纤维束增强复合材料的双层次随机扩大临界核模型

针对纤维束增强复合材料,提出了双层次随机扩大临界核模型。以复合材料制造工艺为基础建立了纤维间距和纤维束中纤维根数的计算模型,将复合材料中的纤维分为2个层次:纤维束和纤维束群,并提出父核和子核的概念对临界核的构成进行了区分,用Beyerlein公式计算纤维束群中纤维束相继失效引起的纤维束的平均应力集中因子,用Sivasambu公式来计算纤维束中纤维相继断裂造成的纤维的应力集中因子。然后,以纤维断裂蔓延的主要模式为基础,将逐渐增大的无效长度引入纤维束内部,根据统计学理论推导相应的复合材料破坏概率计算公式。编制了相关程序,通过该程序分别预测了S玻纤、E玻纤、玄武岩纤维无捻单向纤维布增强复合材料试件的拉伸强度。对3种复合材料板进行了拉伸强度及基体的拉伸和剪切实验,并对比了预测结果与实验结果。研究结果显示,直接将实验对象的材料、几何参数代入就能得到与实验结果吻合的预测结果。

Strength prediction for unidirectional FRP based on the theory of two-leveled randomly enlarging critical core

The theory of two-leveled randomly-enlarging critical core was put forward to predict the tensile strength of unidirectional bundle-reinforced composites. According to the manufacture technologies of FRP, a model was established to calculate the fiber spacing and the quantity of fibers in a bundle. The fibers in composites were treated through 2 levels: fiber bundle, and array of fiber bundles. The father core and son core were put forward so as to precisely describe the structure of a critical core. Beyerleinps formula was adopted to calculate the average stress concent ration factor of the bundle, which is caused by the sequential failure of bundles. Sivasambups formula was applied to calculating the stress concentration factor of the fiber inside bundle, which is caused by the sequential failure of fibers. Based on the propagation mode of fiberps failure, according to the statistics theory, considering the enlarging ineffective length inside the bundle, the formulas calculating the failure possibility of composites were deduced. A computer program was compiled. Through this program, the tensile strengths of plastics reinforced respectively by unidirectional woven rovings of S glass, E glass, and Basalt fiber were predicted. Meanwhile, along with the mechanical performance of the matrix under tension and shearing, the tensile strengths of these FRPs were gained through experiments. Then , the predicted result s were compared with the experiment results. Research result shows that the predicted results, which meet the experiments, can be gained by directly inputting the material and geomet ry parameters of experiment specimens.