Extreme events and predictability of catastrophic failure in composite materials and in the Earth
Extreme events and predictability of catastrophic failure in composite materials and in the Earth
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DOI：
10.1140/epjst/e2012-01570-x
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发表时间：
2012-05
期刊：
影响因子：
--
通讯作者：
I. Main;M. Naylor
中科院分区：
文献类型：
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作者：
I. Main;M. Naylor
尽管人们试图隔离和预测极端地震，但这些地震几乎总是在真实的时间内发生，而没有明显的警告：完全确定性的地震预测在很大程度上是一种“黑天鹅”。另一方面，工程规模的岩石和其他复合材料样品在实验室受控条件下经常显示出明显的动态破坏前兆，并且在几次火山爆发之前成功地进行了疏散。这可能是因为极端地震在统计学上并不特殊，而是动态破裂过程的一种新特性。然而，基于地震在空间和时间上聚集的趋势，对给定规模以上的事件发生率进行概率预测，即使在实时模式下，与随机故障相比，也具有显著的技巧。在这场辩论中，我们使用地球（地震，火山）和实验室的例子来解决几个问题，包括以下问题。在模型选择中，我们如何识别“特征”事件，即超越幂律的事件（龙王存在吗）？我们如何定量地区分平稳和非平稳的危险模型（龙可能很快到来）？系统大小（龙的领域的大小）重要吗？是否有我们可能无法访问的即将发生灾难性故障的局部信号（龙在接近时是否有效地隐形）？我们专注于抽样效应和统计不确定性在识别极端事件及其可预测性的影响，并强调在空间和时间的缩放作为一个突出的问题要解决的定量研究，实验和模型的强大影响。
Despite all attempts to isolate and predict extreme earthquakes, these nearly always occur without obvious warning in real time: fully deterministic earthquake prediction is very much a ‘black swan’. On the other hand engineering-scale samples of rocks and other composite materials often show clear precursors to dynamic failure under controlled conditions in the laboratory, and successful evacuations have occurred before several volcanic eruptions. This may be because extreme earthquakes are not statistically special, being an emergent property of the process of dynamic rupture. Nevertheless, probabilistic forecasting of event rate above a given size, based on the tendency of earthquakes to cluster in space and time, can have significant skill compared to say random failure, even in real-time mode. We address several questions in this debate, using examples from the Earth (earthquakes, volcanoes) and the laboratory, including the following. How can we identify ‘characteristic’ events, i.e. beyond the power law, in model selection (do dragon-kings exist)? How do we discriminate quantitatively between stationary and non-stationary hazard models (is a dragon likely to come soon)? Does the system size (the size of the dragon’s domain) matter? Are there localising signals of imminent catastrophic failure we may not be able to access (is the dragon effectively invisible on approach)? We focus on the effect of sampling effects and statistical uncertainty in the identification of extreme events and their predictability, and highlight the strong influence of scaling in space and time as an outstanding issue to be addressed by quantitative studies, experimentation and models.