Critical Analysis of Dual-Probe Heat-Pulse Technique Applied to Measuring Thermal Diffusivity

Bovesecchi, G.; Coppa, P.; Corasaniti, Sandra; Potenza, M.

doi:10.1007/s10765-018-2402-3

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…where t 0 is the time length of the pulse when it is square shaped. In [65], the authors used two probes similar to those of the TCP, located parallel to each other, and inserted into the material to be tested. One of the two probes was used as a heat flux source, generating a heat flow pulse of finite length in the sample, while the other, located at a short distance, r, recorded the temperature increase.…”

Section: Dual-probe Thermal Diffusivity Measurementmentioning

confidence: 99%

“…The analytical solution of the heat propagation in the case of a square heat pulse is provided by Equation ( 11), as shown by Ref. [65]. A detailed analysis of the errors easily occurring when applying the method is reported in [65], which also describes the possible corrections.…”

Section: Dual-probe Thermal Diffusivity Measurementmentioning

confidence: 99%

“…[65]. A detailed analysis of the errors easily occurring when applying the method is reported in [65], which also describes the possible corrections. With respect to the laser flash method and the other surface methods, which use disk-shaped samples, the DP method allows one to measure the thermal diffusivity of bulk samples, such as soils.…”

Section: Dual-probe Thermal Diffusivity Measurementmentioning

confidence: 99%

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Modeling and Measuring Thermodynamic and Transport Thermophysical Properties: A Review

et al. 2022

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The present review describes the up-to-date state of the evaluation of thermophysical properties (TP) of materials with three different procedures: modeling (also including inverse problems), measurements and analytical methods (e.g., through computing from other properties). Methods to measure specific heat and thermal conductivity are described in detail. Thermal diffusivity and thermal effusivity are a combination of the previously cited properties, but also for these properties, specific measurement and calculation methods are reported. Experiments can be carried out in steady-state, transient, and pulse regimes. For modeling, special focus is given to the inverse methods and parameter estimation procedures, because through them it is possible to evaluate the thermophysical property, assuring the best practices and supplying the measurement uncertainty. It is also cited when the most common data processing algorithms are used, e.g., the Gauss–Newton and Levenberg–Marquardt least squares minimization algorithms, and how it is possible to retrieve values of TP from other data. Optimization criteria for designing the experiments are also mentioned.

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Section: Dual-probe Thermal Diffusivity Measurementmentioning

confidence: 99%

Section: Dual-probe Thermal Diffusivity Measurementmentioning

confidence: 99%

Section: Dual-probe Thermal Diffusivity Measurementmentioning

confidence: 99%

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Modeling and Measuring Thermodynamic and Transport Thermophysical Properties: A Review

et al. 2022

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“…The PTF standard uncertainty of thermal diffusivity primarily depends on the measurements of a period in time, t max , and of a distance, x, respectively. Therefore, the uncertainty is estimated to be better than 5 % (cf., e.g., [11]).…”

Section: Overall Thermal Diffusivitymentioning

confidence: 99%

Silicon Thermal Flow-Sensor Semi-ideal Model

2022

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A so-called semi-ideal model has been derived for a pulse-operated MEMS thermal flow sensor by reciprocal numerical mapping of the ideal model of an instantaneous line heat source to the experimental data of the sensor. The novel model not only applies as a precise potential working equation for the sensor but also provides insight into the complete thermal signal transmission chain from the heater to the thermometers of the sensor. It gives answers to prominent peculiarities of the actual heat path of the sensor, prepares ways to improve its design, and offers guidance for a better control of the measuring process. The semi-ideal model was derived in order to replace the so far utilized empirical relations that require multiple calibration measurements. It was found out that the transient temperature profile of the sensor in response to an electrical pulse to the heater is substantially shaped by series thermal conduction of heat. Moreover, it is demonstrated that the impact of the thermal mass of a (practical) line heat source on its transient temperature and released enthalpy can be modeled by considering a virtual cylinder surrounding the source. The same analytical technique also applies for (practical) temperature stations. The findings of the study primarily concern the MEMS sensor. Nevertheless, the presented simple method of numerical mapping can be an effective analytical tool for mathematical modeling by means of numerical data analysis and function evaluation. The concept of a virtual cylinder can help in modeling the dynamics of practical pulsed heating.

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A Versatile Effective Thermal Diffusivity Model for Porous Materials

Carson

2021

Int J Thermophys

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Critical Analysis of Dual-Probe Heat-Pulse Technique Applied to Measuring Thermal Diffusivity

Cited by 10 publications

References 29 publications

Modeling and Measuring Thermodynamic and Transport Thermophysical Properties: A Review

Modeling and Measuring Thermodynamic and Transport Thermophysical Properties: A Review

Silicon Thermal Flow-Sensor Semi-ideal Model

A Versatile Effective Thermal Diffusivity Model for Porous Materials

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