Determination of Thermal Parameters using Thermography and Data Assimilation and its Application to the Convective Heat Transfer Coefficient

Abstract This paper presents a method to determine thermal parameters, which can neither be calculated analytically nor measured directly. Specifically, the convective heat transfer coefficient is discussed, which is usually determined using empirical models, namely the Nusselt correlations. To overcome the lack of information about the relation between temperature and parameters, the methodology of data assimilation is applied. Therefore, a dynamic model is combined with measurement data from a thermography experiment avoiding interference with the actual process enabling inline parameter identification. The method is first applied on artificially created simulation data and second on real measurement data. This paper shows that the developed method estimates the heat transfer coefficient in agreement with the well-known Nusselt correlations. Moreover, the present work compares different estimation strategies and gives a recommendation regarding state-parameter, pure parameter or combined estimation, including a detailed analysis of the variation of a smoothing parameter.

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Publication Details

Journal
Journal of Nondestructive Evaluation
Published
2025-09-01
DOI
https://doi.org/10.1007/s10921-025-01259-w
Primary Topic
Radiative Heat Transfer Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Determination of Thermal Parameters using Thermography and Data Assimilation and its Application to the Convective Heat Transfer Coefficient

G. Mayr, Philipp Zallinger, Karin Nachbagauer
Journal of Nondestructive Evaluation
Radiative Heat Transfer Studies
article

Determination of Thermal Parameters using Thermography and Data Assimilation and its Application to the Convective Heat Transfer Coefficient

G. Mayr, Philipp Zallinger, Karin Nachbagauer
article en

Abstract

Abstract This paper presents a method to determine thermal parameters, which can neither be calculated analytically nor measured directly. Specifically, the convective heat transfer coefficient is discussed, which is usually determined using empirical models, namely the Nusselt correlations. To overcome the lack of information about the relation between temperature and parameters, the methodology of data assimilation is applied. Therefore, a dynamic model is combined with measurement data from a thermography experiment avoiding interference with the actual process enabling inline parameter identification. The method is first applied on artificially created simulation data and second on real measurement data. This paper shows that the developed method estimates the heat transfer coefficient in agreement with the well-known Nusselt correlations. Moreover, the present work compares different estimation strategies and gives a recommendation regarding state-parameter, pure parameter or combined estimation, including a detailed analysis of the variation of a smoothing parameter.

Journal of Nondestructive EvaluationVol. 44(4)
University of Applied Sciences Upper Austria (AT), Institute for Advanced Study (DE), Technical University of Munich (DE)
Austrian Science Fund, Österreichische Forschungsförderungsgesellschaft, Technische Universität München
Openalex Percentile: Top 75%
Radiative Heat Transfer Studies
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