| Summary: | This dataset is a collection of audio recordings from three frozen lakes that were acquired with the primary purpose of estimating ice thickness using recorded air-coupled flexural waves. The flexural waves were excited by different impulsive artificial sources (hammer strikes, jumping, ice skates) and natural sources (thermal expansion/contraction cracks i.e. icequakes). The flexural wave event characteristics and timings within the audio files are described in the event table. In this study we took an intentionally low-tech approach, aiming to estimate key physical parameters of lake ice using a single, inexpensive microphone. We consider this approach highly relevant to the issue of transport safety and the relatively high number of accidents involving breakthrough failure of thin ice underlines the importance of this topic. We conducted a range of experiments on three frozen lakes in the Tromsø region of Northern Norway and found that the monochromatic air-coupled flexural wave was a robust feature of impulsively excited frozen lakes. Ice thickness was estimated via a closed form solution that only depends on the measured monochromatic frequency of the air-coupled flexural wave and a set of assumed physical parameters for the ice, air and water. We discuss the impact of uncertainty in the assumed parameters on estimated ice thickness and bearing capacity, finding the uncertainty to be quite small, particularly when physical observation of ice type or drilled thickness are available to constrain the assumed Young’s modulus of the ice. Ice thicknesses estimated from air-coupled flexural waves were typically within 5-10% of ice thickness measured in holes drilled in the vicinity of the microphone for both artificial sources including hammer strikes, jumping and tapping with ice skates and natural ice quakes. The thickness estimates were also similarly accurate whether the microphone was resting on the ice, placed on land along the shoreline or handheld. We also showed that it is possible to record the ...
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