2019
DOI: 10.1134/s1063782619050117
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Miniaturized Heat-Flux Sensor Based on a Glass-Insulated Bi–Sn Microwire

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Cited by 4 publications
(1 citation statement)
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“…The gradient method determines the boiling surface temperature gradient by measuring the temperature difference between solid layers ∇T and obtains a linear temperature distribution under steady-state conditions, and the heat flux is calculated by Fourier's law q = −k∇T [110][111][112]. The principle of the thermoelectric effect method, on the other hand, is that materials with anisotropic thermal conductivity generate an electric field with a transverse component in the main axis of the material when heat passes through it due to the Seebeck effect, thus enabling the heat flux to be obtained by detecting the electrical signal, which allows for the ultra-fast response and is suitable for transient heat flux measurements [113]. With the continuous development of Machine Learning, the image [114,115] and acoustic signals [116] of boiling are detected in order to develop a boiling heat flux measurement system with the aid of the Convolutional Neural Networks (CNNs) [117] and Multilayer Perceptron Neural Networks (MLPNNs) [118].…”
Section: Boiling-heat-transfer Coefficient H and Heat Flux Qmentioning
confidence: 99%
“…The gradient method determines the boiling surface temperature gradient by measuring the temperature difference between solid layers ∇T and obtains a linear temperature distribution under steady-state conditions, and the heat flux is calculated by Fourier's law q = −k∇T [110][111][112]. The principle of the thermoelectric effect method, on the other hand, is that materials with anisotropic thermal conductivity generate an electric field with a transverse component in the main axis of the material when heat passes through it due to the Seebeck effect, thus enabling the heat flux to be obtained by detecting the electrical signal, which allows for the ultra-fast response and is suitable for transient heat flux measurements [113]. With the continuous development of Machine Learning, the image [114,115] and acoustic signals [116] of boiling are detected in order to develop a boiling heat flux measurement system with the aid of the Convolutional Neural Networks (CNNs) [117] and Multilayer Perceptron Neural Networks (MLPNNs) [118].…”
Section: Boiling-heat-transfer Coefficient H and Heat Flux Qmentioning
confidence: 99%