Stereoscopic particle image velocimetry of laser energy deposition on a mach 3.4 flow field

2021 ◽  
Vol 62 (2) ◽  
Author(s):  
Arastou Pournadali Khamseh ◽  
Ramez M. Kiriakos ◽  
Edward P. DeMauro
2021 ◽  
Vol 9 (8) ◽  
pp. 905
Author(s):  
Rui Deng ◽  
Shigang Wang ◽  
Wanzhen Luo ◽  
Tiecheng Wu

In this study, particle image velocimetry was applied to measure the flow field around the bow region of a trimaran with different appendages. The dimensionless axial velocity u/U in test planes 1 and 2 of the testing model was measured by using a towed underwater stereoscopic particle image velocimetry (SPIV) system. Based on the measured flow field data, the local sinkage values in test planes 1 and 2 of the testing model with different appendages at speeds of 1.766 and 2.943 m/s were presented. In addition, the effects of speed, bulbous bow type, T foils, and bow wave on the axial velocity u/U were studied in detail. The acquired experimental data help in understanding the distribution of the flow field around the ship bow, and the data can also act as a reference to verify computational fluid dynamics (CFD) results.


Author(s):  
Deb Banerjee ◽  
Ahmet Selamet ◽  
Rick Dehner ◽  
Keith Miazgowicz

Abstract Particle Image Velocimetry has become a desirable tool to investigate turbulent flow fields in different engineering applications, including flames, combustion engines, and turbomachinery. The convergence characteristics of turbulent statistics of these flow fields are of prime importance since they help with the number of images (temporally uncorrelated) to be captured in order for the results to converge to a certain tolerance or with the assessment of the uncertainty of the measurements for a given number of images. The present work employs Stereoscopic Particle Image Velocimetry to examine the turbulent flow field at the inlet of an automotive turbocharger compressor without any recirculating channel. Optical measurements were conducted at five different mass flow rates spanning from choke to surge at a corrected rotational speed of 80 krpm. The velocity fields thus obtained were used to analyze the convergence of the mean (first statistical moment) and variance (second statistical moment) at different operating conditions. The convergence of the mean at a particular location in the flow field depends on the local coefficient of variation (COV). The number of required images for the mean to converge to a particular tolerance was also found to follow roughly a linear trend with respect to COV. While the convergence of the variance, on the other hand, did not appear to show any direct dependence on the coefficient of variation, it takes significantly more images than the mean to converge to the same level of tolerance.


Author(s):  
Jeff R. Harris ◽  
Michael McPhail ◽  
Christine Truong ◽  
Arnold Fontaine

Stereoscopic particle image velocimetry (SPIV) is a variant of particle image velocimetry (PIV) that allows for the measurement of three components of velocity along a plane in a flow field. In PIV, particles in the flow field are tracked by reflecting laser light from tracer particles into two angled cameras, allowing for the velocity field to be determined. Particle shadow velocimetry (PSV) is an inherently less expensive velocity measurement method since the method images shadows cast by particles from an LED backlight instead of scattered light from a laser. Previous studies have shown that PSV is an adequate substitute for PIV for many two-dimensional, two-component velocimetry measurements. In this work, the viability of the two-dimensional, three-component stereoscopic particle shadow velocimetry (SPSV) is demonstrated by using SPSV to examine a simple jet flow. Results obtained using SPIV are also used to provide benchmark comparison for SPSV measurements. Results show that in-plane and out-of-plane velocities measured using SPSV are comparable to those measured using SPIV.


2002 ◽  
Vol 33 (6) ◽  
pp. 794-800 ◽  
Author(s):  
U. Dierksheide ◽  
P. Meyer ◽  
T. Hovestadt ◽  
W. Hentschel

2010 ◽  
Vol 43 (6) ◽  
pp. 1039-1047 ◽  
Author(s):  
Emily J. Berg ◽  
Jessica L. Weisman ◽  
Michael J. Oldham ◽  
Risa J. Robinson

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