Fund Project:Project supported by the Fundamental Research Fund for the Central Universities, China (Grant No. 2020ZDPYMS31)
Received Date:10 February 2021
Accepted Date:06 May 2021
Available Online:30 September 2021
Published Online:20 October 2021
Abstract:Defects that exist inside composites have an important effect on the tensile fracture properties of composites. The fiber bundle model is a theoretical model commonly used to study the tensile fracture properties of disorder materials. Existing work on fiber bundle models with single fiber defects shows that after single fiber defects are introduced into the fiber bundle model, the defects have a significant effect on the tensile fracture properties of the model. Since there are more complex microscopic defect structures in actual materials, such as voids, gaps, impurities, dislocations, micro-cracks, etc, it is necessary to build a multi-size defect model. In order to study the defects of different sizes and damage degrees existing in actual materials, the spatial size of the defect, the degree of defect and the distribution of fiber damage levels within the defect and other influencing factors are introduced to construct an extended fiber bundle model with cluster shaped defects. For the model, it is first assumed that the degree of defect of the fiber inside each cluster decays linearly from the center to the outside in two spatial attenuation forms: exponential decay and constant degree of defect. In the fiber bundle model of this cluster-shaped defect, the two most important factors are the number of defects α and the upper limit of defect size β. The numerical simulation method is used to analyze the influence of the number of defects, the upper limit of defect size, and spatial distribution of degree of defective fibers inside defect on the macroscopic mechanical properties and statistical properties of fracture when the model is subjected to quasi-static load borne under the nearest neighbor stress redistribution. Through the simulation analysis, it is found that owing to the overlapping competition mechanism of the defect spatial distribution, when the upper limit β of the defect size is large, the influence of the number of defects on the system load capacity trends to saturation. Since the defect degree of the defect center fiber is proportional to the defect size, with the upper limit β of the defect size increasing, its influence on the load capacity of the model becomes more and more significant. When large size defects exist, even if the number of defects is small, the load bearing performance of the material will be significantly reduced. The spatial distribution function of the damage degree of fiber inside the defect has no substantial influence on the above rules, and only changes the specific value of each fracture property. The simulation analysis results in this paper have certain theoretical significance in improving the mechanical properties of composite materials. Keywords:fiber bundle model/ defect/ constitutive relation/ avalanche size
