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Meeting MS&T26: Materials Science & Technology
Symposium Computational Materials for Qualification and Certification
Presentation Title 3D Characterization of Microstructure in Printed Alloys Prone to Solidification Cracking
Author(s) Megna N. Shah, J. Michael Scott, Michael Chapman, Greg Sparks, Edwin Schwalbach, Matthew Krug, Daniel Jackson, Michael Uchic
On-Site Speaker (Planned) Megna N. Shah
Abstract Scope Three dimensional serial sectioning tools developed at the Air Force Research Lab have generated 3D microstructure datasets that have helped to either illuminate the structures in 3D or helped to validate descriptions generated by other modalities or predictions. The automation involved in both collecting the data and then registering and analyzing the data have been important for getting accurate and repeatable measurements, the details of which will be elaborated on in this talk. Furthermore, many of the automation tools, initially intended for repeatable measurements for generating 3D tomographic volumes, lend themselves to automated throughput of characterization (often 2D) of large numbers of samples as part of a materials development loop.This may lend itself to gathering enough data to characterize the underlying data topologies of the processing-structure-properties relationships, enabling autonomous navigable materials development. The framework of these ideas will also be discussed here.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

3D Characterization of Microstructure in Printed Alloys Prone to Solidification Cracking
Acoustics for In-Situ Process Data to Inform Computational Models in Metal Additive Manufacturing
AI-Driven Materials Design for Resilient Manufacturing Under Uncertainty
An Overview of the OPAL Digital Twin to Predict Fatigue Lives Via a Inputs from Computational Materials Models and In-Situ Sensing
Benchmarking Spectral Solution Methods for the Mechanical Behavior of Additively Manufactured Metals Containing Pores
Challenges in Materials Maturation for Additive Manufacturing
Computational Materials for Qualification and Certification Steering Group and Community Vision Roadmap
Establishing the Severity of Pores in Structural Components
Integrated Modeling of Solidification Cracking in Fusion Welding of High-Strength Aluminum: Multi-Criteria Analysis Under Variable Restraints
Metal Additive Manufacturing Simulations Driven by In-Situ Experimental Data for Qualification and Certification
Practical Data Management in Computational Materials for Qualification and Certification
Probabilistic Fatigue Modeling of Powder Bed Fusion – Laser Beam Ti-6Al-4V with Model- and Measurement-Based Uncertainty
Providing Validation Datasets for Materials Process Modelling: A Cornell High Energy Synchrotron Source Perspective
Qualification and Certification for Additive Manufacturing Parts in the US Navy
Robust Manufacturing and Qualification of 3D-Printed Ceramics
The Critical Roles of Verification, Validation, and Uncertainty Quantification for Qualification and Certification of Metal AM Components for the Aviation Industry
Towards a Computational Digital Twin of Metals AM
Towards a Predictive Modeling Platform for Fatigue in Additively Manufactured Metals
Transitioning from Basic Research to Industrial Applications for Metal AM Components

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