作者: Jérémie Vasseur , Fabian B. Wadsworth , Yan Lavallée , Andrew F. Bell , Ian G. Main
DOI: 10.1038/SREP13259
关键词: Deformation (engineering) 、 Reliability (statistics) 、 Brittleness 、 Computer science 、 Landslide 、 Variable (computer science) 、 Range (statistics) 、 Soil science 、 Magma 、 Induced seismicity 、 Catastrophic failure 、 Data mining
摘要: Elastic waves are generated when brittle materials subjected to increasing strain. Their number and energy increase non-linearly, ending in a system-sized catastrophic failure event. Accelerating rates of geophysical signals (e.g., seismicity deformation) preceding large-scale dynamic can serve as proxies for damage accumulation the Failure Forecast Method (FFM). Here we test hypothesis that style mechanisms deformation, accuracy FFM, both tightly controlled by degree microstructural heterogeneity material under stress. We generate suite synthetic samples with variable heterogeneity, gas volume fraction. experimentally demonstrate prediction increases drastically heterogeneity. These results have significant implications broad range material-based disciplines which forecasting is central importance. In particular, FFM has been used only success forecast scenarios field (volcanic eruptions landslides) laboratory (rock magma failure). Our show this variability may be explained, reliability quantified significantly improved, accounting first-order control on power.