دورية أكاديمية
Parameters Identification of Rubber-like Hyperelastic Material Based on General Regression Neural Network
| العنوان: | Parameters Identification of Rubber-like Hyperelastic Material Based on General Regression Neural Network |
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| المؤلفون: | Junling Hou, Xuan Lu, Kaining Zhang, Yidong Jing, Zhenjie Zhang, Junfeng You, Qun Li |
| المصدر: | Materials, Vol 15, Iss 11, p 3776 (2022) |
| بيانات النشر: | MDPI AG, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Technology LCC:Electrical engineering. Electronics. Nuclear engineering LCC:Engineering (General). Civil engineering (General) LCC:Microscopy LCC:Descriptive and experimental mechanics |
| مصطلحات موضوعية: | general regression neural network (GRNN), hyperelastic material model, parameters identification, Technology, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Engineering (General). Civil engineering (General), TA1-2040, Microscopy, QH201-278.5, Descriptive and experimental mechanics, QC120-168.85 |
| الوصف: | In this study, we present a systematic scheme to identify the material parameters in constitutive model of hyperelastic materials such as rubber. This approach is proposed based on the combined use of general regression neural network, experimental data and finite element analysis. In detail, the finite element analysis is carried out to provide the learning samples of GRNN model, while the results observed from the uniaxial tensile test is set as the target value of GRNN model. A problem involving parameters identification of silicone rubber material is described for validation. The results show that the proposed GRNN-based approach has the characteristics of high universality and good precision, and can be extended to parameters identification of complex rubber-like hyperelastic material constitutive. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1996-1944 |
| Relation: | https://www.mdpi.com/1996-1944/15/11/3776; https://doaj.org/toc/1996-1944 |
| DOI: | 10.3390/ma15113776 |
| URL الوصول: | https://doaj.org/article/98a3cf7bc11a41eb8df6985e14b52ae7 |
| رقم الأكسشن: | edsdoj.98a3cf7bc11a41eb8df6985e14b52ae7 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19961944 |
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| DOI: | 10.3390/ma15113776 |