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中国科学院力学研究所机构知识库
Knowledge Management System of Institue of Mechanics, CAS
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Defining kerogen maturity from orbital hybridization by machine learning
期刊论文
FUEL, 2022, 卷号: 310, 页码: 10
Authors:
Ma J(马俊)
;
Kang DL(康东亮)
;
Wang XH(王晓荷)
;
Zhao YP(赵亚溥)
Adobe PDF(4071Kb)
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View/Download:266/54
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Submit date:2021/11/29
Kerogen maturity
Orbital hybridization
Machine learning
Quantum chemistry
Wall-model integrated computational framework for large-eddy simulations of wall-bounded flows
期刊论文
PHYSICS OF FLUIDS, 2021, 卷号: 33, 期号: 12, 页码: 10
Authors:
Lv Y(吕钰)
;
Huang XLD
;
Yang XL(杨晓雷)
;
Yang XIA
Adobe PDF(3695Kb)
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Submit date:2022/01/24
Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks
期刊论文
EXPERT SYSTEMS, 2021, 卷号: 38, 期号: 7, 页码: 11
Authors:
Wang, Shuwen
;
Yan, Hao
;
Liu, Caixia
;
Fan, Ning
;
Liu XM(刘小明)
;
Wang, Chengguo
Adobe PDF(1092Kb)
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Submit date:2021/11/01
BP neural networks
high-speed train
SIMPACK
wheel wear
Reynolds number effect on statistics of turbulent flows over periodic hills
期刊论文
PHYSICS OF FLUIDS, 2021, 卷号: 33, 期号: 10, 页码: 28
Authors:
Zhou ZD(周志登)
;
Wu T(吴霆)
;
Yang XL(杨晓雷)
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Submit date:2022/01/13
Predicting the components and types of kerogen in shale by combining machine learning with NMR spectra
期刊论文
FUEL, 2021, 卷号: 290, 页码: 10
Authors:
Kang DL(康东亮)
;
Wang XH(王晓荷)
;
Zheng XJ(郑晓娇)
;
Zhao YP(赵亚溥)
Adobe PDF(5174Kb)
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Submit date:2021/03/30
Machine learning
Kerogen and shale
Molecular structure
High-throughput prediction
NMR spectra datasets
Wheel Wear Prediction of High-Speed Train Using NAR and BP Neural Networks
会议论文
EEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Exeter, ENGLAND, JUN 21-23, 2017
Authors:
Fan N
;
Wang SW
;
Liu CX
;
Liu XM(刘小明)
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Submit date:2018/06/06
Big Data
Wheel Wear
Variance Analysis
Nar Neural Network
Prediction
A Simple Model for Predicting the Two-Phase Heavy Crude Oil Horizontal Flow with Low Gas Fraction
期刊论文
CHEMICAL ENGINEERING COMMUNICATIONS, 2016, 卷号: 203, 期号: 9, 页码: 1131-1138
Authors:
Chen XP(陈小平)
;
Xu JY(许晶禹)
;
Zhang J(张健)
;
Xu, JY (reprint author), Chinese Acad Sci, Inst Mech, Key Lab Mech Fluid Solid Coupling Syst, Beijing 100190, Peoples R China.
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Submit date:2016/06/02
Drift-flux Model
Gas-liquid Flow
Heavy Crude Oil
Pressure Gradient
Viscosity
Void Fraction