Artificial Intelligence and Machine Learning for Materials II

Monday, September 30, 2024: 3:00 PM-5:20 PM
24 (Huntington Convention Center)
Dr. Joshua Stuckner, NASA Glenn Research Center
3:00 PM
Machine learning design of printable high-temperature strength Aluminum alloys
Prof. S. Mohadeseh Taheri-Mousavi, Carnegie Mellon University
3:40 PM
A Data-Driven Approach to Fatigue Life Characterization in A205 Aluminum Alloy: Additive Manufactured and Cast
Mr. Hamed Esmaeili, York University; Mrs. Maryam Avateffazeli, York University; Dr. Meysam Haghshenas, The University of Toledo; Dr. Reza Rizvi, York University
4:00 PM
Application of Machine Learning for Estimating Heat Transfer Coefficients
Prof. Imre Felde, Becsi ut
4:20 PM
Advancing Multiscale Modeling: Innovations and Outcomes from NASA's SBIR-Funded Multiscale Modeling Hub (MMH) Development
Peter Searles, MDMi
4:40 PM
Bayesian calibration of material properties for shape memory alloys from nanoindentation data
Ms. Yingyu Cheng, The Ohio State University; Mr. Daniel Hong, The Ohio State University; Dr. Oksana Chkrebtii, The Ohio State University; Dr. Peter M Anderson, The Ohio State University; Prof. Steve Niezgoda, The Ohio State University; Dr. Thomas Santner, The Ohio State University
5:00 PM
Mapping Nanoindentation to Stress-Strain Response: A Bayesian Approach
Mr. Daniel Hong, The Ohio State University; Ms. Yingyu Cheng, The Ohio State University; Dr. Oksana Chkrebtii, The Ohio State University; Dr. Peter M Anderson, The Ohio State University
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