Applied Mathematics Seminar: Solving and learning phase field models using the modified Physics Informed Neural Networks

Speaker: Jia Zhao, Assistant Professor Department of Math & Statistics, USU

Abstract: Phase field models, including the Allen-Cahn type and Cahn- Hilliard type equations, have been widely used to investigate interfacial dynamic problems. Designing accurate, efficient, and stable numerical algorithms for solving the phase field models has been an active field for decades. In the meanwhile, developing reliable and physically consistent phase field models for applications in science and engineering have also been intensively investigated. In this talk, I will introduce some preliminary results on solving and learning phase field models using deep neural networks.

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