其中$\gamma > \beta $是决定中心缺陷程度的控制变量. 如图1所示, 以缺陷中心为坐标零点建立直角坐标系. 在缺陷内部不同纤维的缺陷程度与其位置之间满足一定的函数关系, 本文首先采用了简单的线性衰减函数关系. 如图1所示, 假设第i个缺陷内部, 以缺陷中心为计数基准, 第$j~(j \leqslant {\beta _i}/2)$根纤维的初始阈值记为${x_j}$, 引入缺陷后其断裂阈值$x_j^*$表示为 图 1 一维纤维束模型的团簇状缺陷程度示意图 Figure1. Schematic diagram of cluster defect degree for one-dimensional fiber bundle model. The Cartesian coordinate system is established with defect center as its coordinate zero.
3.缺陷个数α对断裂过程的影响缺陷个数α表示了纤维束中缺陷的多少, 为了单独分析缺陷个数α对模型拉伸断裂性质的影响, 首先固定缺陷尺寸上限β的值. 在本模型中, 考虑到系统的尺寸以及实际材料出现缺陷的情况. 一般情况下, 缺陷尺寸相比系统的尺寸来说要小得多, 因此β不应太大; 另外, 在以往的研究中, 我们已经分析了β = 1的极限情况, 当β太小时, 模型趋向于β = 1时的极限情况, 团簇状缺陷结构不明显, 因此, β取值也不应太小. 在以下的模拟中, 首先固定β = 150, $\gamma = 200$, 考虑缺陷个数α在50—3200之间变化, 分析缺陷个数α对断裂性质的影响. 图3给出了模型在拉伸断裂过程中本构曲线与缺陷个数α的关系, 横坐标$\varepsilon $表示应变, 纵坐标$\sigma $表示应力, 其中缺陷尺寸上限β固定为150. 从图3可以看出, 虽然模型中每一根纤维都具有脆性断裂性质, 但整体上本构曲线在断裂阶段还是表现出一定的非脆性断裂性质. 由于模型中各纤维的断裂阈值分布存在着涨落, 使得每次模拟得到的临界应变和临界应力也存在涨落, 在最后模拟结果中, 进行系综平均后就呈现出一定的非脆性断裂性质, 在达到临界应力之后, 应力并没有立即降为0. 不同缺陷个数α下的本构曲线在临界断裂前基本上是重合的, 在接近临界断裂时稍有变化. 对拉伸断裂过程的应力应变关系来说, 初始阶段的本构曲线主要由断裂阈值较小的纤维的阈值分布决定, 而缺陷对纤维束中纤维断裂阈值中较小阈值的分布影响较小. 由于在不同的缺陷个数取值下, 纤维断裂阈值分布中较小阈值的分布均近似符合均匀分布, 因此, 缺陷个数取值对模型拉伸断裂的本构曲线初始阶段几乎没有产生影响. 缺陷个数α对纤维束断裂力学性质的影响不是线性的, 在缺陷个数α较小时, 对本构关系的影响比较明显; 而当缺陷个数α取值较大时, 对本构关系的影响反而较小, 接下来定量分析缺陷个数α对临界应力大小的影响. 图 3 不同缺陷个数α下系统的本构关系, α在50—3200的范围内变化, 图中$\varepsilon $表示应变, $\sigma $表示应力 Figure3. Constitutive curves of the system under different number of defects α, α varies from 50 to 3200. In the figure, $\varepsilon $ represents strain and $\sigma $ represents stress.
图4为临界应力σc与缺陷个数α的关系曲线, 其中缺陷尺寸上限β为固定值150. 从图中不难发现, 临界应力随着缺陷个数的增加单调地减小, 当缺陷个数比较小时临界应力随缺陷个数的变化比较明显, 而当缺陷个数增加到相对较大数值时, 临界应力的减小则缓慢得多. 值得注意的是, 模拟中采用了相对较大的缺陷尺寸, 也就是说即使在缺陷数目比较少的情况下, 大尺寸缺陷的出现仍然会对临界应力造成较大的影响. 而且由于缺陷数目比较小, 缺陷的空间分布比较分散, 缺陷之间重叠的情况很少. 因而纵向上不同缺陷程度的竞争作用不强, 此时少数的大尺寸缺陷会对系统的力学性质产生较大的影响. 而当缺陷数目增加到较大值的时候, 缺陷之间将出现较多的重叠, 纵向上缺陷程度的竞争变得激烈, 使得最终缺陷纤维根数和缺陷数目不成正比, 因此对系统力学性质的影响趋于平缓. 为了进一步说明这一点, 减小缺陷尺寸, 将缺陷尺寸上限设定为β = 40, 模拟结果如图4插图所示. 这样在保持缺陷个数的变化区间不变的情况下, 由于缺陷的尺寸较小, 缺陷的重叠可以忽略不计, 也就是纵向上缺陷程度的竞争现象不明显, 此时缺陷纤维的根数和缺陷数目近似呈线性关系, 表现在模拟结果上就是临界应力与缺陷数目之间近似呈线性关系. 以上模拟结果也说明, 减小缺陷尺寸使得模型从团簇状缺陷向非团簇状孤立缺陷转变, 在接下来的分析中将根据最大雪崩尺寸和负载加载步数的变化情况讨论团簇状缺陷模型和非团簇状缺陷模型的区别. 图 4 临界应力随缺陷个数α的变化关系, 插图为β = 40时临界应力随着缺陷个数α的变化关系, 此时临界应力接近于线性变化 Figure4. Relationship between critical stress and the number of defects α. In the inset, the relationship between critical stress and the number of defects α with β = 40 is shown, at this time, the critical stress changes linearly with α.
