• Title of article

    Measuring and localizing acoustic emission events in snow prior to fracture

  • Author/Authors

    Manuel and Reiweger، نويسنده , , Ingrid and Mayer، نويسنده , , Klemens and Steiner، نويسنده , , Kevin and Dual، نويسنده , , Jürg and Schweizer، نويسنده , , Jürg، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2015
  • Pages
    10
  • From page
    160
  • To page
    169
  • Abstract
    Acoustic emissions (AE) are transient elastic waves produced by a sudden redistribution of stress in a material caused by changes in the internal structure. In other natural, heterogeneous materials monitoring AE has proven to be a valuable tool for stability estimation and failure prediction. After studying the characteristics of ultrasonic wave propagation in snow, we measured the acoustic emission signals during snow loading experiments in a cold laboratory. Using snow columns we found that most energy of an artificial acoustic signal was transmitted at 31 kHz. Best coupling to snow was achieved by attaching the AE sensors with silicone adhesive to thin aluminium plates which were then frozen to the snow. Localizing AE events during fracture of layered snow samples showed that the AE originated within the weakest layer, i.e. the relevant layer for snow failure. For finding an indication of imminent failure, we analysed the exponent β of the cumulative size-frequency distribution (‘survival curve’) of event energy. At the occurrence of instabilities, the β-curve deviated from steady behaviour and exhibited distinct ‘drops’, indicating that the power law behaviour of the distribution was not fulfilled anymore. Studying the temporal evolution of the exponent β might therefore provide useful information about snowpack stability also in the field—provided that the AE signals are not too strongly attenuated and can be detected in time before catastrophic failure occurs.
  • Keywords
    Snow , fracture , acoustic emission , Weak layer
  • Journal title
    Cold Regions Science and Technology
  • Serial Year
    2015
  • Journal title
    Cold Regions Science and Technology
  • Record number

    2273295