Prediction of Thermal Exposure and Mechanical Behavior of Epoxy Resin Using Artificial Neural Networks and Fourier Transform Infrared Spectroscopy

Abstract

Thermal degradation detection of cured epoxy resins and composites is currently limited to severe thermal damage in practice. Evaluating the change in mechanical properties after a short-time thermal exposure, as well as estimating the history of thermally degraded polymers, has remained a challenge until now. An approach to accurately predict the mechanical properties, as well as the thermal exposure time and temperature of epoxy resin, using Fourier-transform infrared spectroscopy (FTIR)-spectroscopy, data processing, and artificial neural networks, is presented here. Therefore, an epoxy resin has been fully cured and exposed to elevated temperatures for different time periods. A FTIR-spectrometer was used to measure molecular changes, using mid-IR (MIR)-FTIR for film samples and near-IR (NIR)-FTIR for bulk samples. A quantitative analysis of the thermally degraded film samples shows oxidation, chain-scission, and dehydration in the FTIR spectra in the MIR-range. Using NIR spectroscopy for the bulk samples, only minor changes in the FTIR spectra could be detected. However, using data processing, molecular information was extracted from the NIR range and a degradation model, using an artificial neural network, has been trained. Even though the changes due to thermal exposure were small, the presented model is capable of accurately predicting the time, temperature, and residual strength of the polymer.

Durability of Externally Bonded Fiber-Reinforced Polymer Composites in Concrete Structures: A Critical Review

“…During their service, EB FRP systems are exposed to a variety of environmental conditions, many acting simultaneously. High humidity, elevated temperature, freeze-thaw cycles, UV radiation, and de-icing agents can affect the performance of an EB FRP strengthening system [ 36 , 37 , 38 , 39 ]. So far, the effect of these exposure conditions has been mostly studied in laboratory environment using accelerated testing.…”

Flow Characteristics, Mechanical, Thermal, and Thermomechanical Properties, and 3D Printability of Biodegradable Polylactide Containing Boehmite at Different Loadings

“…The H-O-H peak at 1630 cm −1 was not obtainable from the processed PLA, due to the existence of thermal chain scission at the C-O bond [26]. Supplementary Figure S3 shows the vibrations at 2852 and 3000 cm −1 assigned to the O-H stretching, and 2922 cm −1 due to the axial C-H stretching bond [27]. The FTIR spectra of neat BA (Supplementary Figure S4a) reveal that the vibrations at 3309 and 3095 cm −1 relate to the O-H stretching of BA [28].…”

Predicting Delaminations and Residual Strength of Carbon Fibre Reinforced Polymers (CFRP) After One-Sided Thermal Loading by Means of Infrared Spectroscopy

“…Furthermore, IR spectral data can be used to predict properties of CFRP by means of multivariate data analysis. Regression methods like, e.g., principal component regression, partial least square regression (PLS), or artificial neural networks are suitable to predict residual strength as well as storage time and temperature of CFRP after isothermal treatment [24][25][26][27][28]. Wolfrum et al developed a PLS-model for the prediction of ILSS based on surface spectra for CFRP after one-sided thermal laoding at 50 kW/m 2 [11].…”