在团簇状缺陷模型中, 最大雪崩尺寸${\varDelta _{\text{m}}}$和负载加载步数step随着缺陷个数α呈现相反的变化关系. 如图5所示, 缺陷个数从50个逐渐增加到3200个, 最大雪崩尺寸和负载加载步数均呈非单调变化, 在缺陷个数为400附近, 最大雪崩尺寸和负载加载步数都出现了极值. 当缺陷个数从50增加到400时, 最大雪崩尺寸逐渐增加, 相应的负载加载步数逐渐减少, 系统更容易在经历少数大尺寸雪崩后发生宏观断裂. 而当缺陷个数由400继续增加时, 最大雪崩尺寸开始减少, 而负载加载步数则开始增加, 此时, 系统具有更强的韧性, 在拉伸过程中更不容易发生脆性断裂. 缺陷个数等于400是一个极值点, 此时, 系统具有最小的负载加载步数, 同时最大雪崩尺寸取最大值, 说明此时系统最接近于脆性断裂. 而当缺陷个数大于400时, 随着缺陷个数增加, 虽然临界应力单调减小, 但是减小的速度降低了. 另一方面, 负载加载步数反而增加了, 说明系统虽然能够承担的负载有所下降, 却具有更强的韧性. 需要注意的是, 以上结果只是在β = 150条件下模拟得到的, 对应了缺陷尺寸比较大的情形. 为了详细分析极值出现的条件, 又针对不同β值进行了数值模拟. 如图6所示, 模拟得到了不同β取值下, 最大雪崩尺寸和负载加载步数随缺陷个数的变化关系, 其中图6(a)—图6(d)分别对应β = 120, 90, 70, 60. 图 5 最大雪崩尺寸${\varDelta _{\text{m}}}$和负载加载步数step随着缺陷个数α的变化, 在α = 400处最大雪崩尺寸和负载加载步数均出现极值 Figure5. The maximum avalanche size (${\varDelta _{\text{m}}}$) and the step number of load increase (step) vary with the number of defects. The maximum avalanche size and the step number of load increase reach the extreme value at α = 400.
图 6 不同β取值下的最大雪崩尺寸和负载加载步数极值的出现情况 (a) β = 120; (b) β = 90; (c) β = 70; (d) β = 60. 当β取值较大时最大雪崩和加载步数与缺陷个数α存在类似二次函数的关系 Figure6. The extreme values of the maximum avalanche size and the step number of load increase with different β: (a) β = 120; (b) β = 90; (c) β = 70; (d) β = 60. When the value of β is large, there is a similar quadratic function between the maximum avalanche, the step number of load increase and the number of defects α.
固定缺陷尺寸上限和缺陷个数的情况下, 缺陷程度空间衰减方式分别为线性、指数和常数函数时, 临界应力随着中心缺陷程度的变化如图12所示. 在三种空间衰减方式下, 临界应力随着中心缺陷程度的减小均单调增加. 同时也能发现, 不同的缺陷程度空间衰减方式下, 临界应力随中心缺陷程度都有类似的变化规律. 但是空间衰减方式采用指数函数和常数函数的模型其临界应力的变化曲线很接近, 说明不但变化规律一致, 具体的临界应力数值也足够地近似, 而采用线性衰减方式的模型其临界应力会显著大于另外两种形式. 在三种空间衰减方式下, 临界应力随着中心缺陷程度的减小逐渐出现饱和的趋势, 当缺陷中心的缺陷程度足够小时, 即使缺陷个数和尺寸很大也不会对系统造成显著的影响. 类似的规律也出现在最大雪崩尺寸和负载加载步数随中心缺陷程度的变化关系中. 如图13所示, 最大雪崩尺寸随着中心缺陷程度的减少而减小, 而负载加载步数则正好相反. 这说明减少中心缺陷程度, 断裂过程中的负载加载步数增加, 延缓了宏观断裂发生的进程. 而相应地两次负载加载之间所能够断裂的纤维根数, 也就是雪崩尺寸减小了, 同时最大雪崩尺寸也变小了, 说明系统的断裂进程相应延缓了. 在三种空间衰减方式下, 最大雪崩尺寸和负载加载步数随着中心缺陷程度的减小逐渐出现饱和的趋势, 当缺陷中心的缺陷程度足够小时系统受缺陷的影响很小. 中心缺陷程度和缺陷尺寸之间都是单调的变化关系, 因此, 中心缺陷程度和缺陷尺寸上限对断裂性质具有类似的影响关系. 图 12 缺陷程度空间衰减方式分别为线性、指数和常数函数情况下的中心缺陷程度对临界应力的影响, 缺陷个数为800, 缺陷尺寸上限为150 Figure12. The influence of the degree of central defect on the critical stress when the spatial attenuation modes of the defect degree are linear, exponential and constant functions. The number of defects is 800, and the maximum defect size is 150.
图 13 缺陷程度空间衰减方式分别为线性、指数和常数函数情况下, 最大雪崩尺寸和负载加载步数随中心缺陷程度的变化. 缺陷个数为800, 缺陷尺寸上限为150 Figure13. The maximum avalanche size and the step number of load increase vary with the degree of the central defect when the spatial attenuation modes of the defect degree are linear, exponential and constant functions. The number of defects is 800, and the maximum defect size is 150.