Single-pixel resolution velocity/convection velocity field of a supersonic jet measured by particle/schlieren image velocimetry

2020 ◽  
Vol 61 (6) ◽  
Author(s):  
Yuta Ozawa ◽  
Takuma Ibuki ◽  
Taku Nonomura ◽  
Kento Suzuki ◽  
Atsushi Komuro ◽  
...  
Keyword(s):  
Velocity Field ◽  
Supersonic Jet ◽  
Convection Velocity ◽  
Schlieren Image ◽  
Pixel Resolution ◽  
Image Velocimetry ◽  
Single Pixel

scholarly journals A PIV Methodology for High-Resolution Measurement of Flow Statistics

2000 ◽  
Author(s):  
Eric B. Cummings ◽  
Robert W. Schefer ◽  
Jacob N. Chung
Keyword(s):  
High Resolution ◽  
Diagnostic Technique ◽  
Mean Velocity ◽  
Pixel Resolution ◽  
Piv Measurements ◽  
Velocity Statistics ◽  
Image Velocimetry ◽  
Flow Image ◽  
Image Pairs ◽  
Single Pixel

Abstract Particle-image velocimetry (PIV) is a flow-diagnostic technique that provides velocity fields from a comparison of images of particulate-laden flow. We have developed a PIV processing methodology that extracts measurements of the particle-displacement probability density function (PDF) from a flow video or ensemble of flow-image pairs. Single-pixel measurement of mean velocity can be obtained from an ensemble of O(103) images. Measurements of higher-order moments of the velocity PDF require spatial averaging (i.e., lower spatial resolution), larger ensembles of images, or a combination of the two. We present single-pixel-resolution PIV measurements of a steady microflow and high-resolution measurements of the velocity PDF of a stationary turbulent flow. This methodology has applications in quantifying velocity statistics in other stochastic flows, e.g., bulk and near-wall boiling.

scholarly journals Experimental Validation of Falling Liquid Film Models: Velocity Assumption and Velocity Field Comparison

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1205
Author(s):  
Ruiqi Wang ◽  
Riqiang Duan ◽  
Haijun Jia
Keyword(s):  
Experimental Data ◽  
Particle Image Velocimetry ◽  
Velocity Field ◽  
Experimental Validation ◽  
Particle Image ◽  
Velocity Fields ◽  
Number Range ◽  
Comparison Results ◽  
Image Velocimetry ◽  
Experimental Particle

This publication focuses on the experimental validation of film models by comparing constructed and experimental velocity fields based on model and elementary experimental data. The film experiment covers Kapitza numbers Ka = 278.8 and Ka = 4538.6, a Reynolds number range of 1.6–52, and disturbance frequencies of 0, 2, 5, and 7 Hz. Compared to previous publications, the applied methodology has boundary identification procedures that are more refined and provide additional adaptive particle image velocimetry (PIV) method access to synthetic particle images. The experimental method was validated with a comparison with experimental particle image velocimetry and planar laser induced fluorescence (PIV/PLIF) results, Nusselt’s theoretical prediction, and experimental particle tracking velocimetry (PTV) results of flat steady cases, and a good continuity equation reproduction of transient cases proves the method’s fidelity. The velocity fields are reconstructed based on different film flow model velocity profile assumptions such as experimental film thickness, flow rates, and their derivatives, providing a validation method of film model by comparison between reconstructed velocity experimental data and experimental velocity data. The comparison results show that the first-order weighted residual model (WRM) and regularized model (RM) are very similar, although they may fail to predict the velocity field in rapidly changing zones such as the front of the main hump and the first capillary wave troughs.

scholarly journals Visually precise, low-damage, single-cell spatial manipulation with single-pixel resolution

2021 ◽  
Vol 12 (11) ◽  
pp. 4111-4118
Author(s):  
Qi Zhang ◽  
Yunlong Shao ◽  
Boye Li ◽  
Yuanyuan Wu ◽  
Jingying Dong ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Pixel Resolution ◽  
Single Pixel

We achieved the low-damage spatial puncture of single cells at specific visual points with an accuracy of <65 nm.

scholarly journals Spatial Chemometrics and Comprehensive Chemical Imaging based Molecular Histopathology Delineates Anatomical Heterogeneity at Single Pixel Resolution

2020 ◽  
Author(s):  
Patrick Wehrli ◽  
Wojciech Michno ◽  
Laurent Guerard ◽  
Julia Fernandez-Rodriguez ◽  
Anders Bergh ◽  
...  
Keyword(s):  
Image Registration ◽  
Biological Tissues ◽  
Chemical Imaging ◽  
Chemical Information ◽  
Imaging Data ◽  
Pixel Resolution ◽  
Registration Method ◽  
Analysis Methods ◽  
Multiple Imaging ◽  
Single Pixel

<p>Imaging mass spectrometry (IMS) is a powerful tool for spatially-resolved chemical analysis and thereby offers novel perspectives for applications in biology and medicine. The understanding of chemically complex systems, such as biological tissues, benefits from the combination of multiple imaging modalities contributing with complementary molecular information. Effective analysis and interpretation of multimodal IMS data is challenging and requires both, precise alignment and combination of the imaging data as well as suitable statistical analysis methods to identify cross-modal correlations. Commonly applied IMS data analysis methods include qualitative comparative analysis where cross-modal interpretation is subject to human judgement; Workflows that incorporate image registration procedures are usually applied for co-representing data rather than to mine data across modalities. </p><p>Here, we present an IMS-based, histology-driven strategy for comprehensive interrogation of biological tissues by spatial chemometrics. Our workflow implements a 1+1-evolutionary image registration method enabling direct correlation of chemical information across multiple modalities at single pixel resolution. Comprehensive multimodal imaging data were evaluated using a novel approach based on orthogonal multiblock component analysis (OnPLS). Finally, we present a novel image fusion method by implementing consecutively acquired pathological staining data to enhance histological interpretation.</p><p>We demonstrate the method’s potential in two biomedical applications where trimodal matrix-assisted laser desorption/ionization (MALDI) IMS delineates pathology associated co-localization patterns of lipids and proteins in (1) a transgenic Alzheimer’s disease (AD) mouse model, and in (2) a human xenograft rat model of prostate cancer. The presented image analysis paradigm allows to comprehensively interrogate complex biological systems with single pixel resolution at cellular length scales.</p>

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