Speaker
Description
Ductile damage is a major concern in hot forming processes, particularly in hot rolling, where it can compromise the mechanical integrity and performance of the final product. This work aims to minimize ductile damage risks in as-rolled bars through a combined approach of process optimization and advanced damage modeling. The optimization is carried out using Forge®, a simulation platform developed by Transvalor, employing its automatic optimization module to refine key process parameters.
To accurately predict damage, a new ductile damage model is introduced. Unlike conventional models that primarily rely on stress triaxiality and the Lode parameter, the proposed formulation integrates the evolution of material ductility as a function of temperature. Since ductility varies significantly with thermal conditions, this dependency plays a critical role in damage initiation and progression during hot rolling. Incorporating this effect enables a more realistic representation of material behavior under severe thermo-mechanical loading.
The study presents a practical case of hot rolling optimization using the enhanced damage model. A detailed description of the optimization workflow, the theoretical basis of the damage model, and the implementation of temperature-dependent ductility within the simulation environment is provided. Results highlight the benefits of coupling automated optimization with advanced damage prediction, demonstrating a substantial reduction in damage indicators and improved product quality.
This approach offers a robust framework for industrial applications, enabling manufacturers to design processes that balance productivity and material integrity. The integration of ductility evolution into damage modeling represents a significant step toward more accurate and reliable predictions in hot forming operations.
| Speaker Company/University | ArcelorMittal |
|---|