STOCHASTIC ANALYSIS OF SPATIAL INHOMOGENEITY OF CARBON FIBER PAPER REINFORCED THERMOPLASTICS USING MONTE CARLO METHOD
Topic(s) : Material and Structural Behavior - Simulation & Testing
Co-authors :
Peng XUE (JAPAN), Qian GAO , Yi WAN , Jun TAKAHASHI (JAPAN)Abstract :
1 General Introduction
The widespread use of Carbon Fiber Reinforced Plastics (CFRP) in various industries has prompted a shift from deterministic to stochastic evaluation due to their inherent variability. Reliability-based design of composite materials takes full advantage of their properties. As a kind of recycled CFRP, Carbon Fiber Paper Reinforced Thermoplastics (CPT) is noted for its strong mechanical properties and cost-effectiveness, showing promise in sectors like wind energy and automotive manufacturing. This study employs Monte Carlo (MC) methods to assess uncertainties in CPT and examines the effects of spatial variability from meso to macro scales. The resulting stochastic data will support Fast probability integration methods and contribute to reliability-based design optimization for composite structures.
2 Research Method
In this study, the stochastic distribution of carbon fiber orientation and length at the mesoscopic scale is investigated using X-ray techniques. Utilizing the Cox model [1], this work calculates the distribution of the tensile modulus in two principal directions of the sample's plane. To address spatial inhomogeneity, specimens with different moduli distributions in the length, width, and thickness directions are generated employing an MC approach. In the case of CPT laminates, the variability in interlaminar properties is shown to significantly influence the structure's ultimate failure path. Acknowledging this spatial inhomogeneity, the paper employs a three-point bending test as a case study. The finite element simulation of the three-point bending test is calibrated against experimental data, ensuring the accuracy of the deterministic finite element analysis. The experimental setup is illustrated in Fig.1 (a), with a subsequent Fig.1 (b) comparing finite element and experimental results. The Fig.2 shows the detailed process of the strategy.
3 Discussions
The stochastic distribution of specimen responses is determined by FE calculation in an MC approach. This analysis focuses on the ultimate displacement and maximum load of the specimen and examines their correlation with moduli distributions caused by fiber stochastic distribution. The reliability and failure probability of the samples are calculated. Additionally, considering the typical application of CPT materials in conjunction with other materials to create sandwich structures, this study also investigates the responses in specimens composed of carbon fiber weaves skin and CPT core.
The widespread use of Carbon Fiber Reinforced Plastics (CFRP) in various industries has prompted a shift from deterministic to stochastic evaluation due to their inherent variability. Reliability-based design of composite materials takes full advantage of their properties. As a kind of recycled CFRP, Carbon Fiber Paper Reinforced Thermoplastics (CPT) is noted for its strong mechanical properties and cost-effectiveness, showing promise in sectors like wind energy and automotive manufacturing. This study employs Monte Carlo (MC) methods to assess uncertainties in CPT and examines the effects of spatial variability from meso to macro scales. The resulting stochastic data will support Fast probability integration methods and contribute to reliability-based design optimization for composite structures.
2 Research Method
In this study, the stochastic distribution of carbon fiber orientation and length at the mesoscopic scale is investigated using X-ray techniques. Utilizing the Cox model [1], this work calculates the distribution of the tensile modulus in two principal directions of the sample's plane. To address spatial inhomogeneity, specimens with different moduli distributions in the length, width, and thickness directions are generated employing an MC approach. In the case of CPT laminates, the variability in interlaminar properties is shown to significantly influence the structure's ultimate failure path. Acknowledging this spatial inhomogeneity, the paper employs a three-point bending test as a case study. The finite element simulation of the three-point bending test is calibrated against experimental data, ensuring the accuracy of the deterministic finite element analysis. The experimental setup is illustrated in Fig.1 (a), with a subsequent Fig.1 (b) comparing finite element and experimental results. The Fig.2 shows the detailed process of the strategy.
3 Discussions
The stochastic distribution of specimen responses is determined by FE calculation in an MC approach. This analysis focuses on the ultimate displacement and maximum load of the specimen and examines their correlation with moduli distributions caused by fiber stochastic distribution. The reliability and failure probability of the samples are calculated. Additionally, considering the typical application of CPT materials in conjunction with other materials to create sandwich structures, this study also investigates the responses in specimens composed of carbon fiber weaves skin and CPT core.