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A Data-driven Multiscale Analysis for Hyperelastic Composite Materials Based on the Mean-field Homogenization Method
- Kim, Suhan;
- Lee, Wonjoo;
- Shin, Hyunseong
WEB OF SCIENCE
0초록
The classical multiscale finite element (FE2) method involves iterative calculations of micro-boundary value problems for representative volume elements at every integration point in macro scale, making it a computationally time and data storage space. To overcome this, we developed the data-driven multiscale analysis method based on the mean-field homogenization (MFH). Data-driven computational mechanics (DDCM) analysis is a model-free approach that directly utilizes strain-stress datasets. For performing multiscale analysis, we efficiently construct a strain-stress database for the microstructure of composite materials using mean-field homogenization and conduct data-driven computational mechanics simulations based on this database. In this paper, we apply the developed multiscale analysis framework to an example, confirming the results of data-driven computational mechanics simulations considering the microstructure of a hyperelastic composite material. Therefore, the application of data-driven computational mechanics approach in multiscale analysis can be applied to various materials and structures, opening up new possibilities for multiscale analysis research and applications.
키워드
- 제목
- A Data-driven Multiscale Analysis for Hyperelastic Composite Materials Based on the Mean-field Homogenization Method
- 저자
- Kim, Suhan; Lee, Wonjoo; Shin, Hyunseong
- 발행일
- 2023-10
- 유형
- Article
- 권
- 36
- 호
- 5
- 페이지
- 329 ~ 334