A statistical method for predicting sound absorbing property of porous metal materials by using quartet structure generation set
A statistical method for predicting sound absorbing property of porous metal materials by using quartet structure generation set
复制标题
利用四重体结构生成集预测多孔金属材料吸声性能的统计方法
DOI：
10.1016/j.jallcom.2014.11.159
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发表时间：
2015-03
影响因子：
6.2
通讯作者：
Li Jing
中科院分区：
文献类型：
--
作者：
Dong Guan;Jiu Hui Wu;Li Jing
本文提出了一种预测多孔金属材料吸声性能的统计方法。为了反映多孔金属材料的随机分布特性，基于随机簇生长理论，采用四重结构生成集（quartetetstructuregenerationset，QSGS）方法对多孔金属材料的各种微结构进行了数值生成.然后利用传递函数方法沿着QSGS工具，研究了具有复杂随机几何形状的多孔金属材料的吸声性能。该方法对金属橡胶的数值模拟结果与以往的经验模型和相应的实验数据吻合较好，验证了统计方法的有效性。利用该方法研究了不同厚度、孔隙率等参数对吸声结构吸声性能的影响，并通过经验模型对所得结果进行了验证。因此，该方法是一种可靠、稳健的多孔金属材料吸声性能预测方法，可用于指导多孔金属吸声材料的设计和制备。
In this paper, a statistical method for predicting sound absorption properties of porous metal materials is presented. To reflect the stochastic distribution characteristics of the porous metal materials, a random internal morphology and structure generation-growth method, termed as the quartet structure generation set (QSGS), has been utilized based on the stochastic cluster growth theory for numerical generating the various microstructures of porous metal materials. Then by using the transfer-function approach along with the QSGS tool, we investigate the sound absorbing performance of porous metal materials with complex stochastic geometries. The statistical method has been validated by the good agreement among the numerical results for metal rubber from this method and a previous empirical model and the corresponding experimental data. Furthermore, the effects of different parameters such as thickness and porosity on sound absorption performance of the generated structures are studied by the present method, and the obtained results are validated by an empirical model as well. Therefore, the present method is a reliable and robust method for predicting the sound absorption performance of porous metal materials, and could be utilized to guide the design and fabrication of the sound-absorption porous metal materials.
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影响因子：
2.4
作者：
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通讯作者：
Xiaolin Wang;T. Lu
影响因子：
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作者：
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