Learn · Data-Enabled Tribological Engineering: From Experiments to Predictive Models
Lecture 35 of 35week-12
Lecture 36 - Future Directions in Data-Enabled Tribological Engineering
Prof. (HAG) Harish Hirani · IIT Delhi
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- Data-Enabled Tribological Engineering: From Experiments to Predictive Models, IIT Delhi (at NPTEL)
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All the lectures
- Lecture 1 - Introduction to Tribology
- Lecture 2 - Tribological Interfaces
- Lecture 3 - Fundamentals of Friction and Wear
- Lecture 5 - Wear Measurement Techniques
- Lecture 6 - Principles of Lubrication, types of Lubricants and their properties
- Lecture 7 - Lubrication regimes and film thickness calculations
- Lecture 8 - Mixed Lubrication
- Lecture 9 - Hydrodynamic Lubrication Theory
- Lecture 10 - Design Considerations for Hydrodynamic Lubrication Systems
- Lecture 11 - Elastohydrodynamic Lubrication
- Lecture 12 - Solid Lubrication
- Lecture 13 - Surface modification techniques for tribological applications
- Lecture 14 - Thin film coatings and their tribological properties
- Lecture 15 - Nanotribology
- Lecture 16 - Tribocorrosion
- Lecture 17 - Wear testing techniques and standards
- Lecture 18 - Measurement and analysis of wear debris
- Lecture 19 - Experimental Design and Statistical Analysis
- Lecture 20 - Introduction to Data-Enabled Engineering
- Lecture 21 - Data Collection and Preprocessing
- Lecture 22 - Feature Extraction and Selection
- Lecture 23 - Introduction to Machine Learning Algorithms
- Lecture 24 - Regression and Classification Algorithms for Tribological Modeling
- Lecture 25 - Deep Learning for Tribological Engineering
- Lecture 26 - Data-Driven Models for Friction Prediction
- Lecture 27 - Data-Driven Models for Wear Prediction
- Lecture 28 - Data-Driven Models for Lubricant Optimization
- Lecture 29 - Data-Driven Models for Tribofilm Formation
- Lecture 30 - Data-Driven Models for Tribocorrosion Prediction
- Lecture 31 - Prediction of Coating and Surface Treatment Performance
- Lecture 32 - Optimization of Surface Engineering Processes using Machine Learning
- Lecture 33 - Uncertainty Quantification and Sensitivity Analysis
- Lecture 34 - Data Management and Ethics in Data-Enabled Engineering
- Lecture 35 - Case Studies in Data-Enabled Tribological Engineering
- Lecture 36 - Future Directions in Data-Enabled Tribological Engineering