标题： 突破记录的纤维束模型中的蠕变断裂爆发 显示英文标题

标题： Record breaking bursts in a fiber bundle model of creep rupture

摘要： 我们研究了在异质材料蠕变断裂的纤维束模型中爆裂事件的时间序列中的破纪录事件的统计特性。 在模型中，纤维由于两种机制而断裂：缓慢积累的损伤触发立即断裂的爆发，类似于实验中的声发射。 断裂过程加速，使得断裂级联的大小增加，而连续事件之间的等待时间减少直至失效。 记录事件被定义为在时间序列中比所有先前事件更大的爆发。 我们分析了记录的统计特性，重点放在模型的等载荷共享（ELS）极限，并将结果与独立同分布随机变量序列的记录统计进行比较。 计算机模拟显示，记录的数量随着事件数量的对数增长，除了宏观失效的附近区域，其中显示出指数依赖关系。 这两种模式可以归因于小爆发尺寸的无序主导和应力增强导致的扩展爆发的有效触发。 记录的大小以及连续记录事件之间的增量均以幂律分布为特征，具有共同的指数1.33，这与通常的纤维束ELS爆发大小指数显著不同。 等待时间的分布表现出相同的行为，然而，低负载和高负载下有两个不同的指数。 通过研究记录的演变，我们识别出系统的一个与负载相关的特征尺度，该尺度在接近失效时分离了记录突破的减速和加速。 显示英文摘要

摘要： We investigate the statistics of record breaking events in the time series of crackling bursts in a fiber bundle model of the creep rupture of heterogeneous materials. In the model fibers break due to two mechanisms: slowly accumulating damage triggers bursts of immediate breakings analogous to acoustic emissions in experiments. The rupture process accelerates such that the size of breaking avalanches increases while the waiting time between consecutive events decreases towards failure. Record events are defined as bursts which have a larger size than all previous events in the time series. We analyze the statistics of records focusing on the limit of equal load sharing (ELS) of the model and compare the results to the record statistics of sequences of independent identically distributed random variables. Computer simulations revealed that the number of records grows with the logarithm of the event number except for the close vicinity of macroscopic failure where an exponential dependence is evidenced. The two regimes can be attributed to the dominance of disorder with small burst sizes and to stress enhancements giving rise efficient triggering of extended bursts, respectively. Both the size of records and the increments between consecutive record events are characterized by power law distributions with a common exponent 1.33 significantly different from the usual ELS burst size exponents of fiber bundles. The distribution of waiting times follows the same behavior, however, with two distinct exponents for low and high loads. Studying the evolution of records we identify a load dependent characteristic scale of the system which separates slow down and acceleration of record breaking as failure is approached.