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Simulation of Fragmentation with Material Point Method Based on Gurson Model and Random Failure

by Pengfei Yang1, Yan Liu1, Xiong Zhang1, Xu Zhou3, Yuli Zhao3

School of Aerospace, Tsinghua University, Beijing 100084, China.
Corresponding author: xzhang@tsinghua.edu.cn
Beijing Institute of Special Engineering Design and Research, Beijing 100028, China.

Computer Modeling in Engineering & Sciences 2012, 85(3), 207-238. https://doi.org/10.3970/cmes.2012.085.207

Abstract

The material point method is extended to the simulations of fragmentation driven by detonation. A crack modeling scheme based on contact algorithm with material failure process is developed to study the dynamic crack propagation in plastic media. When considering microscopic damage of material, the plastic behavior is described by Gurson model with randomly-distributed initial void of material points. Gurson model can degenerate to J2 plastic theory while the microscopic void is ignored, in which situation the Weibull random failure scheme will be used. Meanwhile, a background-grid-based searching method is proposed to capture the statistical feature of the fragmentation. The scaling of the fragments in simulation tends to exhibit the same law as that in the experiment. It is found that the material point method possesses great potential for simulating high strain-rate, large deformation fragmentation phenomena.

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APA Style
Yang, P., Liu, Y., Zhang, X., Zhou, X., Zhao, Y. (2012). Simulation of fragmentation with material point method based on gurson model and random failure. Computer Modeling in Engineering & Sciences, 85(3), 207-238. https://doi.org/10.3970/cmes.2012.085.207
Vancouver Style
Yang P, Liu Y, Zhang X, Zhou X, Zhao Y. Simulation of fragmentation with material point method based on gurson model and random failure. Comput Model Eng Sci. 2012;85(3):207-238 https://doi.org/10.3970/cmes.2012.085.207
IEEE Style
P. Yang, Y. Liu, X. Zhang, X. Zhou, and Y. Zhao, “Simulation of Fragmentation with Material Point Method Based on Gurson Model and Random Failure,” Comput. Model. Eng. Sci., vol. 85, no. 3, pp. 207-238, 2012. https://doi.org/10.3970/cmes.2012.085.207



cc Copyright © 2012 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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