Abstract
The objective of this paper is to present methodology of the precise and reliable determination of thermal diffusivity and linear coefficient of thermal expansion of the photoacoustic signal recorded (obtained) using open photoacoustic cell where thickness of the sample served as a control parameter. The methodology was based on the application of neural networks that were trained on numerical experiments and optimized by adding Gaussian noise to the training base that corresponded in percentage to maximum measurement uncertainty. By comparing the predictions of the neural network with theoretical fitting curve for experimental results for the aluminum sample that was 197 μm thick, it was shown that the proposed methodology achieves high precision in the determination of thermoelastic and geometrical properties of the sample.
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