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Journal Articles

Predicting the Erosion Rate of Uni-Directional Glass Fiber Reinforced Polymer Composites Using Machine-Learning Algorithms

Ajaz Ahmed Deliwala, Koshlendra Dubey, Chandra Sekher Yerramalli

J. Tribol. September 2022, 144(9): 091707.

Paper No: TRIB-22-1037

DOI: https://doi.org/10.1115/1.4054247

Published Online: May 3, 2022

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Topics: Algorithms, Artificial neural networks, Erosion, Fibers, Machine learning, Particulate matter, Glass fibers, Composite materials, Fiber reinforced plastics

Journal Articles

Development of a Machine Learning Model for Elastohydrodynamic Pressure Prediction in Journal Bearings

Nathan Hess, Lizhi Shang

J. Tribol. August 2022, 144(8): 081603.

Paper No: TRIB-21-1537

DOI: https://doi.org/10.1115/1.4053815

Published Online: March 7, 2022

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Topics: Artificial neural networks, Journal bearings, Machine learning, Pressure, Modeling, Computer simulation, Optimization

Journal Articles

Enhanced Hybrid Model to Predict the Surface Roughness of Honed Cylinder Bore

Burhan Afzal, Xueping Zhang, Anil K. Srivastava

J. Tribol. January 2022, 144(1): 011201.

Paper No: TRIB-21-1208

DOI: https://doi.org/10.1115/1.4052280

Published Online: September 24, 2021

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Topics: Artificial neural networks, Surface roughness, Machine learning, Cylinders, Surface texture

Journal Articles

Tilt Pad Bearing Distributed Pad Inlet Temperature With Machine Learning—Part I: Static and Dynamic Characteristics

Jongin Yang, Alan Palazzolo

J. Tribol. June 2022, 144(6): 061801.

Paper No: TRIB-20-1503

DOI: https://doi.org/10.1115/1.4052171

Published Online: September 3, 2021

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Topics: Finite element methods, Fluid films, Temperature, Rotors, Bearings, Machine learning, Flow (Dynamics), Computational fluid dynamics, Temperature distribution, Fluids

Journal Articles

Triboinformatics Approach for Friction and Wear Prediction of Al-Graphite Composites Using Machine Learning Methods

Md Syam Hasan, Amir Kordijazi, Pradeep K. Rohatgi, Michael Nosonovsky

J. Tribol. January 2022, 144(1): 011701.

Paper No: TRIB-20-1555

DOI: https://doi.org/10.1115/1.4050525

Published Online: April 19, 2021

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Topics: Composite materials, Friction, Graphite, Metal matrix composites, Tribology, Wear, Algorithms, Machine learning, Artificial neural networks

Journal Articles

Classification of Friction and Wear State of Wind Turbine Gearboxes Using Decision Tree and Random Forest Algorithms

Jinshan Pang, Yuming Chen, Shizhong He, Huihe Qiu, Chili Wu, Lingbo Mao

J. Tribol. September 2021, 143(9): 091702.

Paper No: TRIB-20-1371

DOI: https://doi.org/10.1115/1.4049257

Published Online: January 8, 2021

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Topics: Adhesives, Algorithms, Cutting, Friction, Support vector machines, Wear, Wind turbines, Viscosity, Fatigue, Particulate matter

Journal Articles

Computational Fluid Dynamics Based Mixing Prediction for Tilt Pad Journal Bearing TEHD Modeling—Part II: Implementation With Machine Learning

Jongin Yang, Alan Palazzolo

J. Tribol. January 2021, 143(1): 011802.

Paper No: TRIB-19-1340

DOI: https://doi.org/10.1115/1.4047751

Published Online: August 3, 2020

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Topics: Artificial neural networks, Computational fluid dynamics, Flow (Dynamics), Machine learning, Modeling, Temperature, Journal bearings, Pressure

Journal citation

NARROW

Predicting the Erosion Rate of Uni-Directional Glass Fiber Reinforced Polymer Composites Using Machine-Learning Algorithms

Development of a Machine Learning Model for Elastohydrodynamic Pressure Prediction in Journal Bearings

Enhanced Hybrid Model to Predict the Surface Roughness of Honed Cylinder Bore

Tilt Pad Bearing Distributed Pad Inlet Temperature With Machine Learning—Part I: Static and Dynamic Characteristics

Triboinformatics Approach for Friction and Wear Prediction of Al-Graphite Composites Using Machine Learning Methods

Classification of Friction and Wear State of Wind Turbine Gearboxes Using Decision Tree and Random Forest Algorithms

Computational Fluid Dynamics Based Mixing Prediction for Tilt Pad Journal Bearing TEHD Modeling—Part II: Implementation With Machine Learning

Journals

Conference Proceedings

eBooks

Resources

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Predicting the Erosion Rate of Uni-Directional Glass Fiber Reinforced Polymer Composites Using Machine-Learning Algorithms

Development of a Machine Learning Model for Elastohydrodynamic Pressure Prediction in Journal Bearings

Enhanced Hybrid Model to Predict the Surface Roughness of Honed Cylinder Bore

Tilt Pad Bearing Distributed Pad Inlet Temperature With Machine Learning—Part I: Static and Dynamic Characteristics

Triboinformatics Approach for Friction and Wear Prediction of Al-Graphite Composites Using Machine Learning Methods

Classification of Friction and Wear State of Wind Turbine Gearboxes Using Decision Tree and Random Forest Algorithms

Computational Fluid Dynamics Based Mixing Prediction for Tilt Pad Journal Bearing TEHD Modeling—Part II: Implementation With Machine Learning

Journals

Conference Proceedings

eBooks

Resources

Opportunities

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