Experimental study of test methods for the acoustic properties of snow

IF 4.9 2区 工程技术 Q1 ENGINEERING, CIVIL
Xiaomin Chang , Xuanhao Chen , Ming Xue , Guangyu Zuo , Yinke Dou
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Abstract

Acoustic attenuation is a key property of snow and plays a significant role in avalanche early warning. However, due to the dynamic changes in snow properties under natural environmental conditions, the automated monitoring of snow acoustic attenuation remains highly challenging. In this study, an acoustic testing system was designed using the transmission method to conduct acoustic measurements on natural snow samples and obtain information on the variations in snow acoustic properties under different conditions. Experimental results indicate that under an ambient temperature of −10 °C, the attenuation coefficient of snow layers increases with rising acoustic wave frequency across different snow densities. Additionally, as snow density increases, the attenuation coefficient increases while the boundary sound absorption coefficient decreases. Within the temperature range of −10 °C to 5 °C, the attenuation coefficient shows an increasing trend with rising temperature. In the range of −10 °C to −2.5 °C, the boundary sound absorption coefficient remains relatively stable, while from −2.5 °C to 5 °C, it shows a decreasing trend with increasing temperature. Within a snow water content range of 0–20 %, the attenuation coefficient increases with higher water content, whereas the boundary sound absorption coefficient decreases. Based on the experimental data, predictive models for the attenuation coefficient were developed with respect to ambient temperature and water content. The models demonstrated good predictive performance, with coefficients of determination (R2), root mean square errors (RMSE), biases (BIAS), and Nash-Sutcliffe efficiencies (NASH) of 0.918, 0.061, 0.002, and 0.982 for temperature-based models, and 0.946, 0.026, −0.001, and 0.991 for water content-based models, respectively. These results suggest that the models offer high predictive accuracy and provide a foundation for the automated observation of snow acoustic attenuation characteristics.
雪声特性测试方法的实验研究
声衰减是雪的一个重要特性,在雪崩预警中起着重要作用。然而,由于自然环境条件下积雪特性的动态变化,积雪声衰减的自动监测仍然具有很大的挑战性。本研究采用透射法设计声学测试系统,对天然雪样进行声学测量,获取不同条件下雪声学特性的变化信息。实验结果表明,在−10℃环境温度下,不同雪密度下,随着声波频率的增加,雪层的衰减系数增大。随着雪密度的增大,衰减系数增大,边界吸声系数减小。在−10℃~ 5℃的温度范围内,衰减系数随温度的升高呈增大趋势。在−10°C ~−2.5°C范围内,边界吸声系数保持相对稳定,而在−2.5°C ~ 5°C范围内,随着温度的升高,边界吸声系数呈下降趋势。在雪含水量0 ~ 20%范围内,衰减系数随雪含水量的增加而增大,而边界吸声系数则减小。基于实验数据,建立了基于环境温度和含水量的衰减系数预测模型。基于温度的模型的决定系数(R2)、均方根误差(RMSE)、偏倚(BIAS)和NASH - sutcliffe效率(NASH)分别为0.918、0.061、0.002和0.982,基于含水量的模型分别为0.946、0.026、- 0.001和0.991,显示出良好的预测性能。结果表明,该模型具有较高的预测精度,为积雪声衰减特征的自动观测奠定了基础。
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来源期刊
Cold Regions Science and Technology
Cold Regions Science and Technology 工程技术-地球科学综合
CiteScore
7.40
自引率
12.20%
发文量
209
审稿时长
4.9 months
期刊介绍: Cold Regions Science and Technology is an international journal dealing with the science and technical problems of cold environments in both the polar regions and more temperate locations. It includes fundamental aspects of cryospheric sciences which have applications for cold regions problems as well as engineering topics which relate to the cryosphere. Emphasis is given to applied science with broad coverage of the physical and mechanical aspects of ice (including glaciers and sea ice), snow and snow avalanches, ice-water systems, ice-bonded soils and permafrost. Relevant aspects of Earth science, materials science, offshore and river ice engineering are also of primary interest. These include icing of ships and structures as well as trafficability in cold environments. Technological advances for cold regions in research, development, and engineering practice are relevant to the journal. Theoretical papers must include a detailed discussion of the potential application of the theory to address cold regions problems. The journal serves a wide range of specialists, providing a medium for interdisciplinary communication and a convenient source of reference.
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