B5.2 - Analysis of front side dynamics in laser flash analysis: modeling and adjustment for enhanced thermophysical insights

Event
22. GMA/ITG-Fachtagung Sensoren und Messsysteme 2024
2024-06-11 - 2024-06-12
Nürnberg
Band
Vorträge
Chapter
B5 - IRS2 Teil III
Author(s)
A. Narymany Shandy, M. Zipf - Technische Hochschule Würzburg-Schweinfurt,Würzburg, J. Manara, F. Hemberger, J. Hartmann, T. Stark - Center for Applied Energy Research,Würzburg
Pages
200 - 203
DOI
10.5162/sensoren2024/B5.2
ISBN
978-3-910600-01-0
Price
free

Abstract

The Laser Flash Analysis (LFA) has established itself as a reliable method for determining the thermal diffusivity of materials. In order to expand the measurement range of LFA, the investigation of the temperature development on the surface of the sample facing the laser, referred to as the front side, comes into focus. Initially, an adiabatic front-side model is applied. This model provides a fundamental approximation of the temperature distribution on the front side of the sample. To account for the high dynamics of the front-side temperature caused by the pulsed energy input of the laser, modification of the evaluation models is necessary. In this regard, the temporal evolution of the front-side temperature caused by a Dirac shaped energy input is convoluted with laser pulses of different shapes. This convolution enables a detailed investigation of the effects of various laser pulse shapes on the temperature evolution on the front side. Not only the maximum temperature is considered, but also the temporal evolution of the temperature. The choice of laser pulse shape proves to be a critical aspect, as it significantly influences the response signal of the front side. Two different convolution methods are compared using numerical solution. On one hand, convolution by multiplication in the Fourier domain using Fast Fourier Transformation followed by inverse transformation, and on the other hand, an analytical solution through the convolution integral. Both resulting curves are tested for their robustness and applicability through parameter variations.

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