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Meeting MS&T26: Materials Science & Technology
Symposium Computational Materials for Qualification and Certification
Presentation Title Establishing the Severity of Pores in Structural Components
Author(s) Erik Furton, Allison M. Beese
On-Site Speaker (Planned) Allison M. Beese
Abstract Scope Additive manufacturing of metals can be used to fabricate load-bearing components for structural applications. However, the presence of internal pores may limit the properties of these components. Given that in ductile metals, the strain or stress a material component can withstand before failure depends on the local stress state, as well as existing internal defects, an understanding of the combined impact of stress state and defects on the failure behavior additively manufactured components must be understood for their reliable use. This talk will discuss our methods for experimentally identifying and computationally modeling the combined impacts of stress state and defect size on the ductile failure of metals. The importance of considering these contributions to predict ductile fracture will be demonstrated in complex shaped components and contrasted with conventional methods for defining failure.

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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