Simultaneous optical measurement of temperature and velocity fields in solidifying liquids

Anders, Sten; Noto, Daisuke; Tasaka, Yuji; Eckert, Sven

doi:10.1007/s00348-020-2939-3

Cited by 18 publications

(11 citation statements)

References 43 publications

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“…To solve this kind of multiple input regression problems, an artificial neural network (ANN) would be a practical solution. The application of ANN to a similar color fluid measurement as the one reported here can be seen in liquid crystal thermometry (e.g., [36]). Although the applicable range of the stress field measurements needs more consideration in terms of the flow intensity, incorporating these various methods, temporally and spatially resolved stress field measurements in Newtonian fluids utilizing the stress-optic law, would become possible in future research.…”

Section: Discussionmentioning

confidence: 78%

Applicability evaluation of the stress-optic law in Newtonian fluids toward stress field measurements

Noto

Tasaka

Hitomi

et al. 2020

Phys. Rev. Research

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A novel rheoscopic fluid displaying coloration due to flow-induced birefringence is investigated through laboratory experiments to ascertain if it satisfies the stress-optic law in fluids in direct stress field measurements of Newtonian fluids. To validate this experimentally, two types of spin-up experiments ensuring two-dimensional flows were performed: color visualization using the rheoscopic fluid and velocity field measurement by particle image velocimetry. Using a wave-number analysis, the orientation angle of the birefringence was determined from a single color snapshot in axisymmetric and unidirectional flows. Direct comparisons between color and shear stress values made it possible to establish a unique relation between the two, verifying that the stress-optic law can be applied in the fluid. The results of the present study suggest a promising avenue toward enabling temporally and spatially resolved stress field measurements in Newtonian fluids.

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Section: Discussionmentioning

confidence: 78%

Applicability evaluation of the stress-optic law in Newtonian fluids toward stress field measurements

Noto

Tasaka

Hitomi

et al. 2020

Phys. Rev. Research

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“…More details on the design of the white light source and the light sheet optics can be found in the study of Moller, Resagk & Cierpka (2020). For additional background information, the reader is referred to Schmeling et al (2014) or Anders et al (2020).…”

Section: Experimental Investigationmentioning

confidence: 99%

Combined particle image velocimetry and thermometry of turbulent superstructures in thermal convection

Möller

Käufer

Pandey³

et al. 2022

J. Fluid Mech.

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Turbulent superstructures in horizontally extended three-dimensional Rayleigh–Bénard convection flows are investigated in controlled laboratory experiments in water at Prandtl number ${Pr}=7$ . A Rayleigh–Bénard cell with square cross-section, aspect ratio $\varGamma =l/h=25$ , side length $l$ and height $h$ is used. Three different Rayleigh numbers in the range $10^{5} < {Ra} < 10^{6}$ are considered. The cell is accessible optically, such that thermochromic liquid crystals can be seeded as tracer particles to monitor simultaneously temperature and velocity fields in a large section of the horizontal mid-plane for long time periods of up to 6 h, corresponding to approximately $10^{4}$ convective free-fall time units. The joint application of stereoscopic particle image velocimetry and thermometry opens the possibility to assess the local convective heat flux fields in the bulk of the convection cell and thus to analyse the characteristic large-scale transport patterns in the flow. A direct comparison with existing direct numerical simulation data in the same parameter range of $Pr$ , ${Ra}$ and $\varGamma$ reveals the same superstructure patterns and global turbulent heat transfer scaling ${Nu}({Ra})$ . Slight quantitative differences can be traced back to violations of the isothermal boundary condition at the extended water-cooled glass plate at the top. The characteristic scales of the patterns fall into the same size range, but are systematically larger. It is confirmed experimentally that the superstructure patterns are an important backbone of the heat transfer. The present experiments enable, furthermore, the study of the gradual evolution of the large-scale patterns in time, which is challenging in simulations of large-aspect-ratio turbulent convection.

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“…After recording the RGB-images, the color information is then transformed into the HSV/I (Hue, Saturation, Value/Intensity) color space because the perceptible change in color appearance can be sufficiently described by the Hue value only, which means that a bijective relation between Hue value and temperature exists. However, neural networks (NN) were also successfully applied to estimate the temperature from the intensity data, see Anders et al (2020). The novelty of this work is the application of a multi-spectral camera instead of a conventional RGB color camera to record the color response of the TLCs.…”

Section: Introductionmentioning

confidence: 99%

Multi-spectral imaging for Thermochromic Liquid Crystal based Particle Image Thermometry: A proof of concept

Käufer¹,

Möller²,

Rosenberger³

et al. 2021

ISPIV21

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In this contribution, a novel imaging approach for Thermochromic Liquid Crystal (TLC) based Particle Image Thermometry (PIT) is demonstrated. In contrast to state of the art approaches, a multi-spectral camera was used to record the color response of the Thermochromic Liquid Crystals seeding particles. An experiment with a transparent, water-filled, cylindrical cell as the central element was set up to investigate the novel approach. The temperature in the cell can be controlled by adjusting the temperature of the bottom and top plate. Calibration images at eleven different temperatures ranging from 18 ◦C to 21.6 ◦C, as well as images of a stable thermal stratification, were recorded. 90 percent of the calibration data was used to train a neural network (NN) to predict the temperature. The remaining 10 percent of the calibration data and the data of the stable thermal stratification were used to test the NN. The tests show that the deviation between predicted and ground truth temperature is mostly below 0.1 K and that the linear profile of the stable thermal stratification can be predicted with a maximum deviation of ≈ 0.15 K. This shows that multi-spectral imaging with neural networks for data processing is feasible and a promising concept.

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Simultaneous optical measurement of temperature and velocity fields in solidifying liquids

Abstract: We introduce a complex image processing scheme for the simultaneous application of liquid crystal thermometry (LCT), in addition to the previously established method in

Cited by 18 publications

References 43 publications

Applicability evaluation of the stress-optic law in Newtonian fluids toward stress field measurements

Applicability evaluation of the stress-optic law in Newtonian fluids toward stress field measurements

Combined particle image velocimetry and thermometry of turbulent superstructures in thermal convection

Multi-spectral imaging for Thermochromic Liquid Crystal based Particle Image Thermometry: A proof of concept

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