The temperature- and density-dependent acoustic emission response of snow in monoaxial compression tests

Scapozza, Carlo; Bucher, Felix; Amann, Peter; Ammann, Walter; Bartelt, Perry

doi:10.3189/172756404781814861

Cited by 11 publications

(8 citation statements)

References 15 publications

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“…However, this type of AE were not detected since the attenuation of acoustic waves in snow is high, in particular for high-frequency signals (Capelli and others, 2016). Higher frequency AE for slow experiments were observed by Scapozza and others (2004) for much smaller specimens, and were attributed to creep processes in the ice matrix.…”

Section: Discussionsupporting

confidence: 51%

“…St. Lawrence (1980) developed a relation describing the AE activity as a function of stress and strain for slow deformation of snow. More recently, Scapozza and others (2004) performed displacement-controlled compression experiments with homogeneous snow samples and observed high-frequency AE (500 kHz) probably due to creep processes in the ice skeleton for strain rates <2 × 10 −3 s −1 and lower frequency AE (30 Hz) for strain rates >2 × 10 −3 s −1 , which they attributed to cracking. Moreover, Scapozza and others (2004) reported for low strain rates that the maximum of the AE activity corresponded to the yield point and observed the relation between the peak AE rate (hits s −1 ) and the strain rate , with the parameter C being temperature-dependent and γ a constant.…”

Section: Introductionmentioning

confidence: 98%

“…More recently, Scapozza and others (2004) performed displacement-controlled compression experiments with homogeneous snow samples and observed high-frequency AE (500 kHz) probably due to creep processes in the ice skeleton for strain rates <2 × 10 −3 s −1 and lower frequency AE (30 Hz) for strain rates >2 × 10 −3 s −1 , which they attributed to cracking. Moreover, Scapozza and others (2004) reported for low strain rates that the maximum of the AE activity corresponded to the yield point and observed the relation between the peak AE rate (hits s −1 ) and the strain rate , with the parameter C being temperature-dependent and γ a constant. Reiweger and others (2015b) performed load-controlled experiments with layered snow samples including a weak layer (WL) and observed an acceleration of the AE rate before failure as well as a decrease of the b -value very close to complete failure of the sample; they also found this AE behavior in case of partial failure of the sample.…”

Section: Introductionmentioning

confidence: 98%

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Acoustic emission signatures prior to snow failure

Capelli¹,

Reiweger

Schweizer³

2018

J. Glaciol.

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Snow slab avalanches are caused by cracks forming and propagating in a weak snow layer below a cohesive slab. The gradual damage process leading to the formation of the initial failure within the weak layer (WL) is still not entirely understood. To this end, we designed a novel test apparatus that allows performing loading experiments with large snow samples (0.25 m2) including a WL at different loading rates and simultaneously monitoring the acoustic emissions (AE) response. By analyzing the AE generated by micro-cracking, we studied the evolution of the damage process preceding snow failure. At fast loading rates, the exponent of the AE energy distribution (b-value) gradually changed, and both the energy rate and the inverse waiting time increased exponentially with increasing load. These changes in AE signature indicate a transition from small to large events and an acceleration of the damage processes leading to brittle failure. For the experiments at slow loading rate, these changes in the AE signature were not or only partially present, even if the sample failed, indicating a different evolution of the damage process. The observed characteristics in AE response provide new insights on how to model snow failure as a critical phenomenon.

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Section: Discussionsupporting

confidence: 51%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

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Acoustic emission signatures prior to snow failure

Capelli¹,

Reiweger

Schweizer³

2018

J. Glaciol.

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“…More recently, Scapozza et al (2004) measured acoustic emissions in the ultrasonic range in snow during compression tests in the laboratory. They found that AE signals in snow can be measured over a wide frequency range.…”

Section: Introductionmentioning

confidence: 99%

Measuring and localizing acoustic emission events in snow prior to fracture

Reiweger¹,

Mayer

Steiner

et al. 2015

Cold Regions Science and Technology

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“…For all strain rates, snow fails at strain and stress values that are much higher than the linear elastic limit [7]. This rate dependence of the failure behavior is also reflected in the acoustic emission (AE) response of snow (e.g., [8,9]). The AE response in turn is used for measuring precursors of material breakdown and to predict the time of failure.…”

Section: Introductionmentioning

confidence: 97%

Fiber-bundle model with time-dependent healing mechanisms to simulate progressive failure of snow

et al. 2018

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Snow is a heterogeneous material with strain-and/or load-rate-dependent strength. In particular, a transition from ductile-to-brittle failure behavior with increasing load rate is observed. The rate-dependent behavior can partly be explained with the existence of a unique healing mechanism in snow that stems from its high homologous temperature (temperature close to melting point). As soon as broken elements in the ice matrix get in contact, they start sintering and the structure may regain strength. Moreover, the ice matrix is subjected to viscous deformation, inducing a relaxation of local load concentrations and, therefore, further counteracting the damage process. Ideal tools for studying the failure process of heterogeneous materials are the fiber-bundle models (FBMs), which allow investigating the effects of basic microstructural characteristics on the general macroscopic failure behavior. We present an FBM with two concurrent time-dependent healing mechanisms: sintering of broken fibers and relaxation of load inhomogeneities. Sintering compensates damage by creating additional intact, load-supporting fibers which lead to an increase of the bundle strength. However, the character of the failure is not changed by sintering alone. With combined sintering and load relaxation, load is distributed from old stronger fibers to new fibers that carry fewer load. So as we additionally incorporated load redistribution to the FBM, the failure occurred suddenly without decrease of the order parameter-describing the amount of damage in the bundle-and without divergence of the fiber failure rate. Moreover, the b value, i.e., the power-law exponent of frequency-magnitude statistics of fibers breaking in load redistribution steps, at failure converged to b ≈ 2, a value higher than that of a classical FBM without healing (b = 3 2 ). These results indicate that healing, as the combined effect of sintering and load relaxation, changes the type of the phase transition at failure. This change of the phase transition is important for quantifying or predicting the failure (e.g., by monitoring acoustic emissions) of snow or other materials for which healing plays an important role.

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The temperature- and density-dependent acoustic emission response of snow in monoaxial compression tests

Cited by 11 publications

References 15 publications

Acoustic emission signatures prior to snow failure

Acoustic emission signatures prior to snow failure

Measuring and localizing acoustic emission events in snow prior to fracture

Fiber-bundle model with time-dependent healing mechanisms to simulate progressive failure of snow

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