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Recently acoustic signature of dislocation avalanches in HCP materials was found to be long tailed in size and energy, suggesting critical dynamics. Moreover, the intermittent plastic response was found to be generic for micro- and nano-sized systems independently of their crystallographic symmetry. These rather remarkable discoveries are reviewed in this paper in the perspective of the recent studies performed in our group. We discuss the physical origin and the scaling properties of plastic fluctuations and address the nature of their dependence on crystalline symmetry, system size, and disorder content. A particular emphasis is placed on the formation of dislocation structures, and on our ability to temper plastic fluctuations by alloying. We also discuss the “smaller is wilder” size effect that culminates in a paradoxical crack-free brittle behavior of very small, initially dislocation free crystals. We argue that the implied transition between different rheological behaviors is regulated by the ratio of length scales $R=L/l$, where $L$ is the system size and $l$ is the internal length. We link this size effect with size dependence of strength (“smaller is stronger”) and the size-induced switch between different hardening mechanisms. We show that the task of taming the intermittency of plastic flow at ultra-small scales can be accomplished by generating tailored quenched disorder which allows one to control micro- and nano-forming and opens new perspectives in micro-metallurgy and structural engineering of miniature load-carrying elements. These insights were beyond the reach of conventional theoretical approaches that do not explicitly account for the stochastic nature of collective dislocation dynamics.

In the perspective of an upcoming seasonally ice-free Arctic, understanding the dynamics of sea ice in the changing climate is a major challenge in oceanography and climatology. In particular, the new generation of sea ice models will require fine parameterization of sea ice thickness and rheology. With the rapidly evolving state of sea ice, achieving better accuracy, as well as finer temporal and spatial resolutions of its thickness, will set new monitoring standards, with major scientific and geopolitical implications. Recent studies have shown the potential of passive seismology to monitor the thickness, density and elastic properties of sea ice with significantly reduced logistical constraints. For example, human intervention is no longer required, except to install and uninstall the geophones. Building on this approach, we introduce a methodology for estimating sea ice thickness with high spatial and temporal resolutions from the analysis of icequake waveforms. This methodology is based on a deep convolutional neural network for automatic clustering of the ambient seismicity recorded on sea ice, combined with a Bayesian inversion of the clustered waveforms. By applying this approach to seismic data recorded in March 2019 on fast ice in the Van Mijen Fjord (Svalbard), we observe the spatial clustering of icequake sources along the shoreline of the fjord. The ice thickness is shown to follow an increasing trend that is consistent with the evolution of temperatures during the 4 weeks of data recording. Comparing the energy of the icequakes with that of artificial seismic sources, we were able to derive a power law of icequake energy and to relate this energy to the size of the cracks that generate the icequakes. [ABSTRACT FROM AUTHOR]

The early stage of the postseismic phase is characterized by a large deformation rate. Its analysis is thus key to decipher the role played by different mechanisms (afterslip and viscoelasticity) at various time scales. Here, we process GPS data to obtain 30‐s kinematic position time series recording the surface deformation following the Mw 9.0 Tohoku‐Oki megathrust earthquake (2011), and combine them with static solutions over 9 years. We analyze the temporal evolution of the time series and use these observations to image the postseismic slip. We find that the first month of deformation following Tohoku‐Oki can be explained by an afterslip mechanism, that exhibits an "Omori‐like" decay, with a p‐value around 0.75 almost everywhere with the exception of a small region around Ibaraki prefecture where p ∼ 1 is observed. This p < 1 indicates that the postseismic displacements do not increase logarithmically with time as predicted by rate‐and‐state rheology. Instead, we argue that early afterslip is associated with a transient brittle creep mechanism. We use numerical simulations to show that an exponent of p < 1 can be explained by a combination of thermal activation of local slips and elastic interactions. Over longer time scales, an additional mechanism is required to explain the observed deformation signal, and the transient brittle creep mechanism is combined with viscoelastic relaxation modeled by a Newtonian flow. The spatial analysis reveals two distinct afterslip regions, a major one on the North, associated with a p‐value around 0.75, and a smaller one close to the Ibaraki aftershock, associated with p ∼ 1. Plain Language Summary: The Tohoku‐Oki earthquake of 11 March 2011, is the largest subduction earthquake of the past decade. Earthquakes produce a perturbation in the state of stress of the crust and mantle, and this perturbation is relaxed after the earthquake, during the postseismic phase. This phase is associated with deformations measurable at the earth surface with instruments such as GPS stations. Two main mechanisms are commonly considered to explain this postseismic phase: afterslip, which corresponds to the aseismic slip occurring around the fault zone, or a viscoelastic relaxation in the mantle. The originality of our study is the inclusion of the GPS signal from the first few minutes after the earthquake, giving details on the early postseismic deformation. We find that the early postseismic phase of Tohoku‐Oki can be understood from a different physical model than those commonly considered. Based on a spatial analysis, we have identified a first major afterslip region downdip of the Tohoku‐Oki rupture zone and a second small area near the largest aftershock. These two regions also show different temporal evolutions. Further studies on other large earthquakes should allow to revisit the early postseismic phase of large subduction earthquakes. Key Points: Kinematic and static positions time series are used to analyze the postseismic deformation following the Mw 9.0 Tohoku‐Oki earthquakeThe temporal evolution of the early postseismic is explained by an Omori‐like Transient Brittle Creep mechanism with a p‐value around 0.75The spatial analysis reveals a major afterslip zone downdip from the main rupture and a secondary one close to the Ibaraki‐Oki event [ABSTRACT FROM AUTHOR]

