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Figure 5 Anisotropic propagation of correlations in 2D.
In two dimensions, the propagation of correlations is anisotropic with the velocity being minimal along the lattices axes and maximal along the diagonals.
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Development of the forward propagation approach then allows propagation of correlation uncertainty in the reverse direction from the free substructure into the fixed interface based Craig Bampton representation.
Then, for a given direction in k-space, the maximum group velocity v max = max ∇ k ω k determines the maximum propagation speed of correlations, i.e., the effective light cone.
As in the one-dimensional setup, we see again a revival of oscillations of p μ ( n ) after the propagation of the correlations through the whole lattice.
We find that the time evolution of the local particle-number distribution p μ ( n ) is directly related to the propagation of the correlations 〈 b ˆ 1 † b ˆ 2 〉.
The approach gives insight into the propagation of the correlation between c and ϕ through their joint probability into the reliability analysis, and their influence on the calculated reliability of the rock slope.
Transverse directional correlation length also showed good correlation with propagation of micropitting, with the correlation length decreasing during increase of micropitting on sample surfaces.
Based on the damage propagation of the plate and the correlation among three parameters including the residual strains, three damage levels of composite plates were classified.
In this paper, an approach is provided for teaching uncertainty propagation as part of a larger process engineering statistics course, applying analytical and numerical propagation principles, including consideration of correlation in inputs.
In WT STA cell 2, the correlation was laterally propagating, indicating the lateral propagation of pseudopodia (rotation pattern).
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