Fig. 2: Low-dimensional representation of the microstructure evolution. | npj Computational Materials

Fig. 2: Low-dimensional representation of the microstructure evolution.

From: Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Fig. 2

a Transformation of a two-phase microstructure realization (top row) to its autocorrelation representation (middle row: autocorrelation; bottom row: radial average) at three separate frames (t0, t10, and t100). b Microstructure evolution trajectories over 100 frames represented as a function of the first three principal components. c Cumulative variance explained as a function of the number of principal components included in the representation of the microstructure.

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