Analysis of transverse cracking in cross-ply laminates: Weibull distribution based approach

Fiber reinforced polymer composite laminates make up more than 50% of modern aircrafts. Such composite laminates are exposed to various environmental and in-service thermo-mechanical load conditions. Transverse/intralaminar cracking is usually the first form of damage appears in a composite laminate and they tend to increase in number during the service life. The growth in number of these cracks significantly degrades the thermo-elastic properties of the composite laminate and eventually leads to final failure. Thus, it is important to predict the crack density (number of cracks per unit length) growth in both non-interactive crack density region and interactive crack density region and its effect in thermo-elastic properties degradation. Non-interactive crack density region is the region where the cracks are far apart and stress perturbation between cracks do not overlap. Interactive crack density region is where the cracks are close to each other and stress perturbation between cracks overlaps and affects the formation of new cracks. In this study, transverse cracks in thick Glass Fiber Epoxy (GF/EP) cross-ply composite laminates under quasi-static tensile loading and tension-tension fatigue loading have been analyzed and predicted. In the first paper attached here, increase in number of transverse cracks in GF/EP cross-ply laminates under quasi-static tensile loading at room temperature (RT) are analyzed using 2 material systems. The failure stress distribution in 90° plies of the laminates is defined by Weibull distribution and the Weibull parameters are determined from crack density versus applied thermo-mechanical transverse stress in 90° layer (σTCLT) data points within the non-interactive crack density region. The crack density growth is then predicted versus the σTCLT and applied mechanical strain in the laminate from the determined Weibull parameters using Monte Carlo method and the stress distribution models between adjacent cracks. The predicted results using the novel stress distribution model introduced here were in good agreement with the non-interactive and interactive crack density regions of test results. The importance of using the Monte Carlo method and novel stress distribution model to predict the whole crack density region have been emphasized in the article, in addition to that it also redefined the interval of non-interactive crack density region. The second paper expands the concept from the first paper, to address the tension-tension fatigue loading at RT. It deals with the crack density analysis and prediction in [0/90]s GF/EP laminate under fatigue loading at RT. The fatigue tests were performed at 3 maximum stress levels. Here the Weibull parameters were determined from the data points within the non-interactive crack density region in quasi-static and fatigue loading. From the determined Weibull parameters of each stress level and using Monte Carlo method and the novel stress distribution model, the crack density versus the number of fatigue cycles were predicted and in good agreement with the fatigue test results at the respective stress level. The intention here was to use Weibull parameters of one stress level to predict crack density at arbitrary stress levels. Based on it, the predicted results were not sufficiently good and suggested to revisit the Weibull parameter determination by performing fatigue tests at two stress levels. In the attached paper 3, new methodology on crack density growth simulation and Weibull parameter determination in tension-tension fatigue loading has been developed. In the newly developed methodology, in detailed fatigue tests are performed at one maximum stress level to obtain all data points and at higher stress level to obtain one data point that is a crack density data point at certain number of cycles to determine Weibull parameters. Using the determined Weibull parameters from non-interactive crack density region, the whole crack density region was successfully predicted for other stress levels