Polymer composite laminates are preferred in many load bearing applications for its tailorable mechanical properties while offering light-weight solution, corrosive resistance etc. Hence, polymer composites are attractive material choice for aircraft manufacturers to reduce weight and emissions. However, one of the challenges existing in composite laminates is accumulation of damage before final failure, that reduces mechanical properties of the composite laminates during service life. Hence it is crucial to develop a reliable model to predict damage and consequently mechanical properties degradation. The thesis focuses on transverse/intralaminar cracks, that are the first form of damage to appear in off-axis layers of composite laminates when subjected to tensile load and they increase in number with increase in load. Transverse crack growth in numbers was analyzed in terms of transverse crack density (= number of cracks / observed length) growth. Appended papers present methodologies developed using statistical transverse failure stress distribution approach to predict the transverse crack density growth when composite laminates subjected to quasi-static tensile and tension-tension fatigue loading at different temperatures. For that purpose, continuous fibers reinforced polymer composite cross-ply laminates containing different material systems were manufactured, and damage growth was studied in 90-layer in coupon scale specimens. In static tests, the crack density growth in specimens were analyzed against the thermo-mechanical transverse stress in the 90-layer. Distribution of transverse failure stress to initiate a crack along the transverse direction of the layer has been defined using 2 parameter Weibull distribution model. Paper 1 presents, methodology to predict crack density growth, using probability of failure stress distribution (based on Weibull model) in Monte Carlo simulation along with the developed stress distribution model between cracks, in specimens tested at room temperature (RT). The crack density was well predicted in both non-interactive and interactive crack density region using improved Weibull parameter determination routine. The presented Weibull model was extended to address the effect of iso-thermal heat treatment and test temperature in Paper 4. It was observed that both heat treatment and elevated test temperatures, in general, resulted in reduction of transverse cracking resistance. The effect of heat treatment and test temperature on transverse cracking was modelled as Weibull scale parameter dependency using polynomial expression. The developed model was validated against laminates with same material system but with different layups and fiber content.Fatigue tests were performed at different maximum stress levels and at RT and 150℃. Crack density growth was analyzed against number of fatigue cycles. The observed decrease in resistance to transverse cracking with every cycle of load was interpreted as monotonic decrease of Weibull scale parameter. Simple power function with respect to number of cycles was proposed to decrease the scale parameter. Paper 2 presents, fatigue test results at RT and methodology to predict crack density growth in different fatigue stress levels. The methodology, using maximum local transverse stress in a fatigue cycle in Weibull model and the Weibull parameters determined at a reference fatigue stress level, was limited in ability to predict the crack density growth at other stress levels. It was then found that the crack density growth not only depends on maximum local stress in a fatigue cycle, but also on the local stress ratio in the 90-layer, presented in Paper 3. Wherein, an equivalent stress was introduced to replace maximum local stress in Weibull model by addressing the combined effect of maximum local stress in a cycle and also the local stress ratio. Equivalent stress model was validated across different layups and fiber content with same material system. Paper 5 presents fatigue test results at different stress levels and temperatures. It was found that in fatigue tests at 150℃, in spite of lower thermal stress, crack density growth was more rapid than for RT fatigue tests. Methodology to predict crack density growth in 150℃ fatigue tests by combining the analytical model with the equivalent stress and with enhanced test temperature effect has been presented. 

This project aimed to broaden the knowledge of high-temperature polymers and composites when exposed to elevated temperatures and an oxygen-containing atmosphere. The main accent has been on thermosetting polyimide resins reinforced with carbon fibers. When subjected to harsh atmospheric conditions, such as elevated temperatures and oxygen, polymer resins can undergo thermo-oxidative degradation, often resulting in weight loss and a surface layer with altered properties. High-temperature composites could experience such environments during operation. Therefore, it is crucial to understand how exposure to it could affect their performance. To simulate such an environment in the lab, the materials are aged in a controlled manner in a furnace or other equipment. The ageing of polyimide composites in this project was often performed at temperatures at or above 288 degrees Celsius for extended periods of up to 1500 hours.

The first part of the project, and the first article, delved into the effect of different layups and thicknesses of the carbon fiber bundles on the thermo-oxidative behaviour of two composite materials made with the same thermosetting polyimide. Modelling the desorption during the initial stages of the ageing, showed that it exhibited a Fickian behaviour. X-ray computed tomography experiments were used to investigate the ageing behaviour of the materials and revealed that the satin weave composite formed a network of cracks, voids, and delaminations, that progressed with the ageing time, while the damage in the material made of thin plies was in the form of delaminations at the edges. The analysis of the tomographic datasets was performed using Otsu’s thresholding method for semantic segmentation of the defects within the materials.

In an attempt to counter the crack formation on the surface of the satin weave composite observed during the first study, a new polyimide formulation was developed by the manufacturer. The amount of internal crosslinkers was reduced, aiming to increase the toughness of the resin after curing. The second article compares neat resin samples of the original and newly developed formulations with the help of a three-point bending test, differential scanning calorimetry, dilatometry, weight loss, light optical microscopy and nanoindentation experiments. Samples were aged up to 1500 hours in ambient air. The results showed that while there were hints of a slight increase in the fracture toughness of the new formulation, the glass transition temperature had decreased, compared to the original resin.

The two formulations were further investigated and compared with the help of thermogravimetric analysis in the fourth paper. Experiments were performed in isothermal and non-isothermal conditions for more robust results. It was found that the thermal oxidation of the two materials follows an autocatalytic model. The study highlights the importance of using both isothermal and non-isothermal data in the pursuit of more precise and robust analysis and modelling of the thermal oxidation of high-temperature polymers. Based on the results, a diagram, predicting the weight loss at specific times and temperatures, was created for each material.

An alternative way of studying crack formation within challenging polymer composite tomographic datasets was presented in the fourth article. Instead of using a thresholding method, such as the

previously used Otsu’s in the first study, in this case, a deep learning model was applied to the datasets to follow the progressive micro-cracking within the composite during a series of thermo-mechanical loadings. In contrast to a global thresholding method, which segments all defects within the dataset, the deep learning model, Attention U-Net, made it possible to create a more straightforward and robust way of performing segmentation on transverse cracks. The model was compared to and outperformed both Otsu’s method and a conventional U-Net.

The previously developed methodology for semantic segmentation and the obtained results on transverse cracks were applied in a practical case in the fifth article, where the developed damage prediction model assumes that transverse cracks in thick plies span through the whole width of the specimen. The tomography and deep learning methodology helped shed light on the nature of the cracks and showed that previous assumptions, based on edge observation with light optical microscopy, should be taken as a conservative estimation.