DDPS | “Data-driven techniques for analysis of turbulent flows” скачать в хорошем качестве

DDPS | “Data-driven techniques for analysis of turbulent flows”

DDPS Talk date: September 27th, 2024 Speaker: Akhil Nekkanti (CalTech, https://scholar.google.co.in/citation...) Description: Turbulent flows are high-dimensional systems characterized by instabilities and non-linearity, which make modeling challenging. Data-driven techniques reduce complexity by extracting key flow features and projecting governing equations onto a low-dimensional subspace. Recently, spectral proper orthogonal decomposition (SPOD), a frequency-domain variant of principal component analysis, has emerged as a powerful tool for analyzing turbulent flows. We extend SPOD to include low-rank reconstruction, denoising, and frequency-time analysis. In this talk, I will demonstrate two applications: gappy-data reconstruction and the intermittency of coherent structures. First, our gappy-data reconstruction algorithm uses spatial and temporal correlations to estimate compromised or missing regions, outperforming standard techniques like gappy POD and Kriging. Second, we introduce a convolution-based strategy for frequency-time analysis that characterizes the intermittency of spatially coherent flow structures. When applied to turbulent jet data, SPOD-based frequency-time analysis reveals that the intermittent occurrence of large-scale coherent structures is directly associated with high-energy events. Finally, we present bispectral mode decomposition (BMD), a technique that extracts flow structures linked to nonlinear triadic interactions by optimizing third-order statistics. This method is applied to a forced turbulent jet to examine and construct the cascade of triads. Bio: Akhil Nekkanti is a postdoctoral scholar in the Division of Engineering and Applied Sciences at Caltech. He received his Ph.D. from the University of California San Diego in 2023. His research interests include reduced-order modeling, hydrodynamic stability, aeroacoustics, and turbulent flows. He specializes in high-fidelity numerical simulations and developing data-driven techniques for flow control and the discovery of flow physics. DDPS webinar: https://www.librom.net/ddps.html 💻 LLNL News: https://www.llnl.gov/news 📲 Instagram:   / livermore_lab   🤳 Facebook:   / livermore.lab   🐤 Twitter:   / livermore_lab   About LLNL: Lawrence Livermore National Laboratory has a mission of strengthening the United States’ security through development and application of world-class science and technology to: 1) enhance the nation’s defense, 2) reduce the global threat from terrorism and weapons of mass destruction, and 3) respond with vision, quality, integrity and technical excellence to scientific issues of national importance. Learn more about LLNL: https://www.llnl.gov/. LLNL-VIDEO-870221