Researchers release CP-Agent for automated crystal plasticity simulations
Researchers introduced CP-Agent, an AI agent designed to automate crystal plasticity (CP) simulations for metals. The tool uses natural language to execute full workflows, including configuring tools, managing data pipelines, and calibrating parameters against experimental data. Developed under the ReAct paradigm, CP-Agent combines reasoning with established numerical optimizers while embedding…
Key points
- CP-Agent automates crystal plasticity simulations for metals using natural language inputs and ReAct paradigm
- Tool embeds domain knowledge in tool schemas, not hard-coded logic, for flexibility and interpretability
- Validated on four case studies, including stainless steel calibration and copper texture recovery
The agent was tested on four case studies: calibrating slip parameters for stainless steel 316L, validating workflows against published copper benchmarks, recovering initial crystallographic texture, and simulating multi-pass rolling texture evolution in a Mg-Zn-Ca alloy. In each case, CP-Agent correctly inferred execution sequences, delivered physically interpretable results, and maintained reproducibility across repeated runs. The study positions harness engineering as a scalable approach to automating complex simulations while preserving auditability through visible reasoning traces.
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