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首页> 外文期刊>International Journal of Biometeorology: Journal of the International Society of Biometeorology >Analysis and simulation of dynamic response behavior of Scots pine trees to wind loading
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Analysis and simulation of dynamic response behavior of Scots pine trees to wind loading

机译:苏格兰松树对风荷载的动态响应行为分析与仿真

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摘要

This paper presents an empirical approach for the decomposition, simulation, and reconstruction of wind-induced stem displacement of plantation-grown Scots pine trees. Results from singular spectrum analysis (SSA) allow a low-dimensional characterization of the complex and complicated tree motion patterns in response to non-destructive wind excitation. Since motion of the sample trees was dominated by sway in the first mode, the application of SSA on time series of sample trees' stem displacement yielded characteristic and distinguishable non-oscillatory trend components, quasi-oscillatory sway, and noise, of which only the non-oscillatory components were correlated directly with wind characteristics. Although sway in the range of the dominant damped fundamental frequency dominated the measured stem displacement signals, it was almost decoupled from near-surface airflow. The ability to discriminate SSA-components is demonstrated based on correlation and spectral analysis. These SSA-components, as well as wind speed measured in the canopy space of the Scots pine forest, were used to train neural networks, which could then reasonably simulate tree response to wind excitation.
机译:本文提出了一种经验方法,用于人工种植的苏格兰松树风诱导的茎位移的分解,模拟和重建。奇异频谱分析(SSA)的结果可响应复杂的风向激励,对复杂的树木运动模式进行低维表征。由于在第一模式下样本树的运动主要由摇摆控制,因此在样本树茎位移的时间序列上应用SSA可以产生特征性和可区分的非振荡趋势成分,准振荡摇摆和噪声,其中只有非振荡成分与风的特性直接相关。尽管在主导阻尼基频范围内摇摆在测得的杆位移信号中占主导地位,但它几乎与近地表气流分离。基于相关性和光谱分析证明了区分SSA成分的能力。这些SSA分量以及在苏格兰松林冠层空间中测得的风速被用于训练神经网络,然后可以合理地模拟树木对风激励的响应。

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