6 July 1999 Stereoscopic imaging velocimetry for space material processing experiments
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Abstract
Measurement of 3D three-component velocity fields is of profound importance in microgravity fluid experiments including crystal growth, two-phase flows, and thermocapillary phenomena. Stereoscopic imaging velocimetry (SIV) is an optical nonintrusive technique for measuring gross-field flow, which is advantageous in system simplicity for building compact hardware and in software efficiency for continual near-real-time velocity monitoring. However, the challenge is how to increase spatial resolution, that is, marker particle density while maximizing data recovery rate. In this paper, the new SIV algorithms which utilize neural networks, are presented. Preliminary results from both simulating calculation and experiment show that the neural network algorithms offer very good potential for performance enhancement and has proven to be very useful for the SIV technique.
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Yi Ge, Soyoung Stephen Cha, "Stereoscopic imaging velocimetry for space material processing experiments", Proc. SPIE 3792, Materials Research in Low Gravity II, (6 July 1999); doi: 10.1117/12.351287; https://doi.org/10.1117/12.351287
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KEYWORDS
Particles

Neural networks

Stochastic processes

Velocimetry

Evolutionary algorithms

Stereoscopy

Detection and tracking algorithms

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