Automated Fiber Placement (AFP) frequently introduces triangular gap defects during the manufacture of double-curved composite fuselage panels, which significantly degrade structural mechanical performance. Most existing studies adopt idealized defects on flat plates, which cannot reflect trajectory deviations and complex defect morphologies in real engineering components. This study proposes a trajectory- informed finite element analysis (FEA) modeling approach according to practical AFP trajectory variations in engineering scenarios. Via Python scripting, the approach achieves automatic mapping from AFP trajectories, defect data, and material properties to finite element meshes. It can address the analytical method challenge of how deviations arising from arbitrary trajectory design during actual AFP affect structural performance. Meanwhile, the mechanical property effects of such realistic irregular triangular gap defects in double-curved fuselage panel are systematically investigated in combination with experimental tests. Tensile tests on curved specimens extracted from full-scale panels demonstrate that triangular gap defects induce significant stress concentration and load path distortion, leading to a 10.8
Geometric deviations and forced fitting during the assembly of carbon fiber-reinforced polymer (CFRP) structures induce severe local stress concentrations, limiting the mechanical performance and reliability of composite parts. To address this quantitative evaluation bottleneck, this work develops a coupled framework integrating three-dimensional digital image correlation (3D-DIC) and physics-informed neural networks (PINNs), to reconstruct full assembly stress fields and synergistically estimate effective orthotropic elastic parameters using surface optical measurements for thin-to-moderately thick CFRP laminates under quasi-static linear elastic assembly conditions. The internal through-thickness stress distribution is extrapolated via continuum mechanics constraints rather than directly measured, under the assumed linear-elastic orthotropic constitutive model. In the proposed pipeline, coded circular targets unify raw DIC speckle point clouds into a consistent material reference coordinate frame. By embedding orthotropic constitutive laws and static equilibrium partial differential equations (PDEs) into a multi-objective weighted loss function, the network simultaneously estimates macroscopic in-plane orthotropic constants while providing physically-regularized out-of-plane parameter estimations through continuum constraints across the full structural thickness. The framework is validated via compression-fit assembly tests on an industrial CFRP stiffened panel. Surface strain predictions are cross-checked against discrete strain gauge measurements, while internal and back-surface reconstructed stress fields are benchmarked against a co-calibrated Abaqus finite element (FE) model for internal physical consistency. The coefficients of determination (R-squared) of dominant stress components all exceed 0.99, with global relative L2-norm errors controlled below 6.6
This study investigates the effect of embedded circular defects with varying sizes and locations on the compressive properties of twill-woven carbon fiber reinforced composites. Composite laminates with dimensions of 150 mm × 100 mm × 4 mm were fabricated using the prepreg stacking and hot-press curing. Circular defects with diameters ranging from Φ 10 mm to Φ 50 mm were introduced at different through-thickness locations, including single (1/2, 1/4) and combined locations (e.g., 1/2 1/4, 1/2 1/4 1/8). To predict the compressive strength and modulus under complex defect conditions, an artificial neural network (ANN) model was developed using four input features: defect diameter and multi-label binary spatial encoding defect location. The ANN model achieved high prediction accuracy with a coefficient of determination (R2) exceeding 0.94 on the strictly withheld independent test set evaluating single-plane defect scale interpolation, demonstrating its capability to capture the non-linear relationship between embedded damage characteristics and mechanical response. Results indicate that both defect size and location significantly influence compressive performance, and the combined presence of multiple defects introduces non-additive degradation effects. This work provides a practical data-driven framework for evaluating the residual compressive performance of twill-woven CFRP laminates within the verified material and geometric boundary envelopes.
The consequences of long-term immersion in a natural marine environment of unidirectional flax / PolyPropylene + Maleic Anhydride grafted PolyPropylene (PP + MAPP) composites were compared with those of ageing in deionized water containing a biocide in laboratory conditions (20 °C and 40 °C). The mechanical properties under tensile loading, microstructure evolution and mass and density variation were studied over time. The drop in the mechanical properties of samples immersed in seawater is much greater than that of samples aged in the laboratory with biocide. This difference is consistent with degradation of the flax fibers potentially associated with biological colonization by fungi and bacteria. SEM observations confirmed the presence of biological colonization within the biocomposites, but the relative contributions of abiotic and biotic processes were not quantified in this study. Therefore, natural seawater ageing tests should consider both abiotic and biotic mechanisms to accurately describe the overall degradation processes occurring during the biocomposite lifetime. The mechanisms observed highlight the need to reassess protocols for accelerated ageing tests and to develop complementary experiments to determine the contributions of both biological and non‑biological factors.
Lattice structures have great potential for lightweight load-bearing and energy absorption applications, but sharp-cornered nodes in traditional composite lattices can cause abrupt changes in fiber paths and local manufacturing defects. To address this issue, this study proposes a symmetric double-corrugated lattice design strategy. Using TCL as the control, three corrugated lattices, namely SCL, CCL and PCL, are designed and manufactured through a modular orthogonal assembly method. Micro-defect characterization, quasi-static crushing tests and finite element simulations were combined to investigate the effects of corrugation geometry on manufacturing quality, crushing response, energy absorption and failure modes. The results show that the symmetric double-corrugated design improves fiber-path conformity, reduces defect concentration near sharp-cornered nodes and promotes a transition from localized failure to progressive crushing. Compared with TCL, SCL increases the average crushing load, specific energy absorption, and crushing force efficiency by 16.47
