Tomographic particle image velocimetry

By G. Elsinga, Fulvio Scarano, Bernhard Wieneke, B. W. van Oudheusden. 2006

1,505 citations recorded by the source corpus.

Subfields: Computational Mechanics, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/073b265b26dce17d51489328cced962162b5a45c

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In Computational Mechanics

In Ocean Engineering

Citations in the corpus

Motion tracking-enhanced MART for tomographic PIV (2010, methodology): “The accuracy of the reconstruction can be quantified by the quality factor Q (Elsinga et al 2006b), computed as the normalized cross-correlation coefficient between the actual solution (usually only available for computer-simulated problem) and the reconstructed intensity field: Q = ∑ Eactual ·…”
Decomposition of time-resolved tomographic PIV (2012, methodology): “Threedimensional velocity fields are then computed based on a spatial cross-correlation of two subsequent volumes, and data postprocessing using a space-time regression with a 5 pt 9 5 pt 9 5 pt 9 5 pt kernel reduces velocity fluctuations due to measurement or processing noise (Elsinga et al. 2006).”
Three-dimensional vortex organization in a high-Reynolds-number supersonic turbulent boundary layer (2010, methodology): “The intensity distribution in the volume was reconstructed from the recorded images using the multiplicative algebraic reconstruction technique (MART) algorithm (Elsinga et al. 2006b) with five iterations.”
On the use of helium-filled soap bubbles for large-scale tomographic PIV in wind tunnel experiments (2015, background): “The appearance of tomographic PIV (Elsinga et al. 2006) has moved further the research tools for investigating the fundamental aspects of complex turbulent flows (Westerweel et al.”
Using digital holographic microscopy for simultaneous measurements of 3D near wall velocity and wall shear stress in a turbulent boundary layer (2008, background): “tomographic PIV ( Elsinga et al. 2006 ), has enables characterization of vortical structures in regions extending from 15 to 47% of a supersonic turbulent boundary layer (Elsinga et al. 2007).”
Lagrangian and Eulerian pressure field evaluation of rod-airfoil flow from time-resolved tomographic PIV (2011, methodology): “By this work, tomographic particle image velocimetry technique (Elsinga et al. 2006; Schröder et al. 2008), in thin-volume configuration, enabling to fully describe the velocity gradient tensor, is applied to study the 3-”
Pulsed operation of high-power light emitting diodes for imaging flow velocimetry (2010, neutral): “, tomographic PIV [17] or 3D-PTV [18]).”
PIV-based pressure measurement (2013, methodology): “(26) In comparison to equation (9), this shows that a 3D characterization of the mean flow, obtainable for example with multiple-plane 3C-PIV, is a sufficient basis to be able to compute the in-plane mean pressure distribution.”
Eulerian and Lagrangian views of a turbulent boundary layer flow using time-resolved tomographic PIV (2011, methodology): “With the same software tool, the reconstruction of the three-dimensional particle light intensity distributions was computed by means of the MART tomographic algorithm specialized for PIV signals (Elsinga et al. 2006).”
Three-dimensional vorticity patterns of cylinder wakes (2009, methodology): “According to the numerical evaluation of Elsinga et al. (2006) , systems with two cameras are only adequate for very low seeding density (below 0.01 ppp), whereas the most commonly used configuration with four cameras is able to deal with a particle image density of 0.05 ppp (i.e.”
Universal aspects of small-scale motions in turbulence (2010, methodology): “(2008), who measured the full three-dimensional (3D) velocity distribution in water by tomographic particle image velocimetry (PIV) (Elsinga et al. 2006).”
Shake-The-Box: Lagrangian particle tracking at high particle image densities (2016, methodology): “From various experimental investigations, average velocity errors ranging from 0.2 to 0.5 px (Elsinga et al. 2006b; Atkinson et al. 2011; Lynch and Scarano 2014) have been reported.”
Estimation of the dissipation rate of turbulent kinetic energy: A review (2021, methodology): “Tomographic PIV is capable of measuring 3-D, 3-C velocity field based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume (Elsinga et al., 2006; Scarano, 2012).”
Volume self-calibration for 3D particle image velocimetry (2008, neutral): “The tomographic reconstruction step requires that each voxel position in space is mapped to a camera pixel position with an error less than 0.4 pixel ( Elsinga et al. 2006 ), preferably less than 0.1 pixel.”