Advances in iterative multigrid PIV image processing

By Fulvio Scarano, M. Riethmuller. 2000

790 citations recorded by the source corpus.

Subfields: Computational Mechanics, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/e3c26faad83e5532466ba017bdac869a23c1f70b

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In Computational Mechanics

In Mechanics of Materials

Citations in the corpus

PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB (2014, methodology): “Several methods that account for the transformation of the interrogation areas have been proposed [20–22].”
Motion tracking-enhanced MART for tomographic PIV (2010, methodology): “In the present case, the problem has been reduced to 2D objects, which are therefore analyzed with WIDIM (Scarano and Riethmuller 2000) using interrogation windows elongated in the Xdirection.”
Three-dimensional vorticity patterns of cylinder wakes (2009, methodology): “The analysis is performed with an iterative technique based on the window deformation technique (WIDIM, Scarano and Riethmuller 2000) extended to three dimensional intensity fields [volume deformation iterative multigrid (VODIM)].”
Unsteady aerodynamic forces estimation on a square cylinder by TR-PIV (2007, methodology): “The recordings are analysed with the WIDIM technique (Scarano and Riethmuller 2000) with interrogation windows of 31 · 31 pixels and 75% overlap factor.”
Evaluation of aero-optical distortion effects in PIV (2005, methodology): “Using the results from particle and ray traces, synthetic PIV recordings are produced, which are analyzed using a window deformation iterative multi-grid scheme (WIDIM, Scarano and Riethmuller 2000) with interrogation windows of 31x31 pixels and 50% overlap.”
Estimation of uncertainty bounds for individual particle image velocimetry measurements from cross-correlation peak ratio (2013, background): “Advanced schemes including discrete or continuous window offsets [3–5], image [6] and window deformation [7], and many other techniques provide consistent results even in conditions of high displacement, shear and rotation.”
Digital particle image velocimetry (DPIV) robust phase correlation (2009, methodology): “To simplify our model, we have chosen to approximate the intensity distribution by a discrete Gaussian [19, 20], where higher frequency components of the Gaussian are aliased, contributing to the Paliased noise signal.”
Experimental investigation on interactions among fluid and rod-like particles in a turbulent pipe jet by means of particle image velocimetry (2014, methodology): “00019, whereas for rod-like particles, St is computed according to the formulation of Shapiro and Goldenberg (1993) for the particle response time.”
Analysis and treatment of errors due to high velocity gradients in particle image velocimetry (2003, methodology): “These techniques of window deformation are beginning to be commonly used, and error tests have been carried out by Fincham and Delerce (2000) and Scarano and Riethmuller (2000).”
Dense velocity reconstruction from tomographic PTV with material derivatives (2016, methodology): “For tomographic PIV analysis, an iterative cross-correlation technique with multi-grid and window-deformation (Scarano and Riethmuller 2000) is used with four iterations and an interrogation volume size such that ten particles are included in the measurement box.”
Lagrangian and Eulerian pressure field evaluation of rod-airfoil flow from time-resolved tomographic PIV (2011, methodology): “Three-dimensional particle field motion is computed by spatial cross-correlation of pairs of reconstructed volumes with VODIM software (Volume Deformation Iterative Multigrid, developed at TU Delft), an extension to volumetric intensity fields of the window deformation technique for planar cross-cor”
Limitations of accuracy in PIV due to individual variations of particle image intensities (2009, methodology): “The bi-cubic spline interpolation, the Whittaker interpolation [30, 31] and the Gaussian low-pass image interpolation [32] have been implemented based on a 11× 11 pixel image sub-space.”