مطالعه عددي رشد آسيب پيشرونده در كامپوزيت‌هاي خود-ترميم شونده مبتني بر الياف توخالي

One of the biggest problems with composite materials during operation is the formation and growth of microcracks within them. The growth of these microcracks and their coalescence can lead to the failure of the composite structure. To address this issue, researchers, especially in recent years, have made significant efforts to develop self-healing materials that can repair the generated cracks and prevent the failure of the entire component. Various tests, such as the TDCB and DCB tests, have been designed to eva‎luate the effectiveness of the repair in these materials. In this research, the finite element modeling of the TDCB and DCB tests using self-healing composites was investigated based on the damage growth pathways. For this purpose, zero-thickness elements were embedded in the predicted crack growth paths, and properties and damage parameters were assigned to them according to the bilinear traction-separation equations. Subsequently, initial loading on the models was performed, and the results of damage growth were reported. After that, by replacing the damaged elements with healthy elements with new properties, the repair behavior in these types of composites was predicted. Finally, by modifying the diameter and spacing of the vessels, the impact on the maximum force and fracture energy was reported. The results from the TDCB sample indicate that as the diameter of the vessels decreases from 0.9 to 0.1 millimeters, the maximum force increases by 25 percent. Additionally, with a reduction in the spacing of the vessels from 5 to 5.1 millimeters, the maximum force decreases by up to 5 percent. Furthermore, the results from the DCB sample show that there is a significant increase in the rate of strain energy release in the samples with an increase in the diameter of the hollow vessels. Thus, with an increase in the diameter of the vessels to 680 micrometers, the rate of strain energy release is reported to be 790 joules per square meter, representing an increase of over 50 percent compared to the standard sample.

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