding complex modes with a $90\circ$ phase shift between the real and imaginary components. These modes capture propagating structures effectively but introduce filtering artefacts from the Hilbert transform that is used to derive the analytic signal. The current work investigates the relationship between the modes of the POD and those of the HPOD on the velocity fluctuations in the wake of a sphere. By comparing their outputs, POD mode pairs that correspond to the same propagating structures revealed by HPOD are identified. Furthermore, this study explored whether computing the analytic signal of the POD modes can replicate the HPOD modes, offering a more computationally efficient method for determining the pairs of POD modes that represent propagating structures. The results show that the pairs of POD modes identified by the HPOD can be more efficiently determined using the Hilbert transform directly on the POD modes. This method enhances the interpretive power of POD, enabling more detailed analysis of turbulent dynamics without introducing the filtering from the Hilbert transform.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.