Finite element model for unified EB–PVD machine dynamics.
- Published in:
- Surface Engineering, 2007, v. 23, n. 6, p. 453, doi. 10.1179/174329407X239225
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- Publication type:
- Article
Works matching DE "MACHINE dynamics"
Results: 251
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Developing Efficient Small Molecule Acceptors with sp<sup>2</sup>‐Hybridized Nitrogen at Different Positions by Density Functional Theory Calculations, Molecular Dynamics Simulations and Machine Learning.
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- Chemistry - A European Journal, 2022, v. 28, n. 2, p. 1, doi. 10.1002/chem.202103712
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- Publication type:
- Article
3
Combining Algorithmic Information Dynamics Concepts and Machine Learning for Electroencephalography Analysis: What Can We Get?
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- Complex Systems, 2022, v. 31, n. 4, p. 389, doi. 10.25088/ComplexSystems.31.4.389
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4
Investigation of water desalination/purification with molecular dynamics and machine learning techniques.
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- AIMS Materials Science, 2022, v. 9, n. 6, p. 919, doi. 10.3934/matersci.2022054
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- Publication type:
- Article
5
Regulation of Flowering Time and Other Developmental Plasticities by 3' Splicing Factor-Mediated Alternative Splicing in Arabidopsis thaliana.
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- Plants (2223-7747), 2023, v. 12, n. 19, p. 3508, doi. 10.3390/plants12193508
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- Article
6
Two Is Company, but Four Is a Party—Challenges of Tetraploidization for Cell Wall Dynamics and Efficient Tip-Growth in Pollen.
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- Plants (2223-7747), 2021, v. 10, n. 11, p. 2382, doi. 10.3390/plants10112382
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- Publication type:
- Article
7
Numerical Simulation and Optimization of Screening Process for Vibrating Flip-Flow Screen Based on Discrete Element Method–Finite Element Method–Multi-Body Dynamics Coupling Method.
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- Minerals (2075-163X), 2024, v. 14, n. 3, p. 278, doi. 10.3390/min14030278
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- Article
8
Analysis of urban sprawl dynamics using machine learning, CA-Markov chain, and the Shannon entropy model: a case study in Mbombela City, South Africa.
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- Environmental Systems Research, 2024, v. 13, n. 1, p. 1, doi. 10.1186/s40068-024-00348-5
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9
Effect of machine scatter on the rotating bending fatigue life of materials.
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- Journal of the Mechanical Behavior of Materials, 2018, v. 27, n. 3/4, p. N.PAG, doi. 10.1515/jmbm-2018-0021
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- Article
10
Reconstructing coupled time series in climate systems using three kinds of machine-learning methods.
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- Earth System Dynamics, 2020, v. 11, n. 3, p. 835, doi. 10.5194/esd-11-835-2020
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- Article
11
Integrating machine learning techniques for Air Quality Index forecasting and insights from pollutant-meteorological dynamics in sustainable urban environments.
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- Earth Science Informatics, 2024, v. 17, n. 4, p. 3733, doi. 10.1007/s12145-024-01382-8
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- Article
12
A Rube Goldberg Approach to Teaching Dynamics of Machine Elements.
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- Advances in Engineering Education, 2019, v. 7, n. 3, p. 1
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- Article
13
Machine Learning in Nonlinear Dynamical Systems.
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- Resonance: Journal of Science Education, 2021, v. 26, n. 7, p. 953, doi. 10.1007/s12045-021-1194-0
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- Article
14
Thermal Conductivity of Hydrous Wadsleyite Determined by Non‐Equilibrium Molecular Dynamics Based on Machine Learning.
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- Geophysical Research Letters, 2022, v. 49, n. 22, p. 1, doi. 10.1029/2022GL100337
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- Article
15
Frontispiece: Distance versus Capillary Flow Dynamics‐Based Detection Methods on a Microfluidic Paper‐Based Analytical Device (μPAD).
