fig3

Accelerating phase-field simulation of coupled microstructural evolution using autoencoder-based recurrent neural networks

Figure 3. Performance of autoencoder in reducing and reconstructing coupled microstructures. Reduced and reconstructed microstructure of five coupled fields for a representative Oswald ripening simulation at (A) t = t1, (B) t = t10, and (C) t = t100; (D) Four selected feature values of reduced microstructures are plotted as a function of 100 time frames for each field. The variations of these feature values in the latent space can reflect the real microstructural evolution in the original space based on manifold hypothesis. For instance, the microstructural stability at a certain time frame (e.g., flat curves) in the latent space is equivalent to the stability at that same time frame in the original 2D space. 2D: Two-dimensional.

Journal of Materials Informatics
ISSN 2770-372X (Online)
Follow Us

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/