Transient and Periodic Steady-State Characteristics of the Local Heat Transfer Measurement by Thermal Perturbation with Gaussian Power Density Distribution & A Supplementary Perspective with Comments

TL;DR

This paper investigates the measurement of local heat transfer coefficients using thermal perturbation with Gaussian power density, analyzing factors like spikiness, Biot number, and data processing optimization for improved accuracy.

Contribution

It introduces an analytical and statistical approach to optimize thermal perturbation measurements, emphasizing the impact of spikiness and time series data processing.

Findings

Optimal Gaussian perturbation parameters identified.

Time series measurement benefits near Biot number of unity.

Comparison of temporal modes reveals counterintuitive features.

Abstract

The local heat transfer coefficient measurement with temperature oscillation induced by periodic thermal perturbation - usually via a Gaussian laser beam, was investigated for the impact of the spikiness (i.e., the standard deviation) elaborated in comparison with the analytical model for dimensional analysis. The statistically more robust technique that relies on the linearity of the spatial phase distribution of the test point array was favored when the target Biot number approaches unity in terms of its order of magnitude. The preferred upper limit for thermographic scanning was discussed as the simplification of later data processing is concerned. Nonetheless, the time elapsed for an acceptable periodic steady state, which in principle leans to the higher end of the target Biot number spectrum in a log scale, indicates the benefit from the time series of pointwise temperature measurement - as in the conventional single-blow testing, where the effect of spikiness, as well as that of the location of individual test point, holds. Note that the vicinity as the target Biot number approaches unity was again observed with higher preference. A supplementary perspective was provided to the concerns, including noise tolerance, sampling rate, test duration, the spikiness of the imposed heat flux, and the accuracy-related parameters, in the measurement of local Biot number with thermal perturbation. The optimization was implemented with a Gaussian process surrogate model for data processing, within the specified parametric range of interest. The two commonly employed temporal modes of the imposed heat flux were compared with counterintuitive features discussed.