Reduced-Order Modeling of the Deformation Response of Polycrystalline Aggregates
Abstract
Modeling the crystal-scale deformation of polycrystalline aggregates is computationally costly. Cheaper models are necessary to crystal-scale behavior in simulations of large-scale engineering components in aerospace assets. Here, a computational framework to develop reduced order crystal plasticity models to describe the deformation response of polycrystalline aggregates has been developed. This was achieved through training a convex neural network via large datasets generated from crystal plasticity finite element simulations. This framework has been demonstrated by creating a computationally inexpensive model which relates the state of the material to its macroscopic yield behavior. Data from the reduced order model was qualitatively compared against simulated data, with robust correlation. The framework was developed to be extendable to consider increasingly complex material descriptions to further the generality, accuracy, and precision in its predictions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 14, 2022
- Accession Number
- AD1176714
Entities
People
- Matthew Kasemer
Organizations
- University of Alabama