Quad-plane stereoscopic PIV for fine-scale structure measurements in turbulence

Naka, Yoshifumi; Tomita, Ken-ichi; Shimura, Masayasu; Fukushima, Naoya; Tanahashi, Mamoru; Miyauchi, Toshio

doi:10.1007/s00348-016-2146-4

Cited by 12 publications

(8 citation statements)

References 52 publications

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“…This underestimation of points of unstable node/saddle/saddle (region IV) is partially compensated by an overestimation of points of unstable focii (region II). Therefore, in the experiment there is a transfer of data from the strain-dominated regions (D < 0) to the rotationally dominated regions (D > 0), consistent with Buxton et al (2011) and Naka et al (2016). The observed underestimation of points of unstable node/saddle/saddle and overestimation of points of stable node/saddle/saddle can be the result of measurement noise, particularly in the tomographic reconstruction process.…”

Section: Assessment Of the Experimental Datasetsupporting

confidence: 57%

Long-range μPIV to resolve the small scales in a jet at high Reynolds number

2014

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The investigation of flows at high Reynolds number is of great interest for the theory of turbulence, in that the large and the small scales of turbulence show a clear separation. But, as the Reynolds number of the flow increases, the size of the Kolmogorov length scale (g) drops almost proportionally. Aiming at achieving the adequate spatial resolution in the central region of a selfsimilar round jet at high Reynolds numbers (Re k % 350), a long-range lPIV system was applied. A vector spacing of 1:5g was achieved, where the Kolmogorov length scale was estimated to be 55 lm. The resulting velocity fields were used to characterize the small-scale flow structures in this jet. The autocorrelation maps of vorticity and k ci (the imaginary part of the eigenvalue of the reduced velocity gradient tensor) reveal that the structures of intense vorticity have a characteristic diameter of approximately 10g. From the autocorrelation map of the reduced (2D) rate of dissipation, it is inferred that the regions of intense dissipation tend to organize in the form of sheets with a characteristic thickness of approximately 10g. The regions of intense dissipation have the tendency to appear in the vicinity of intense vortices. Furthermore, the joint pdf of the two invariants of the reduced velocity gradient tensor exhibits the characteristic teapot-shape. These results, based on a statistical analysis of the data, are in agreement with previous numerical and experimental studies at lower Reynolds number, which validates the suitability of longrange lPIV for characterizing turbulent flow structures at high Reynolds number.

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Section: Assessment Of the Experimental Datasetsupporting

confidence: 57%

Long-range μPIV to resolve the small scales in a jet at high Reynolds number

2014

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“…Although tomo-PIV has become one of the most widely used volumetric measurement techniques in fluid mechanics, the compromise between the measurement domain size and the spatial resolution resulting from the cross-correlation (Lawson & Dawson 2014; Naka et al. 2016; Fiscaletti et al. 2022) is the major issue that limits its application in certain circumstances.…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, the approaches are only applicable to statistically stable flows as a large database is required in the training process. In the fields of computer vision and video processing, STR reconstruction is commonly known as frame interpolation (Niklaus, Mai & Liu 2017;Chi et al 2020;Bao et al 2021) and is widely used to artificially increase the frame rate of a video by creating fake frames containing sufficient image details between real frames. However, similar studies have rarely been conducted for turbulent flows with the recovery of small-scale structures having evolution frequencies much higher than the sampling rate.…”

Section: Introductionmentioning

confidence: 99%

Four-dimensional variational data assimilation of a turbulent jet for super-temporal-resolution reconstruction

He,

Zeng,

Wang

et al. 2024

J. Fluid Mech.

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The super-temporal-resolution (STR) reconstruction of turbulent flows is an important data augmentation application for increasing the data reach in measurement techniques and understanding turbulence dynamics. This paper proposes a data assimilation (DA) strategy based on weak-constraint four-dimensional variation to conduct an STR reconstruction in a turbulent jet beyond the Nyquist limit from given low-sampling-rate observations. Highly resolved large-eddy simulation (LES) data are used to produce synthetic measurements, which are used as observations and for validation. A segregated assimilation procedure is realised to assimilate the initial condition, inflow boundary condition and model error separately. Different types of observational data are tested. The first type is down-sampled LES data containing many small-scale turbulence structures with or without synthetic noise. The DA results show that the temporal variation of the small-scale structures is well recovered even with noise in the observations. The spectra are resolved to a frequency approximately one order of magnitude higher than what can be captured within the Nyquist limit. The second type of observation is low-sampling-rate tomographic particle image velocimetry (tomo-PIV) data with or without the injection of small-scale structures. The modulation between the large-scale structures contained in the tomo-PIV fields and the small scales injected from the observations is improved. The resultant small scales in the STR reconstruction have the characteristics of authentic turbulence to a considerable extent. Additionally, DA yields much smaller errors in the prediction of particle positions when compared with the Wiener filter, demonstrating the great potential for Lagrangian particle tracking in measurement techniques.

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“…Spherical porous SiO2 particles of which mean particle diameter is 2 μm (Suzukiyushi K.K, Godd Ball, E-6C) were used as tracer particles for SPIV. A PIV algorithm which has been developed in our previous studies (Tanahashi, et al, 2000(Tanahashi, et al, , 2008Shimura, et al, 2011;Naka, et al, 2016) was used to evaluate velocity from the successive particle images. 2D calibration (Prasad, 2000) was applied to each particle images.…”

Section: Simultaneous Measurement Methods Of Oh Plif/chemiluminescencementioning

confidence: 99%