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Isogeometric Convolution Hierarchical Deep-learning Neural Network: Isogeometric analysis with versatile adaptivity 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2023, 卷号: 417, 页码: 46
作者:  Zhang L(张磊);  Park, Chanwook;  Lu, Ye;  Li, Hengyang;  Mojumder, Satyajit;  Saha, Sourav;  Guo, Jiachen;  Li, Yangfan;  Abbott, Trevor;  Wagner, Gregory J.;  Tang, Shaoqiang;  Liu, Wing Kam
Adobe PDF(9021Kb)  |  收藏  |  浏览/下载：66/2  |  提交时间：2024/01/08
Convolution isogeometric analysis (C-IGA)  Convolution hierarchical deep-learning neural network (C-hiDeNN)  Software 2.0  r-h-p-s-a adaptive finite element method (FEM)  High-order smoothness and convergence  
Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning 期刊论文
INTERNATIONAL JOURNAL OF APPLIED MECHANICS, 2023, 卷号: 15, 期号: 9, 页码: 2350078
作者:  Zhou R(周睿);  Xu XH(许向红)
Adobe PDF(1896Kb)  |  收藏  |  浏览/下载：62/1  |  提交时间：2023/10/23
Contact force of pantograph-catenary system  selective crow search algorithm  surrogate model  multi-parameter optimization  
A computational method for the load spectra of large-scale structures with a data-driven learning algorithm 期刊论文
SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2023, 卷号: 66, 期号: 1, 页码: 141-154
作者:  Chen XJ(陈贤佳);  Yuan, Zheng;  Li, Qiang;  Sun, ShouGuang;  Wei YJ(魏宇杰)
Adobe PDF(2512Kb)  |  收藏  |  浏览/下载：257/80  |  提交时间：2023/02/09
load spectrum  computational mechanics  deep learning  data-driven modeling  gated recurrent unit neural network  
Machine Learning Method for Fatigue Strength Prediction of Nickel-Based Superalloy with Various Influencing Factors 期刊论文
MATERIALS, 2023, 卷号: 16, 期号: 1, 页码: 13
作者:  Guo, Yiyun;  Rui SS(芮少石);  Xu, Wei;  Sun CQ(孙成奇)
Adobe PDF(9664Kb)  |  收藏  |  浏览/下载：76/0  |  提交时间：2023/02/09
machine learning  nickel-based superalloy  fatigue strength prediction  temperature  stress ratio  
Deep learning method for the super-resolution reconstruction of small-scale motions in large-eddy simulation 期刊论文
AIP ADVANCES, 2022, 卷号: 12, 期号: 12, 页码: 9
作者:  Zhao QY(赵庆义);  Jin GD(晋国栋);  Zhou ZD(周志登)
Adobe PDF(10288Kb)  |  收藏  |  浏览/下载：135/37  |  提交时间：2023/02/03
Artificial neural network based response surface for data-driven dimensional analysis 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 卷号: 459, 页码: 19
作者:  Xu ZY(许昭越);  Zhang XL(张鑫磊);  Wang SZ(王士召);  He GW(何国威)
Adobe PDF(2241Kb)  |  收藏  |  浏览/下载：346/33  |  提交时间：2022/07/18
Artificial neural network  Response surface  Data-driven dimensional analysis  Machine learning  Fluid-structure interaction  
Defining kerogen maturity from orbital hybridization by machine learning 期刊论文
FUEL, 2022, 卷号: 310, 页码: 10
作者:  Ma J(马俊);  Kang DL(康东亮);  Wang XH(王晓荷);  Zhao YP(赵亚溥)
Adobe PDF(4071Kb)  |  收藏  |  浏览/下载：284/60  |  提交时间：2021/11/29
Kerogen maturity  Orbital hybridization  Machine learning  Quantum chemistry  
A Direct-Forcing Immersed Boundary Method for Incompressible Flows Based on Physics-Informed Neural Network 期刊论文
Fluids, 2022, 卷号: 7, 期号: 2, 页码: 56
作者:  Huang Y(黄毅);  Zhang ZY(张治愚);  Zhang X(张星)
Adobe PDF(6539Kb)  |  收藏  |  浏览/下载：361/84  |  提交时间：2022/01/27
physics-informed neural networks (PINN)  direct-forcing immersed boundary method  incompressible laminar flow  circular cylinder  
Assessment of Regularized Ensemble Kalman Method for Inversion of Turbulence Quantity Fields 期刊论文
AIAA JOURNAL, 2022, 卷号: 60, 期号: 1, 页码: 3-13
作者:  Zhang XL(张鑫磊);  Xiao, Heng;  He GW(何国威)
Adobe PDF(1913Kb)  |  收藏  |  浏览/下载：214/60  |  提交时间：2022/01/24
Flexible Electronics: Theory and Method of Structural Design 专著
Wuhan; Beijing; Xi'an:Springer Nature, 2022
作者:  Huang, YongAn;  Su YW(苏业旺);  Jiang, Shan
Adobe PDF(20110Kb)  |  收藏  |  浏览/下载：99/1  |  提交时间：2023/03/23