.png){kind=icon}
返回
Multi-Scale Anisotropic Yield Function Based on Neural Network Model
.png){kind=icon}
OA
AI
DOI：10.3390/ma18030714.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The increasingly complex form of traditional anisotropic yield functions brings difficulties to parameter calibration and finite element application, and it is necessary to establish a unified paradigm model for engineering applications. In this study, four traditional models were used to calibrate the anisotropic behavior of a 2090-T3 aluminum alloy, and the corresponding yield surfaces in sigma xx,sigma yy,sigma xy and alpha,beta,r spaces were studied. Then, alpha and beta are selected as input variables, and r is regarded as an output variable to improve the prediction and generalization capabilities of the fully connected neural network (FCNN) model. The prediction results of the FCNN model are finally compared to the calibration results of the traditional model, and the reliability of the FCNN model to predict the anisotropy is verified. Then, the data sets with different stress states and loading directions are generated through crystal plasticity finite element simulation, and the yield surface is directly predicted by the FCNN model. The results show that the FCNN model can accurately reflect the anisotropic characteristics. The anisotropic yield function based on the FCNN model can cover the characteristics of all traditional models in one subroutine, which greatly reduces the difficulty of subroutine development. Moreover, the finite element subroutine based on the FCNN model can model anisotropic behaviors.
Keyword:
neural network
anisotropic yield function
multi-scale modeling
crystal plasticity
finite element analysis
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.2
论文数:
5.7W
被引数:
15.1W
机构
引用论文
Foraminifera from the Maastrichtian phosphate-bearing strata of El Hasa, Jordan约旦El Hasa马斯特里赫特阶含磷地层中的有孔虫
.png){kind=icon}
PREAI
分享收藏Chondrodermatitis Nodularis Chronica Auriculae耳部慢性软骨皮炎结节性 [Chondrodermatitis Nodularis Chronica Auriculae]OAAI
OAAI分享收藏A machine learning framework to predict local strain distribution and the evolution of plastic anisotropy & fracture in additively manufactured alloys一种机器学习框架，用于预测局部应变分布以及增材制造合金中塑性各向异性和断裂的演变
PREAI
分享收藏Machine learning-driven stress integration method for anisotropic plasticity in sheet metal forming基于机器学习的板料成形各向异性塑性应力积分方法
PREAI
分享收藏
查看更多内容