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The development trend of spallation damage mechanics is to construct a physical model that couples information with micro-mesoscale structure of materials, which also promotes the development of numerical calculation methods, experimental techniques and theoretical research. The mechanism responsible for plastic deformation and failure of structural metal materials at high strain rates is complex and ainfluenced by heterogeneities in the micro-mesoscale structure that comprises the distribution of grain boundaries, interfaces, and pre-existing densities voids. The distribution of these mesoscale heterogeneities can provide either strengthening behavior or void nucleation sites and influence spall failure behavior. Due to the lack of evolutionary information of micro-mesoscopic void distribution characteristics, the current spallation damage model is not only restricted in its application in extreme environments with high strain rates, high pressures, and shock, but also does not effectively provide some information about the correlation between material damage and final material fragmentation particle size, which is of very concern in engineering. Therefore, it is urgent to develop a spallation damage model that can reflect the variation law of micro-mesoscopic void distribution characteristics in damaged materials. The probability distribution function of void nucleation based on cosine function is given in this work by analyzing various influencing factors in the process of void nucleation, combining the characteristics of early void growth, and considering the convenience of analytical solution. The analytical calculation results of the new probability function of void nucleation are consistent not only with the results of the variation of void number with time calculated by molecular dynamics, but also with the experimental results of tantalum spallation in the early stage of damage development, that is to say, the new probability function of void nucleation can reflect the variation law of micro-void distribution characteristics in the early stage of spallation damage to a certain extent.
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图 2 孤立孔洞数随时间的变化
Figure 2. Number of independent voids as a function of time from MD data and our work.
图 3 所有的孔洞数随时间的变化
Figure 3. Number of sum of independent voids and void cluster as a function of time from MD data and our work.
图 4 孔洞体积份额(损伤度)随时间的变化
Figure 4. Void volume fraction as a function of time from MD data and our work.
图 5 孔洞数累积百分比随孔洞大小的变化规律
Figure 5. Cumulative percentage of void number as a void size
图 6 孔洞数累积百分比随时间的变化规律
Figure 6. Cumulative percentage of void number as a function of time.
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