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Figure 1: Embrittled grain boundary networks are an example of
heterogeneous random materials. Randomness comes from different
strength properties of various grain boundaries (special boundaries as
Sigma 3, Sigma 9, or random). The location of the fracture surfaces
is predicted using efficient graph-theoretical optimization
algorithm [1], and compared with actual surfaces from embrittled
polycrystalline materials, such as bismuth-embrittled copper.
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Fractality of Fracture Surfaces in Polycrystalline MaterialsEira T. Seppälä, Bryan Reed, Mukul Kumar and Robert E. Rudd | |||
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In this joint project with experimentalists from
CMS/MSTD
fracture surfaces of embrittled polycrystalline materials, such as
pure aluminum and bismuth-embrittled copper, are studied both by
computations and experimentally. In statistical mechanics fracture
surfaces of random media have attracted considerable interest due to
their self-affine scaling properties with a characteristic exponent,
zeta. Grain boundary networks are constructed computationally by matching
empirical special boundary fractions (e.g. of Sigma 3, Sigma 9, or
random types) and triple junction distributions which have been
obtained from electron backscatter diffraction (EBSD) data using
scanning electron microscopy (SEM) [2]. The minimum energy paths
through the dual networks of the grain boundary structures are
searched, where the edges of the networks are assigned with strength
values depending on the type of the grain boundary. These minimum
energy paths serve as predicted cracks through the samples [1].
Finally such properties as roughness, special boundaries belonging to
the cracks, etc., of the surfaces of the simulated networks with the
properties from actual fracture surfaces in polycrystalline materials
are compared.
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EOS & Materials Theory | Condensed Matter Physics | Physics & Adv. Tech. | LLNL |
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Maintained by Robert E. Rudd -- Last updated on 7 March 2007. |
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