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In order to accurately analyze the motion characteristics of nanofluid particles in the flow state, a method for micro-motion analysis of nanofluid particles based on machine vision was proposed. The influence of temperature on the micro-motion of nanoparticles was studied by establishing a water-based near-wall flow simulation model of nanofluids, and the Lennard-Jones potential parameters of nanofluids were obtained. Machine vision imaging technology is used to establish a reference system for nanofluid particles micro-motion image acquisition. Based on this system, the micro-motion images of nanofluid particles are collected, and the micro-motion characteristics of nanofluid particles are accurately detected. An experimental measuring platform composed of optical system and electronic system is established. The rotational and translational motions of nanoparticles and the velocity and temperature distributions of nanofluids are obtained. It was found that the velocity gradient of the nanofluid near the wall was higher than that of the base liquid, and the temperature of the nanofluid near the wall was significantly higher than that of the single-phase base liquid. The experimental results show that the velocity and temperature distributions of nanofluids at different temperatures can be obtained by using this method.
PAPER REVISED: 2021-06-12
PAPER ACCEPTED: 2021-07-07
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THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Issue 6, PAGES [4145 - 4151]
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