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Meeting MS&T21: Materials Science & Technology
Symposium Development of Light Weight Alloys and Composites
Presentation Title Existing and Emerging Applications of Machine Learning in Design, Synthesis, and Characterization of Metal Matrix Composites
Author(s) Amir Kordijazi, Pradeep Rohatgi
On-Site Speaker (Planned) Amir Kordijazi
Abstract Scope We present an overview of existing and emerging machine learning (ML) applications in the design, synthesis, and characterization of metal matrix composites (MMC). We have shown that machine learning approaches can be used in three different categories: property prediction, microstructure analysis, and process optimization, which are correlated with three different types of machine learning techniques: regression, classification, and optimal control, respectively. Mechanical, tribological, corrosion, and wetting properties of various MMCs have all been successfully predicted using machine learning algorithms. However, despite their enormous capabilities, ML methods such as computer vision, which is useful for microstructural characterization and defect detection, and optimization algorithms (e.g., reinforcement learning) have not been widely utilized for the design, processing, and characterization of metal matrix composites. We conclude that ML offers enormous opportunities to gain more knowledge about MMC’s; they can help design, manufacture, and deploy new MMC’s significantly faster at a fraction of the cost.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Data-driven Analysis for Selection of Ti-based Alloys for Aircraft Landing Gear Beams and Future Directions
Coarsening of Strengthening Phases in Al(Cu) Alloys: Correlated Atomic-Resolution Microscopy and Composition Analysis
Development of a High-temperature High Strength Aluminum Alloys by Microstructure Tuning
Development of Bulk Nanocrystalline Aluminum Materials with Enhanced Mechanical Properties
Effect of Copper Contents on Corrosion of High Performance ACMZ Cast Aluminum Alloys
Energy Efficient Solid-state Alloying and Composite Manufacturing
Existing and Emerging Applications of Machine Learning in Design, Synthesis, and Characterization of Metal Matrix Composites
Grain Boundary Relaxation in Nanocrystalline Aluminum
Impact of Laser Shock Peening on Stress Corrosion Susceptibility in Al-Mg Alloys
Inoculation of ML5 Cast Magnesium Alloy with Carbon Nano Powder
Insights into Metal-based Polymer Pyrolysis for In-situ MMC Production
Investigation of Microstructure, Interfaces and Mechanical Properties of Metal Matrix Composites
Low Cycle Fatigue Behavior of Conventional High Temperature Titanium Alloys for Aeroengine Applications
Magnesium Alloy Composite with Metal Reinforced Particles Using Friction Stir Processing To Improve Mechanical Properties
Non-Rule-of-Mixtures Thermal Diffusivity in Core-Shell-based Nanocrystalline Composite Ceramics
Precipitation of Stable Icosahedral Quasicrystalline Phase in Mg-Al-Zn Alloys
Surge for Design and Development of Low-density High Entropy Alloys and Composites
Tensile Properties of Epoxy Composites Reinforced with Continuous Mixed Natural Fibers
The Effect of Multiple Age Treatment on Mechanical Properties of 7075 Al Alloy

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