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Article

Parameters Identification of Rubber-like Hyperelastic Material Based on General Regression Neural Network

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State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an 710049, China
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Research Institute of Xi’an Jiaotong University, Hangzhou 311215, China
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Xi’an Jiaotong University Suzhou Institute, Suzhou 215123, China
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Xi’an Modern Chemistry Research Institute, Xi’an 710065, China
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The 41st Institute of the Forth Academy of CASC, Xi’an 710025, China
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Solid Rocket Motor National Key Laboratory of Combustion Flow and Thermo-Structure, Xi’an 710025, China
*
Author to whom correspondence should be addressed.
Academic Editor: Enrique Casarejos
Materials 2022, 15(11), 3776; https://doi.org/10.3390/ma15113776
Received: 26 April 2022 / Revised: 19 May 2022 / Accepted: 23 May 2022 / Published: 25 May 2022
(This article belongs to the Section Mechanics of Materials)
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. View Full-Text
Keywords: general regression neural network (GRNN); hyperelastic material model; parameters identification general regression neural network (GRNN); hyperelastic material model; parameters identification
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MDPI and ACS Style

Hou, J.; Lu, X.; Zhang, K.; Jing, Y.; Zhang, Z.; You, J.; Li, Q. Parameters Identification of Rubber-like Hyperelastic Material Based on General Regression Neural Network. Materials 2022, 15, 3776. https://doi.org/10.3390/ma15113776

AMA Style

Hou J, Lu X, Zhang K, Jing Y, Zhang Z, You J, Li Q. Parameters Identification of Rubber-like Hyperelastic Material Based on General Regression Neural Network. Materials. 2022; 15(11):3776. https://doi.org/10.3390/ma15113776

Chicago/Turabian Style

Hou, Junling, Xuan Lu, Kaining Zhang, Yidong Jing, Zhenjie Zhang, Junfeng You, and Qun Li. 2022. "Parameters Identification of Rubber-like Hyperelastic Material Based on General Regression Neural Network" Materials 15, no. 11: 3776. https://doi.org/10.3390/ma15113776

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