IMECH-IR

Browse/Search Results:  1-9 of 9 Help

Filters    
Selected(0)Clear Items/Page:    Sort:
颗粒的高通量微流动操控机理研究 学位论文
博士论文,北京: 中国科学院大学, 2021
Authors:  苏敬宏
Adobe PDF(7268Kb)  |  Favorite  |  View/Download:318/6  |  Submit date:2022/01/12
微流动  颗粒操控  非球形效应  惯性升力  弹性-惯性迁移  
Physics-driven machine learning model on temperature and time-dependent deformation in lithium metal and its finite element implementation 期刊论文
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS, 2021, 卷号: 153, 页码: 104481
Authors:  Wen JC(温济慈);  Zou, Qingrong;  Wei YJ(魏宇杰)
Adobe PDF(3559Kb)  |  Favorite  |  View/Download:285/73  |  Submit date:2022/10/25
Physics-driven machine learning  Lithium-metal anode  Creep  Finite-element analysis  Constitutive model  
基于数据驱动的湍流和空化流动数值模拟研究 学位论文
博士论文,北京: 中国科学院大学, 2021
Authors:  张珍
Adobe PDF(21508Kb)  |  Favorite  |  View/Download:806/23  |  Submit date:2021/06/09
数据驱动  雷诺平均  神经网络  差异模型  空化流动  隐式修正  
微纳尺度下溶解流动的物理力学研究 学位论文
博士论文,北京: 中国科学院大学, 2021
Authors:  苗青
Adobe PDF(8137Kb)  |  Favorite  |  View/Download:389/16  |  Submit date:2021/06/04
溶解流动、动边界、受限流体、结构演化、标度律  
高超声速气动热实验数据的多层学习方法 学位论文
硕士论文,北京: 中国科学院大学, 2021
Authors:  陈正
Adobe PDF(14953Kb)  |  Favorite  |  View/Download:271/14  |  Submit date:2021/06/04
气动热  实验数据  小样本  特征工程  多层学习  
Machine learning assisted fast prediction of inertial lift in microchannels 期刊论文
LAB ON A CHIP, 2021, 页码: 13
Authors:  Su JH(苏敬宏);  Chen XD(陈晓东);  Zhu YZ(朱勇铮);  Hu GQ(胡国庆)
Adobe PDF(7711Kb)  |  Favorite  |  View/Download:438/118  |  Submit date:2021/06/07
基于人工神经网络的物性预测与反应流场重构研究 学位论文
博士论文,北京: 中国科学院大学, 2021
Authors:  李波
Adobe PDF(14001Kb)  |  Favorite  |  View/Download:556/13  |  Submit date:2021/06/02
计算流体力学,人工神经网络,真实气体物性预测,全流场重构,燃烧热释放速率重构  
Reconstruction model for heat release rate based on artificial neural network 期刊论文
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2021, 卷号: 46, 期号: 37, 页码: 19599-19616
Authors:  Li B(李波);  Yao W(姚卫);  Li YC(李亚超);  Fan XJ(范学军)
Adobe PDF(5169Kb)  |  Favorite  |  View/Download:136/38  |  Submit date:2022/10/25
Heat release rate (HRR)  Artificial neural network (ANN)  Proper orthogonal -12omposition (POD)  Chemiluminescence  Supersonic hydrogen flame  
Prediction and evaluation of plasma arc reforming of naphthalene using a hybrid machine learning model 期刊论文
JOURNAL OF HAZARDOUS MATERIALS, 2021, 卷号: 404, 页码: 10
Authors:  Wang, Yaolin;  Liao, Zinan;  Mathieu, Stephanie;  Bin F(宾峰);  Tu, Xin
Adobe PDF(7145Kb)  |  Favorite  |  View/Download:327/110  |  Submit date:2021/03/03
Machine learning  Non-thermal plasma  Biomass gasification  Tar reforming  Naphthalene