- Published in:
- Chemistry - A European Journal, 2019, v. 25, n. 57, p. N.PAG, doi. 10.1002/chem.201985762
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- Article
16
Multiple operational mode prediction at milling tool-tip based on transfer learning.
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- Journal of Intelligent Manufacturing, 2025, v. 36, n. 3, p. 1959, doi. 10.1007/s10845-024-02364-9
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- Article
17
Model predictive force control in milling based on an ensemble Kalman filter.
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- Journal of Intelligent Manufacturing, 2022, v. 33, n. 7, p. 1907, doi. 10.1007/s10845-022-01931-2
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18
Accurate real-time trajectory generation of circular motion using FIR interpolation: a trochoidal milling case study.
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- International Journal of Advanced Manufacturing Technology, 2025, v. 137, n. 11, p. 5625, doi. 10.1007/s00170-025-15385-2
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- Article
19
A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 135, n. 11, p. 5843, doi. 10.1007/s00170-024-14841-9
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20
Process-integrated computerized numerical control: an analysis on process-machine coupling and feed scheduling.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 135, n. 3/4, p. 1291, doi. 10.1007/s00170-024-14437-3
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- Article
21
Single artifact inverse RCSA with improved cross compliance identification.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 134, n. 11/12, p. 5413, doi. 10.1007/s00170-024-14296-y
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22
A data and mechanism hybrid driven cutting parameter optimization method considering the machine tool and coolant condition flexibility.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 133, n. 3/4, p. 1349, doi. 10.1007/s00170-024-13704-7
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23
Finish dry turning of DC53 tool steel via modified carbide inserts: a study of machining dynamics.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 132, n. 9/10, p. 4505, doi. 10.1007/s00170-024-13594-9
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24
Tri-dexel-based cutter-workpiece engagement: computation and validation for virtual machining operations.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 131, n. 2, p. 623, doi. 10.1007/s00170-023-10950-z
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- Article
25
Automated machine tool dynamics identification for predicting milling stability charts in industrial applications.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2024, v. 130, n. 11/12, p. 5879, doi. 10.1007/s00170-024-12952-x
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26
Inconel-718 processing windows by directed energy deposition: a framework combining computational fluid dynamics and machine learning models with experimental validation.
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- International Journal of Advanced Manufacturing Technology, 2024, v. 130, n. 7/8, p. 3997, doi. 10.1007/s00170-024-12980-7
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27
Position-dependent FRF identification without force measurement in milling process.
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- International Journal of Advanced Manufacturing Technology, 2023, v. 128, n. 11/12, p. 4981, doi. 10.1007/s00170-023-11925-w
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28
Auto-identification of dominant modal parameters from multi-batch signals based on weighted SSA to suppress milling vibration.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 128, n. 9/10, p. 4077, doi. 10.1007/s00170-023-12156-9
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- Publication type:
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29
Robust tool condition monitoring in Ti6Al4V milling based on specific force coefficients and growing self-organizing maps.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 128, n. 9/10, p. 3761, doi. 10.1007/s00170-023-11930-z
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30
Local corner smoothing algorithm for screw motor high-precision machining.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 126, n. 5/6, p. 2117, doi. 10.1007/s00170-023-11228-0
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31
Influence of unilateral constraint on machining dynamics of large overhang milling cutter.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 125, n. 7/8, p. 3577, doi. 10.1007/s00170-023-11028-6
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32
A novel control strategy for suppression of regenerative chatter in conventional lathe.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 125, n. 3/4, p. 1917, doi. 10.1007/s00170-022-09044-z
