[1]董建材,刘 洋,徐 福,等.大应变条件下金属橡胶刚度特性建模及预测[J].机械与电子,2025,(09):3-9.
　DONG Jiancai,LIU Yang,XU Fu,et al.Modeling and Prediction of Stiffness Characteristics of Metal Rubber under Large Strain Conditions[J].Machinery & Electronics,2025,(09):3-9.
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大应变条件下金属橡胶刚度特性建模及预测
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2025年09期
页码:
3-9
栏目:
研究与设计
出版日期:
2025-09-25

文章信息/Info

Title:
Modeling and Prediction of Stiffness Characteristics of Metal Rubber under Large Strain Conditions
文章编号:
1001-2257 ( 2025 ) 09-0003-07
作者:
董建材; 刘 洋; 徐 福; 李家磊; 阳 红
中国工程物理研究院机械制造工艺研究所,四川 绵阳 621000
Author(s):
DONG Jiancai ;  LIU Yang ;  XU Fu ;  LI Jialei ;  YANG Hong
( Institute of Mechanical Manufacturing Processes , China Academy of Engineering Physics , Mianyang 621000 , China )
关键词:
高动态离心环境; 金属橡胶; 微元弹簧模型; 神经网络; 大应变
Keywords:
high-dynamic centrifugal environment ;  metal rubber ;  micro-unit spring model ;  neural network ;  large-strain
分类号:
TQ336.4 ;TP183
文献标志码:
A
摘要:
针对高动态离心环境,即大应变(应变 >10% )工况作用下,金属橡胶进入硬特性区,刚度指标呈现指数级增加,传统金属橡胶刚度特性的建模均研究关注小应变(应变 ≤10% )条件,无法有效应对大应变(应变 >10% )条件下金属橡胶刚度特性的高精度建模需求的问题,面向金属橡胶的建模和预测需求,提出分别建立微元弹簧模型和基于材料本构的神经网络模型实现大应变条件下金属橡胶刚度特性的准确预测,引入非线性过渡函数及横观各项同性本构描述金属橡胶大应变条件下的非线性行为。仿真和实验结果表明,建立的微元弹簧模型能够较准确地基于成型过程描述大应变条件下的刚度特性,且建立的神经网络模型能够准确地基于训练数据描述大应变条件下的刚度特性,满足金属橡胶高动态离心工况下对预测精度的需求。
Abstract:
Under high-dynamic centrifugal environments , specifically under large-strain working conditions ( strain >10% ), metal rubber enters a hardening characteristic zone where stiffness indices exhibit exponential growth.Traditional modeling studies on metal rubber stiffness characteristics have focused on small-strain conditions ( strain ≤10% ), failing to effectively address the high-precision modeling requirements for metal rubber stiffness characteristics under large-strain conditions ( strain >10% ) . To meet the modeling and prediction demands of metal rubber , this study proposes establishing separate micro-unit spring models and neural network models based on material constitutive relationships to achieve accurate prediction of metal rubber stiffness characteristics under large-strain conditions.Nonlinear transition functions and transversely isotropic constitutive descriptions are introduced to characterize the nonlinear behavior of metal rubber under large-strain conditions.Simulation and experimental results demonstrate that the established micro-unit spring model can effectively describe stiffness characteristics under large strain conditions based on forming process parameters , while the developed neural network model accurately captures stiffness characteristics under large-strain conditions through training data , satisfying the precision requirements for metal rubber predictions in high-dynamic centrifugal working conditions.

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备注/Memo

备注/Memo:
收稿日期: 2025-04-08
基金项目:国 家 重 点 研 发 计 划 ( 2022YFF070900 );国家自然科学基金资助项目 ( 52205543 );四川省自然科学基金资助项目( 24NSFSC0989 );科技部重点研发计划( 2023YFB4606202 , 2023YFB3405800 )
作者简介:董建材 ( 2001- ),男,河北邢台人,硕士研究生,研究方向为金属减振器仿真设计;刘 洋 ( 1993- ),男,河北东光人,副研究员,研究方向为精密光电装备减振致稳,通信作者, E-mail : y.liu@mail.nwpu.edu.cn 。
更新日期/Last Update: 2025-09-29