In chopped carbon fiber tape reinforced thermoplastic（CTT）material, the anisotropic region of fiber orientation after press molding often causes the degradation of mechanical properties and damage and fracture. This study explores means of obtaining the fiber shape and fiber orientation tensors from molded products and then predicting the CTT mechanical properties and damage fracture locations. Extensive fiber shape data obtained by X-ray CT image processing are analyzed using a simple method to create a fiber waviness model.The fiber orientation tensor of the molded product is obtained through X-ray phase imaging. The material properties of a finite element model with CTT are calculated and mapped from the fiber waviness model and orientation tensor, and damage fracture prediction is simulated. Results showed that the fracture positions of both the test and simulation agreed in specimens having large anisotropic regions. However, the specimens with small anisotropic regions did not match. Therefore, the images of strain distribution of the test piece under a tensile load were compared by cross-correlation. Results showed a large correlation between the tensile test and simulation results, thus confirmed the effectiveness of the simulation.
In this study, a variational stress analysis was performed on a laminate that contained regions with varying material properties in the loading direction. Investigation of material properties and damage behavior of laminates with fiber discontinuity (resin-rich region) has been the main motivation for this study. The analysis considered an arbitrary number of regions with different material properties. For simplicity, we assumed a plane stress condition or stress distribution, we assumed that the normal stress in the loading direction was constant along the direction of thickness in each ply. The admissible stress state that satisfied both equilibrium and boundary/continuity conditions was constructed with unknown functions that were determined using the principle of minimum complementary energy. The analysis was applied to laminates with single fiber discontinuity and with distributed fiber discontinuities. These results were compared using finite element analyses, which obtained good agreement. The results show the validity of this analysis, which can be used to investigate the effects of fiber discontinuity on the laminate mechanical properties and damage behavior in laminates with fiber discontinuities.
To predict the moisture desorption behavior of a composite structure in outer space, it is necessary to know the through-thickness distribution of moisture absorption rate in the composite material at the time of launch. However, it is impossible to identify the moisture distribution state by measuring the weight change of the assembled large-scaled structure. In this study, we proposed a method for estimating the moisture distribution state of a composite space structure from the information obtained during the moisture desorption test of a witness sample, which had the same moisture distribution as the target structure as it was exposed to the same hygrothermal environment. We used physics-informed neural network (PINN), a neural network with physics-based constraints, for estimation. This neural network model takes time and through-thickness location as input and returns the local moisture concentration. PINN trains the model by enforcing that the output of the network fulfills the diffusion equation and the change in moisture content during the moisture desorption test of the witness sample. First, a numerical experiment using finite element analysis was performed to confirm the effectiveness of the proposed approach. Furthermore, a demonstration experiment was conducted using carbon/epoxy laminates to confirm the practicality of the method.