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Meeting MS&T21: Materials Science & Technology
Symposium Additive Manufacturing of Metals: ICME Gaps: Material Property and Validation Data to Support Certification
Presentation Title Determining Data Requirements to Quantify Porosity in the Laser Powder Bed Fusion Process
Author(s) Mahya Shahabi, Caitlin M. Kean, Adrianna Y. Yuen, Anthony D. Rollett, Sneha Prabha Narra
On-Site Speaker (Planned) Sneha Prabha Narra
Abstract Scope Data-driven quantification of microstructure in additively manufactured parts helps establish process-structure-property relations. For instance, fatigue resistance is governed by the upper tail of the porosity distribution. However, the amount of data required to accurately populate the porosity distribution is still unknown. Towards addressing this gap, this talk discusses the data required to quantify porosity in the laser powder bed fusion (L-PBF) additively manufactured parts. 2D porosity data obtained from cross-sectional microscopy was used as an example. The minimum required number of pores was identified for multiple L-PBF specimens (varying porosity levels) to achieve a representative Generalized Pareto distribution to describe the upper tail. Our results confirm the intuition that the data required to characterize part porosity is primarily determined by the quality of the sample and the required precision of the model. Methods described here can also be applied to 3D porosity data and features such as grain size.


An Analysis of the Dislocation Density of Inconel 718 Additive Manufacturing Powder
An ICME Approach for Designing Appropriate Heat Treatments in Additively Manufactured Nitrogen Atomized 17-4PH Stainless Steel
Capturing and Analyzing In-situ Data within the Directed Energy Deposition Process with DEDSmart
CFD Modelling for AM Processes
Critical Issues and Gaps in Testing and Characterization Data for Computational Materials in Qualification and Certification of Additively Manufactured Metallic Materials
Determining Data Requirements to Quantify Porosity in the Laser Powder Bed Fusion Process
Enabling Quality Assurance by Completing the Process-Property-Performance Paradigm for Additive Manufacturing
Experimental and Numerical Investigation of Pressureless Sintering for Binder Jetted Metal Parts
High Temperature Material Properties Measurement Capabilities of the NASA MSFC Electrostatic Levitation (ESL) Laboratory
High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing
ICME Gap Analysis for Materials Design and Process Optimization in Additive Manufacturing
ICME Gaps for Additive Manufacturing of Metals
Laser Energy Coupling during Metal Additive Manufacturing
Lessons Learned from Calibration and Validation of Process Models for Laser Powder Bed Fusion
Methods for Improved Part-scale Thermal Process Simulations in Laser Powder Bed Fusion
On Scan Path Knowledge for Model Informed Process Planning and Material Quality Predictions
Phase Field Informed Monte Carlo Texture Evolution Models for Additive Manufacturing Microstructure Simulation and the Need for Experimental Grain Competition Data
Predicting Melt Properties Using Atomistic Simulations with a Highly Accurate Physically Informed Neural Network Interatomic Potential
Providing a Rigorous Measurement Foundation for Modeling-Informed Qualification and Certification of Metal AM Components
Transferability of Terrestrial Development of Metal Additive to Extraterrestrial Applications

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