Artificial intelligence-aided materials design : AI-algorithms and case studies on alloys and metallurgical processes /
"This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials. Readers new to AI/ML algorithms can use the book as a starting point and use the included MATLAB and Python implementation...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boca Raton, FL :
CRC Press,
2022.
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| Edition: | First edition. |
| Subjects: | |
| Online Access: | CONNECT |
Table of Contents:
- 1. Introduction. 2. Metallurgical/Materials Concepts. 3. Artificial Intelligence Algorithms. 4. Case Study 1: Nanomechanics and Nanotribology: Combined Machine Learning-Experimental Approach. 5. Case Study 2: Design of Hard Magnetic Alnico Alloys: Combined Machine Learning-Experimental Approach. 6. Case Study 3: Design of Soft Magnetic Finemet Type Alloys: Combined Machine Learning-CALPHAD Approach. 7. Case Study 4: Design of Nickel-Base Superalloys: Combined Machine Learning-CALPHAD Approach. 8. Case Study 5: Design of Aluminum Alloys: Combined Machine Learning-CALPHAD Approach. 9. Case Study 6: Design of Titanium Alloys for High-Temperature Application: Combined Machine Learning-CALPHAD Approach. 10. Case Study 7: Design of Titanium Based Biomaterials: Combined Machine Learning-CALPHAD Approach. 11. Case Study 8: Industrial Furnaces I: Application of Machine Learning on an Industrial Iron Making Blast Furnace Data. 12. Case Study 9: Industrial Furnaces II: Application of Machine Learning Algorithms on an Industrial LD Steel Making Furnace Data. 13. Software/Codes Included with this Book. 14. Conclusion.
