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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 On Scan Path Knowledge for Model Informed Process Planning and Material Quality Predictions
Author(s) Emil Duong, Lukas Masseling, Ulrich Thombansen, Christian Knaak, Mustafa Megahed
On-Site Speaker (Planned) Mustafa Megahed
Abstract Scope Scan paths have been shown to play a significant role in printing accuracy, defect generation and material quality. Open processes such as DED enable access to virtual and digital twins to path planning tools and files thus supporting a complete representation of the process and the component thermal history. Processes where path planning is not available, such as in commercial LPBF systems, pose a significant challenge to modelers limiting research efforts to trial and error and reverse engineering machine behavior before focusing on technological progress. In this presentation a DED hybrid twin consisting of physics- and data-based models will be presented. In contrast physics-based LPBF models are used to demonstrate the negative effect of inaccurate path planning knowledge on numerical predictions. As a result LPBF digital twins must represent several process unknowns as well as the material response to process parameters.
Proceedings Inclusion? Planned: None Selected


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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