A new methodology for thermoelastic model identification in composite materials using digital image correlation

Official URL: http://dx.doi.org/10.1016/j.optlaseng.2021.106689

Local strain measurement techniques, such as strain gauges or extensometers, have been broadly utilized as input data source for thermoelastic effect model identification in fiber-reinforced polymers, despite their well-known high heterogeneity. This experimental setup strongly limits the possibility of assigning thermoelastic models in a local-based manner for posterior Thermoelastic Stress Analysis. This issue has been addressed herein through proposing a novel method for spatial identification of thermoelastic models in composite structures using full-field experimental measurements. The proposed concept is validated by conducting tests on laminated tensile coupons with various stacking sequences. To this end, the displacements and thermal data collected from Digital Image Correlation and infrared camera, respectively, are interpolated to a mutual background mesh using a Smoothing Element Analysis. It is shown that this procedure results in a continuous strain field and a reconstructed thermal map for the laminate domain at various loading stages. The resulting smoothed strain map is used as the input for three different thermoelastic models, followed by a comparison of the calculated analytic temperature variations for each model against the infrared camera’s measurements. The relative error associated to this model assignment process is underlined, and it is revealed a significant effect of material properties variability in the accuracy of the method. It is shown that the proposed methodology can circumvent inaccuracies of the conventional Thermoelastic Stress Analysis method, while providing a viable and computationally efficient method for the selection of appropriate thermoelastic models at the local level.