A generalized void closure model in hot forging process of superalloys
This study proposes a void closure prediction model applicable to hot forging processes. The void closure under various stress states was evaluated using a Representative Volume Element (RVE) model, and the effects of different materials and initial temperatures on the void closure were analyzed. To represent the volumetric behavior of voids, the void closure prediction model was represented in an evolutionary manner as a function of equivalent plastic strain, effective stress, stress triaxiality, and Lode parameter. The coefficients in the model were fitted through the RVE model analysis, and the void closure prediction model was subsequently applied to multiple voids. To validate the applicability of the proposed model, compression tests were performed using rectangular prism-shaped specimens with hemispherical voids inside, and the radius ratios from the experiments were compared with those from simulations. Additionally, the void volume closure was simulated using FEA (Finite Element Analysis) and was compared with the proposed model, demonstrating the ability of the model to accurately predict the volumes of voids located at various locations. Finally, the model was integrated into FEA simulations, enabling the determination of the compression ratio or strain required to completely close voids. This demonstrates the applicability of the proposed model in hot forging processes.
Authors
- Joonhee Park (ORCID: https://orcid.org/0000-0003-4146-8980)
- Naksoo Kim (ORCID: https://orcid.org/0000-0003-3844-0661)
- I. Kim
- Jong‐Sik Kim (ORCID: https://orcid.org/0000-0003-2248-2576)
- S. H. Oh
Institutions
- Sogang University (KR)
- Kyungil University (KR)
- Hanwha Solutions (South Korea) (KR)
Publication Details
- Journal
- Journal of Materials Research and Technology
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1016/j.jmrt.2025.04.201
- Citations
- 1
- Primary Topic
- Metallurgy and Material Forming
- Type
- article
- Field-Weighted Citation Impact
- 0.86