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Research on Material Stress Strain Curve Prediction Methods Based on Transfer Learning and Artificial Intelligence Chongqing Jiaotong University
- Format:
- Book
- Conference/Event
- Author/Creator:
- Zou, Jie, author.
- Conference Name:
- WCX SAE World Congress Experience (2025-04-08 : Detroit, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2025
- Summary:
- The mechanical properties of materials play a crucial role in real life. However, methods to measure these properties are usually time-consuming and labour intensive. Small Punch Through (SPT) has non-destructive characteristics and can obtain load-displacement curves of specimens, but it cannot visually extract the mechanical properties of materials. Therefore, we designed a proprietary SPT experiment and fixture, built a finite element method (FEM) model and developed a multi-fidelity model capable of predicting the mechanical properties of steel and aluminium alloys. It makes use of multi-fidelity datasets obtained from SPT and FEM simulation experiments, and this integration allows us to support and optimize the predictive accuracy of the study, thus ensuring a comprehensive and reliable characterization of the mechanical properties of the materials. The model also takes into account variations in material thickness and can effectively predict the mechanical properties of materials with different thicknesses
- Notes:
- Vendor supplied data
- Publisher Number:
- 2025-01-8317
- Access Restriction:
- Restricted for use by site license
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