Due to global warming, the decline in the Arctic sea ice has been accelerating over the last 4 decades, with a rate that was not anticipated by climate models. To improve these models, there is the need to rely on comprehensive field data. Seismic methods are known for their potential to estimate sea-ice thickness and mechanical properties with very good accuracy. However, with the hostile environment and logistical difficulties imposed by the polar regions, seismic studies have remained rare. Due to the rapid technological and methodological progress of the last decade, there has been a recent reconsideration of such approaches. This paper introduces a methodological approach for passive monitoring of both sea-ice thickness and mechanical properties. To demonstrate this concept, we use data from a seismic experiment where an array of 247 geophones was deployed on sea ice in a fjord at Svalbard, between 1 and 24 March 2019. From the continuous recording of the ambient seismic field, the empirical Green function of the seismic waves guided in the ice layer was recovered via the so-called "noise correlation function". Using specific array processing, the multi-modal dispersion curves of the ice layer were calculated from the noise correlation function, and then inverted for the thickness and elastic properties of the sea ice via Bayesian inference. The evolution of sea-ice properties was monitored for 24 d, and values are consistent with the literature, as well as with measurements made directly in the field. [ABSTRACT FROM AUTHOR]

This work presents a new damage criterion suitable for elastic, elastic-plastic/viscous or elastic-viscous-plastic materials involving rupture effects. Its derivation, made here within a thermodynamic framework, follows previous scalar-valued damage mechanics approaches. Such approaches are appropriate to many geophysical problems involving quasi-brittle materials for which there is no clear physical justification for the level of complexity of a tensorial damage variable. Distinction between the mechanical response to compressive and tensile stresses is therefore not introduced by the damage itself but via a special definition of the Helmholtz free energy. This scheme differs from previous ones in that it combines with an evolution of Poisson's ratio with the level of damage, which allows expressing the damage criterion in the principal stresses space. Moreover, there is no need to compute the stress eigensystem, which makes it simpler to implement than the Mohr–Coulomb damage criterion. Here we derive this damage criterion and compare it to observations of the variations of the bulk modulus in damaged geomaterials. We also compare it to in-situ stress measurements and find a good agreement in terms of the shape of the criterion in the stress space. We tentatively interpret the results in the context of previous studies of rock and ice mechanics. [ABSTRACT FROM AUTHOR]

