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Speed and attenuation of acoustic waves in snow: Laboratory experiments and modeling with Biot's theory

机译:雪中​​声波的速度和衰减:毕奥特理论的实验室实验和建模

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Monitoring acoustic emissions (AE) prior to imminent failure is considered a promising technique for assessing snow slope instability. Gaps in elastic wave propagation characteristics in snow hinder quantitative interpretation of AE signals. Our study focuses on characterizing the propagation of acoustic reference signals in the ultrasonic range across cylindrical snow samples with varying density (240-450 kg m(-3)). We deduced the acoustic attenuation coefficient within snow by performing experiments with different column lengths to eliminate possible influences of the snow-sensor coupling. The attenuation coefficient was measured for the entire burst signal and for single frequency components in the range of 8 to 35 kHz. The acoustic wave propagation speed, calculated from the travel time of the acoustic signal, varied between 300 m s(-1) and 950 m s(-1), depending on the density and hardness of snow. From the sound speed we also estimated the Young's modulus of our snow samples; the values of the modulus ranged from 30 to 340 MPa for densities between 240 and 450 kg m(-3). In addition, we modeled the sound propagation for our experimental setup using Biot's model for wave propagation in a porous medium. The model results were in good agreement with our experimental results and suggest that our acoustic signals consisted of Biot's slow and fast waves. Our results can be used to improve the identification and localization of acoustic emission sources within snow in view of assessing snow slope instability. (c) 2016 The Authors. Published by Elsevier B.V.
机译:在即将发生故障之前监测声发射(AE)被认为是评估雪坡不稳定性的有前途的技术。雪中​​弹性波传播特性的间隙阻碍了AE信号的定量解释。我们的研究重点在于表征超声参考信号在密度变化为(240-450 kg m(-3))的圆柱形雪样之间的超声范围内的传播特性。我们通过在不同长度的柱上进行实验来推算雪中的声衰减系数,以消除雪传感器耦合的可能影响。测量整个突发信号和8至35 kHz范围内的单个频率分量的衰减系数。根据声波的传播时间计算出的声波传播速度在300 m s(-1)和950 m s(-1)之间变化,具体取决于雪的密度和硬度。根据声速,我们还估计了雪样的杨氏模量。对于240至450 kg m(-3)之间的密度,模量值的范围从30到340 MPa。此外,我们使用Biot模型在多孔介质中传播波的过程中,对实验设置中的声音传播进行了建模。模型结果与我们的实验结果非常吻合,表明我们的声音信号由比奥的慢波和快波组成。考虑到评估雪坡的不稳定性,我们的结果可用于改善对雪内声发射源的识别和定位。 (c)2016作者。由Elsevier B.V.发布

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