An application of Gappy POD

Murray, Nathan E.; Ukeiley, Lawrence

doi:10.1007/s00348-006-0221-y

Cited by 80 publications

(39 citation statements)

References 13 publications

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“…The corresponding overall standard deviations of velocity in region 1, 2 and 3 were 6%, 2% and 4%, respectively, of the mean jet velocity. The uncertainty calculation was based on the error analysis developed by Coleman and Steele (1995); this error analysis was previously applied to PIV velocity measurements by Gui et al (2001) and by Murray and Ukeiley (2007).…”

Section: Piv Experimental Setupmentioning

confidence: 99%

PIV measurements of an air jet impinging on an open rotor-stator system

et al. 2012

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Section: Piv Experimental Setupmentioning

confidence: 99%

PIV measurements of an air jet impinging on an open rotor-stator system

et al. 2012

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“…We can simplify the process by considering two types of vectors: valid vectors and spurious vectors needing post-processing. Only the valid vectors are retained and serve as input for an iterative Gappy POD algorithm (Everson and Sirovich 1995;Murray and Ukeiley 2007). The spurious vectors are considered simply as gaps and are estimated using this method.…”

Section: α = 0 • Incidence Casementioning

confidence: 99%

“…Specifically, an extension of POD, called Gappy POD, is chosen, a technique first described by Everson and Sirovich (1995) as a means of approximating the complete velocity fields using a small number of velocity measurements. More recently, Gappy POD has been applied successfully to PIV data by Murray and Ukeiley (2007). Venturi and Karniadakis (2004) also used Gappy POD to investigate its ability to recover large artificial gaps in direct numerical simulation data of flow past a cylinder.…”

mentioning

confidence: 98%

Stereoscopic Particle Image Velocimetry Measurements in an Urban-Type Boundary Layer: Insight into Flow Regimes and Incidence Angle Effect

Monnier¹,

Neiswander²,

Wark³

2010

Boundary-Layer Meteorol

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An experimental investigation of the three-dimensional flow through an urban-type array (four rows of three cuboid Plexiglas blocks) in a laboratory modelled neutrally stratified atmospheric boundary layer is presented. We concentrate on the effect of the streamwise spacing between adjacent rows defining two different flow regimes (wake interference and skimming flow) as well as the effect of the incident angle of the approaching boundary layer. Stereoscopic particle image velocimetry measurements provide all three components of the velocity field in closely spaced two-dimensional planes in a region located in the middle row downstream of the centre block. It is found that the maximal exchange rate between the fluid within the street and the flow above is for the wake interference regime. Two regions are apparent: one influenced by streamwise velocity fluctuations, the other by spanwise fluctuations. In addition, the incidence angle of the incoming flow has a much more dramatic effect for the wake interference regime that would greatly favour dispersion. Coherent-structure identification tools are applied to obtain information on the shape, extent and localisation of vortical structures.

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“…The authors proposed a methodology, dubbed "Gappy POD", constructing an approximation subspace when only some elements of each solution h(θ) are observed. This approach has been applied with success to e.g., oceanography in [7] or fluid mechanics in [8][9][10]. Unfortunately, Gappy POD requires some diversity in the observation operator to work properly: as noted in [9], this method is doomed to produce poor approximation subspaces as soon as some directions of H are never observed.…”

Section: Introductionmentioning

confidence: 99%

Model reduction from partial observations

Herzet

Héas

Drémeau

2017

Numerical Meth Engineering

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This paper deals with model-order reduction of parametric partial differential equations (PPDE). More specifically, we consider the problem of finding a good approximation subspace of the solution manifold of the PPDE when only partial information on the latter is available. We assume that two sources of information are available: i) a "rough" prior knowledge, taking the form of a manifold containing the target solution manifold; ii) partial linear measurements of the solutions of the PPDE (the term partial refers to the fact that observation operator cannot be inverted). We provide and study several tools to derive good approximation subspaces from these two sources of information. We first identify the best worst-case performance achievable in this setup and propose simple procedures to approximate the corresponding optimal approximation subspace. We then provide, in a simplified setup, a theoretical analysis relating the achievable reduction performance to the choice of the observation operator and the prior knowledge available on the solution manifold.

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An application of Gappy POD

Cited by 80 publications

References 13 publications

PIV measurements of an air jet impinging on an open rotor-stator system

PIV measurements of an air jet impinging on an open rotor-stator system

Stereoscopic Particle Image Velocimetry Measurements in an Urban-Type Boundary Layer: Insight into Flow Regimes and Incidence Angle Effect

Model reduction from partial observations

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