Despite their high potential for accurate sea ice properties estimation, seismic methods are still limited by the difficulty of access and the challenging logistics of polar environments. Conventional seismic methods generally require tens of geophones together with active seismic sources for monitoring applications. While this is not an issue for mainland environment, it is restrictive for sea ice and prevents long‐term monitoring. We introduce a method to estimate sea ice thickness and elastic properties from passive recordings of the ambient seismic field with a minimal number of geophones. In comparison with our previous work (Moreau et al., 2020; https://doi.org/10.1029/2019JC015709) where about 50 sensors were used, the number of geophones is reduced by 1 order of magnitude, thanks to a new strategy of inversion of the passive seismic data. The method combines noise interferometry for estimating the elastic properties, with a Bayesian inversion of the dispersion in the waveforms of icequakes for inferring ice thickness, based on passive recordings from only 3–5 geophones, depending on the signal to noise ratio. We demonstrate its potential both on data recorded on thin landfast ice in Svalbard, and on data recorded on thick pack ice in the Arctic ocean. Plain Language Summary: Seismic methods have high potential for monitoring important properties of sea ice, such as its thickness of rigidity. Such data are essential for improving climate models. However, the use of seismic methods is limited by the difficulty of access and the challenging logistics of polar environments. It is therefore essential to reduce as much as possible the instruments required for their application. Conventional seismic methods generally require tens of geophones together with active seismic sources for monitoring applications. We introduce a method to estimate sea ice properties based on the recordings of seismic noise with only three seismic stations, and demonstrate its potential on data recorded in a frozen fjord in Svalbard, as well as on data collected on drifting sea ice in the Arctic Ocean. The method is shown to have very promising potential for long‐term and accurate monitoring of the properties of sea ice. Key Points: The Young's modulus and Poisson's ratio of sea ice are estimated from seismic noise interferometryBayesian inference is applied to icequake recordings for a simultaneous inversion of the icequake position and sea ice thicknessIn comparison with our previous work, where about 50 sensors were required, the number of stations is reduced by 1 order of magnitude [ABSTRACT FROM AUTHOR]

Field data are needed for a better understanding of sea ice decline in the context of climate change. The rapid technological and methodological advances of the last decade have led to a reconsideration of seismic methods in this matter. In particular, passive seismology has filled an important gap by removing the need to use active sources. We present a seismic experiment where an array of 247 geophones was deployed on sea ice, in the Van Mijen fjord near Sveagruva (Svalbard). The array is a mix of 1C and 3C stations with sampling frequencies of 500 and 1000 Hz. They recorded continuously the ambient seismic field in sea ice between 28 February and 26 March 2019. Data also include active acquisitions on 1 and 26 March with a radar antenna, a shaker unit, impulsive sources, and artificial sources of seismic noise. This data set is of unprecedented quality regarding sea ice seismic monitoring, as it also includes thousands of microseismic events recorded each day. By combining passive seismology approaches with specific array processing methods, we demonstrate that the multimodal dispersion curves of sea ice can be calculated without an active source and then used to infer sea ice properties. We calculated an ice thickness, Young's modulus, and Poisson's ratio with values h=54±3 cm, E=3.9±0.15 GPa, and ν=0.34±0.02 on 1 March, and h=58±3 cm, E=4.4±0.15 GPa, and ν=0.32±0.02 on 5 March. These values are consistent with in situ field measurements and observations. Key Points: An array of 247 geophones was deployed on sea ice for 27 days during winter 2019Broadband dispersion of several guided wave modes propagating in sea ice were extracted from passive seismic dataSea ice thickness and elastic properties were estimated from guided wave dispersion [ABSTRACT FROM AUTHOR]

The deformation of a circular fault in a thin floating ice plate imposed by a slow rotational displacement is investigated. Temporal changes in shear strength, as a proxy for the resistance of the fault as a whole, are monitored by the torque required to impose a constant displacement rate. Micro‐seismic monitoring is used to study the relationship between fault average resistance (torque) and micro‐ruptures. The size distribution of ruptures follows a power‐law scaling characterized by an unusually high exponent (b≃3), characteristic of a deformation driven by small ruptures. In strong contrast to the typical brittle dynamics of crustal faults, an 'apparently aseismic' deformation regime is observed in which small undetected seismic ruptures, below the detection level of the monitoring system, control the slip budget. Most (≃71%) of the detected ruptures are organized in bursts with highly similar waveforms, suggesting that these ruptures are only a passive by‐product of apparently aseismic slip events. The seismic signature of this deformation regime has strong similarities with crustal faulting in settings characterized by high temperature and with non‐volcanic tremors. Key Points: A micro‐seismic monitoring of a fault is setup to monitor its deformationSmall undetected fractures control the slip and energy budgets of the faultFractures are mostly a by‐product of the imposed slip, similarly to swarm‐seismicity [ABSTRACT FROM AUTHOR]