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33
Model of force interaction for stability prediction in turning of thin-walled cylindrical workpiece.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 125, n. 1/2, p. 195, doi. 10.1007/s00170-022-10343-8
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- Article
34
Investigation on stability of robotic rotary ultrasonic edge milling component with poor rigidity.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2023, v. 124, n. 5/6, p. 1579, doi. 10.1007/s00170-022-10498-4
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35
Analysis of the effect of part geometry and cutting parameters over tool vibration and surface integrity on hard turning.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2022, v. 122, n. 9/10, p. 4065, doi. 10.1007/s00170-022-10162-x
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- Article
36
A review on dynamics in micro-milling.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2022, v. 122, n. 9/10, p. 3467, doi. 10.1007/s00170-022-10014-8
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- Article
37
Real-time compensation of backlash positional errors in CNC machines by localized feedrate modulation.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2022, v. 119, n. 9/10, p. 5763, doi. 10.1007/s00170-021-08515-z
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- Article
38
Simulation-based optimization of CNC interpolator parameters for machining accuracy improvement.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2022, v. 119, n. 5/6, p. 3757, doi. 10.1007/s00170-021-08434-z
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- Article
39
Dynamic modeling and experimental research on position-dependent behavior of twin ball screw feed system.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2021, v. 117, n. 11/12, p. 3693, doi. 10.1007/s00170-021-07874-x
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- Publication type:
- Article
40
New Precedence Theorems for One-Machine Weighted Tardiness.
- Published in:
- Mathematics of Operations Research, 2007, v. 32, n. 3, p. 579, doi. 10.1287/moor.1070.0255
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- Article
41
Analysis of Soil Carbon Stock Dynamics by Machine Learning—Polish Case Study.
- Published in:
- Land (2012), 2023, v. 12, n. 8, p. 1587, doi. 10.3390/land12081587
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- Article
42
Identification of high‐dimensional omics‐derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling.
- Published in:
- CPT: Pharmacometrics & Systems Pharmacology, 2021, v. 10, n. 4, p. 350, doi. 10.1002/psp4.12603
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- Publication type:
- Article
43
Pioneering the Future: A Trailblazing Review of the Fusion of Computational Fluid Dynamics and Machine Learning Revolutionizing Plasma Catalysis and Non-Thermal Plasma Reactor Design.
- Published in:
- Catalysts (2073-4344), 2024, v. 14, n. 1, p. 40, doi. 10.3390/catal14010040
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- Publication type:
- Article
44
Molecular Dynamics and Machine Learning in Catalysts.
- Published in:
- Catalysts (2073-4344), 2021, v. 11, n. 9, p. 1129, doi. 10.3390/catal11091129
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- Article
45
Computational Assessments on Dragline Bucket Oscillations.
- Published in:
- Romanian Journal of Acoustics & Vibration, 2018, v. 15, n. 2, p. 149
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- Article
46
A Novel Improved Maximum Entropy Regularization Technique and Application to Identification of Dynamic Loads on the Coal Rock.
- Published in:
- Journal of Electrical & Computer Engineering, 2019, p. 1, doi. 10.1155/2019/9602954
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- Publication type:
- Article
47
Contribution of Professor M. Z. Kolovsky to the Science of Mechanisms and Machines.
- Published in:
- International Review of Mechanical Engineering, 2020, v. 14, n. 2, p. 79, doi. 10.15866/ireme.v14i2.18244
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- Article
48
Heuristics for a coupled-operation scheduling problem.
- Published in:
- Journal of the Operational Research Society, 2007, v. 58, n. 10, p. 1375, doi. 10.1057/palgrave.jors.2602272
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- Article
49
Behavioral biometrics to detect fake expert profiles during negotiation.
- Published in:
- Multimedia Tools & Applications, 2024, v. 83, n. 32, p. 78293, doi. 10.1007/s11042-024-18644-8
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- Article
50
Partition of the workspace for machine tool based on position-dependent modal energy distribution and clustering algorithm.
- Published in:
- International Journal of Advanced Manufacturing Technology, 2020, v. 108, n. 3, p. 943, doi. 10.1007/s00170-020-05487-4
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- Publication type:
- Article