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About this Abstract
Meeting	2025 TMS Annual Meeting & Exhibition
Symposium	Artificial Intelligence Applications in Integrated Computational Materials Engineering
Presentation Title	A Multiscale Simulation Framework for Incremental Deformation Processing Using a Recurrent Neural Network Surrogate Model for Crystal Plasticity
Author(s)	John S. Weeks, Aaron Stebner
On-Site Speaker (Planned)	John S. Weeks
Abstract Scope	Incremental deformation processing using precise robotic control offers the capability to produce tailored local microstructure and material properties within engineering components. However, proper modeling of anisotropic behavior in polycrystalline metals during deformation processing is necessary to attain these targeted local properties. Concurrent multiscale models using crystal plasticity can accurately capture and track texture evolution of relevant scale components but are typically computationally expensive due to the required evaluation of both micro- and macro-scale models. In this work, we use a recurrent neural network as a surrogate model for a visco-plastic self-consistent crystal plasticity model (VPSC8) and integrate this into a macroscale finite element framework (ABAQUS/Explicit). Quantities such as forming forces, plastic strains, residual stresses, and texture are investigated for an incremental forming process of varying toolpaths. We demonstrate an efficient multiscale model which allows for trade study evaluation and increased understanding of microstructure evolution during incremental deformation processing to help guide future techniques in the field.
Proceedings Inclusion?	Planned:
Keywords	Modeling and Simulation, ICME, Shaping and Forming

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