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We consider the frequency domain form of proper orthogonal decomposition (POD) called spectral proper orthogonal decomposition (SPOD). Spectral POD is derived from a space-time POD problem for statistically stationary flows and leads to…

Fluid Dynamics · Physics 2018-06-05 Aaron Towne , Oliver T. Schmidt , Tim Colonius

The identification of coherent structures from experimental or numerical data is an essential task when conducting research in fluid dynamics. This typically involves the construction of an empirical mode base that appropriately captures…

Fluid Dynamics · Physics 2016-04-20 Moritz Sieber , Kilian Oberleithner , Christian Oliver Paschereit

Modal decomposition methods are important for characterizing the low-dimensional dynamics of complex systems, including turbulent flows. Different methods have varying data requirements and produce modes with different properties. Spectral…

Fluid Dynamics · Physics 2025-08-28 Caroline Cardinale , Steven L. Brunton , Tim Colonius

Most model reduction methods reduce the state dimension and then temporally evolve a set of coefficients that encode the state in the reduced representation. In this paper, we instead employ an efficient representation of the entire…

Numerical Analysis · Mathematics 2025-11-03 Peter Frame , Cong Lin , Oliver Schmidt , Aaron Towne

Experimental spatio-temporal flow data often contain gaps or other types of undesired artifacts. To reconstruct flow data in the compromised or missing regions, a data completion method based on spectral proper orthogonal decomposition…

Fluid Dynamics · Physics 2023-02-22 Akhil Nekkanti , Oliver T. Schmidt

An adaptive algorithm for spectral proper orthogonal decomposition (SPOD) of mixed broadband-tonal turbulent flows is developed. Sharp peak resolution at tonal frequencies is achieved by locally minimizing the bias of the spectrum. Smooth…

Fluid Dynamics · Physics 2024-06-25 Brandon C. Y. Yeung , Oliver T. Schmidt

A streaming algorithm to compute the spectral proper orthogonal decomposition (SPOD) of stationary random processes is presented. As new data becomes available, an incremental update of the truncated eigenbasis of the estimated…

Fluid Dynamics · Physics 2019-01-14 Oliver T. Schmidt , Aaron Towne

We demonstrate that accurate computation of the spectral proper orthogonal decomposition (SPOD) critically depends on the choice of frequency resolution. Using both artificially generated data and large-eddy simulation data of a turbulent…

Fluid Dynamics · Physics 2024-02-27 Liam Heidt , Tim Colonius

Four different applications of spectral proper orthogonal decomposition (SPOD): low-rank reconstruction, denoising, frequency-time analysis, and prewhitening are demonstrated on large-eddy simulation data of a turbulent jet. SPOD-based…

Fluid Dynamics · Physics 2021-09-22 Akhil Nekkanti , Oliver T. Schmidt

The use of multitaper estimates for spectral proper orthogonal decomposition (SPOD) is explored. Multitaper and multitaper-Welch estimators that use discrete prolate spheroidal sequences (DPSS) as orthogonal data windows are compared to the…

Fluid Dynamics · Physics 2022-09-14 Oliver T. Schmidt

Many turbulent flows exhibit time-periodic statistics. These include turbomachinery flows, flows with external harmonic forcing, and the wakes of bluff bodies. Many existing techniques for identifying turbulent coherent structures, however,…

Fluid Dynamics · Physics 2024-05-01 Liam Heidt , Tim Colonius

Transport-dominated phenomena provide a challenge for common mode-based model reduction approaches. We present a model reduction method, which is suited for these kind of systems. It extends the proper orthogonal decomposition (POD) by…

Numerical Analysis · Mathematics 2018-02-20 Julius Reiss , Philipp Schulze , Jörn Sesterhenn , Volker Mehrmann

We propose a new algorithm to compute a shifted proper orthogonal decomposition (sPOD) for systems dominated by multiple transport velocities. The sPOD is a recently proposed mode decomposition technique which overcomes the poor performance…

Numerical Analysis · Mathematics 2018-03-06 Philipp Schulze , Julius Reiss , Volker Mehrmann

This work investigates the spatio-temporal evolution of coherentstructures in the wake of a high-speed train. SPOD is used to extract energy spectra and empirical modes for both symmetric and antisymmetric components of the fluctuating flow…

We propose a parallel (distributed) version of the spectral proper orthogonal decomposition (SPOD) technique. The parallel SPOD algorithm distributes the spatial dimension of the dataset preserving time. This approach is adopted to preserve…

The spectral proper orthogonal decomposition (SPOD) is a newly introduced extension of snapshot POD that recently gained attention but also brought up controversial issues. Within the first proposition, the approach was mainly presented in…

Fluid Dynamics · Physics 2017-12-22 Moritz Sieber , C. Oliver Paschereit , Kilian Oberleithner

This study presents band-ensemble Spectral Proper Orthogonal Decomposition (bSPOD). The approach is inspired by frequency smoothing, a method used to reduce estimator variance in power spectral density estimates, and is here extended to…

Direct numerical simulations, performed with a high-order spectral-element method, are used to study coherent structures in turbulent pipe flow at friction Reynolds numbers $Re_{\tau} = 180$ and $550$. The database was analysed using…

Fluid Dynamics · Physics 2023-07-19 Leandra Abreu , André Cavalieri , Philipp Schlatter , Ricardo Vinuesa , Dan Henningson

We propose a technique for performing spectral (in time) analysis of spatially-resolved flowfield data, without needing any temporal resolution or information. This is achieved by combining projection-based reduced-order modeling with…

Fluid Dynamics · Physics 2023-07-31 Katherine J. Asztalos , Abdulrahman Almashjary , Scott T. M. Dawson

We present a new methodology for decomposing flows with multiple transports that further extends the shifted proper orthogonal decomposition (sPOD). The sPOD tries to approximate transport-dominated flows by a sum of co-moving data fields.…

Numerical Analysis · Mathematics 2025-03-07 Philipp Krah , Arthur Marmin , Beata Zorawski , Julius Reiss , Kai Schneider
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