Revealing the spatiotemporal complexity of the magnitude distribution and b-value during an earthquake sequence

Analysis of critical states based on acoustic emission signals during progressive failure of wood

The analysis of critical states during fracture of wood materials is crucial for wood building safety monitoring, wood processing, etc. In this paper, beech and camphor pine are selected as the research objects, and the acoustic emission signals during the fracture process of the specimens are analyzed by three-point bending load experiments. On the one hand, the critical state interval of a complex acoustic emission signal system is determined by selecting characteristic parameters in the natural time domain. On the other hand, an improved method of b_value analysis in the natural time domain is proposed based on the characteristics of the acoustic emission signal. The K-value, which represents the beginning of the critical state of a complex acoustic emission signal system, is further defined by the improved method of b_value in the natural time domain. For beech, the analysis of critical state time based on characteristic parameters can predict the "collapse" time 8.01 s in advance, while for camphor pines, 3.74 s in advance. K-value can be analyzed at least 3 s in advance of the system "crash" time for beech and 4 s in advance of the system "crash" time for camphor pine. The results show that compared with traditional time-domain acoustic emission signal analysis, natural time-domain acoustic emission signal analysis can discover more available feature information to characterize the state of the signal. Both the characteristic parameters and Natural_Time_b_value analysis in the natural time domain can effectively characterize the time when the complex acoustic emission signal system enters the critical state. Critical state analysis can provide new ideas for wood health monitoring and complex signal processing, etc.

B-value variations in the Central Chile seismic gap assessed by a Bayesian transdimensional approach

The b-value can be used to characterize the seismic activity for a given earthquake catalog and provide information on the stress level accumulated at active faults. Here we develop an algorithm to objectively estimate variations of b-value along one arbitrary dimension. To this end, we employ a Bayesian transdimensional approach where the seismic domains will be self-defined according to information in the seismic catalog. This makes it unnecessary to prescribe the location and extent of domains, as it is commonly done. We first show the algorithm's robustness by performing regressions from synthetic catalogs, recovering the target models with great accuracy. We also apply the algorithm to a microseismicity catalog for the Central Chile region. This segment is considered a seismic gap where the last major earthquake with shallow slip was in 1730. Our results illuminate the downdip limit of the seismogenic zone and the transition to intraslab seismicity. In the along-strike direction, low b-value coincides with the extent of locked asperities, suggesting a high-stress loading at the Central Chile seismic gap. Our results indicate the reliability of the Bayesian transdimensional method for capturing robust b-value variations, allowing us to characterize the mechanical behavior on the plate interface of subduction zones.

A comprehensive suite of earthquake catalogues for the 2016-2017 Central Italy seismic sequence

The protracted nature of the 2016-2017 central Italy seismic sequence, with multiple damaging earthquakes spaced over months, presented serious challenges for the duty seismologists and emergency managers as they assimilated the growing sequence to advise the local population. Uncertainty concerning where and when it was safe to occupy vulnerable structures highlighted the need for timely delivery of scientifically based understanding of the evolving hazard and risk. Seismic hazard assessment during complex sequences depends critically on up-to-date earthquake catalogues—i.e., data on locations, magnitudes, and activity of earthquakes—to characterize the ongoing seismicity and fuel earthquake forecasting models. Here we document six earthquake catalogues of this sequence that were developed using a variety of methods. The catalogues possess different levels of resolution and completeness resulting from progressive enhancements in the data availability, detection sensitivity, and hypocentral location accuracy. The catalogues range from real-time to advanced machine-learning procedures and highlight both the promises as well as the challenges of implementing advanced workflows in an operational environment.

Rock and fault rheology explain differences between on fault and distributed seismicity

Analysis of seismicity can illuminate active fault zone structures but also deformation within large volumes of the seismogenic zone. For the M_w 6.5 2016–2017 Central Italy seismic sequence, seismicity not only localizes along the major structures hosting the mainshocks (on-fault seismicity), but also occurs within volumes of Triassic Evaporites, TE, composed of alternated anhydrites and dolostones. These volumes of distributed microseismicity show a different frequency-magnitude distribution than on-fault seismicity. We interpret that, during the sequence, shear strain-rate increase, and fluid overpressure promoted widespread ductile deformation within TE that light-up with distributed microseismicity. This interpretation is supported by field and laboratory observations showing that TE background ductile deformation is complex and dominated by distributed failure and folding of the anhydrites associated with boudinage hydro-fracturing and faulting of dolostones. Our results indicate that ductile crustal deformation can cause distributed microseismicity, which obeys to different scaling laws than on-fault seismicity occurring on structures characterized by elasto-frictional stick-slip behaviour.

A new study sheds light on earthquake physics, showing that lithological and rheological heterogeneities in the rocks composing the seismogenic layer strongly influence seismicity distributions and earthquake scaling laws.