Inverse Identification of Constitutive Model for GH4198 Based on Genetic–Particle Swarm Algorithm
A precise Johnson-Cook (J-C) constitutive model is the foundation for precise calculation of finite-element simulation. In order to obtain the J-C constitutive model accurately for a new cast and forged alloy GH4198, an inverse identification of J-C constitutive model was proposed based on a genetic-particle swarm algorithm. Firstly, a quasi-static tensile test at different strain rates was conducted to determine the initial yield strength <i>A</i>, strain hardening coefficient <i>B</i>, and work hardening exponent <i>n</i> for the material's J-C model. Secondly, a new method for orthogonal cutting model was constructed based on the unequal division shear theory and considering the influence of tool edge radius. In order to obtain the strain-rate strengthening coefficient <i>C</i> and thermal softening coefficient <i>m</i>, an orthogonal cutting experiment was conducted. Finally, in order to validate the precision of the constitutive model, an orthogonal cutting thermo-mechanical coupling simulation model was established. Meanwhile, the sensitivity of J-C constitutive model parameters on simulation results was analyzed. The results indicate that the parameter <i>m</i> significantly affects chip morphology, and that the parameter <i>C</i> has a notable impact on the cutting force. This study addressed the issue of missing constitutive parameters for GH4198 and provided a theoretical reference for the optimization and identification of constitutive models for other aerospace materials.
Authors
- Qichao Jin (ORCID: https://orcid.org/0000-0001-7085-4923)
- Rui Fu (ORCID: https://orcid.org/0009-0007-3873-2898)
- Hongyu Yu (ORCID: https://orcid.org/0000-0002-6899-9346)
- Jun Li (ORCID: https://orcid.org/0000-0002-6239-2922)
- Lei Guo
- Fulin Li (ORCID: https://orcid.org/0000-0001-8731-8828)
Institutions
- Chang'an University (CN)
- Aero Engine Corporation of China (China) (CN)
Publication Details
- Journal
- Materials
- Published
- 2024-08-29
- DOI
- https://doi.org/10.3390/ma17174274
- Citations
- 2
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.43
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shaanxi Province