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Meeting MS&T22: Materials Science & Technology
Symposium Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
Presentation Title Studying Melt Pool Variation and Its Effects on the Formation of Porous Defects via GPU-based Process Simulation
Author(s) David Scott Anderson, Chaitanya Krishna Prasad Vallabh, Shawn Hinnebusch, Xiayun Zhao, Albert To
On-Site Speaker (Planned) David Scott Anderson
Abstract Scope The development of parts using Laser-Powder Bed Fusion (L-PBF) additive manufacturing processes face several challenges that stem from porosity formation. These porosities are typically generated from under-heating or over-heating the powders, also known as lack-of-fusion and keyholing, respectively. Although these two occurrences are closely linked to printing parameters such as laser scan speed, laser intensity, hatch spacing, and scan path orientation, the independent effects of each of these parameters on porosity formation is not well documented. Through GPU-based computational modeling, the effects of these process parameters on the melt pool geometry have been simulated. By comparing these simulations with serial cross-sectioning data of printed samples, these results aid in calibrating the simulations to predict melt pool geometries more accurately, that may lead to keyholing or lack-of-fusion, and thus porous defects.


A-10: Smoothed Particle Hydrodynamics Modeling of Charpy Impact Test of A36 Steel
A-11: Thermal Barrier Coating with Additively Manufactured Nickel Base Superalloy Substrate
A-12: Utilizing Virtual Reality to Help Educate Additive Manufacturing
A-2: A Data-driven Approach to Identify Structural Characteristics that Connect Macroscale Material Properties
A-3: Corrosion and Mechanical Properties of Additively Manufactured 316L Stainless Steel Coated with Epoxy
A-4: Design and Mechanical Properties of 3D Printed Bioinspired Honeycomb Structures
A-5: Development a Customized Inkjet 3D Printer for Ceramic Component Fabrication
A-6: Fabrication and Characterizations of 3D Printed Lithium-Ion Battery Electrodes
A-7: Layerwise Thermal Process Simulation for Laser Powder Bed Fusion: Calibration and Validation with Infrared Camera
A-8: Modeling of Fatigue Behavior of 3D Printed Polycrystal Metals
A-9: Reducing the Order of a Kinetic Monte Carlo Potts Solidification Model with Machine Learning
A Modeling Tool for Mechanical Performance Prediction and Qualification of Additive Manufacturing Parts
A Parametric Molecular Dynamics Study of Additive Nanomanufacturing: Effects of Size, Misorientation, and Temperature on Sintering Characteristics
Additive Manufacturing Beyond the Gaussian Beam: Insights from Mesoscale Modeling Studies
Additive Manufacturing Moment Measure: A Reduced Order Model of the Laser Powder Bed Fusion Process
Additively Manufactured Multi-metallic Design for Ti-6Al-4V and Inconel 718 Joining by Scheil-Gulliver Ternary Projection Diagrams
Analyzing Uncertainty in Modeled Additive Process-Microstructure-Property Relationships Using the ExaAM Framework
Anisotropic Distortion Modeling during Sintering of Binder Jet Printed Parts
CFD Simulations of Spatter Removal in a Laser Powder Bed Fusion Machine
Computational Fluid Dynamics Data-driven Heat Source Model for Finite Element Process Simulation in Laser Powder Bed Fusion Additive Manufacturing
Crystal Plasticity Modeling Effort to Capture Microstructural Variations in Cold Sprayed Materials
Development of Rapid Solidification Model for Additive Manufacturing and Application to Al-Si Alloys
Discrete Element Method Based Simulations of Metal Powder Pouring and Raking Processes in Additive Manufacturing
Effects of a Novel Post Processing Technique on Mechanical Performance of AlSi10Mg Produced via LPBF
Embracing Variability: Machine Learning-based Sequential Optimization of Additive Manufacturing Processes
Energy and Microstructural Evolution of In-situ Alloyed Cu-4at% Cr -2 at% Nb via Laser Powder Bed Fusion
Generating Novel Porosity Distributions Produced by Metal Additive Manufacturing via Deep Learning
In Situ Confocal Imaging and Quantification of Defects in Binder-Jet Printed (BJP) Steel Parts
Increasing the Service Life of the Trimming Punch Using Nimonic Cutting Edge
Machine Learning Segmentation Methods for Fatigue Fracture Surface Defect Analyses
Mesoscale Modeling of the Additively Manufactured 316L: Effects of Microstructure and Microscale Residual Stresses
Microstructure Predictions in Additive Manufacturing from Analytical Solidification Models – A Critical Assessment of Simplifying Assumptions
Modeling the Solidification Cracking Susceptibility of Additively Manufactured Alloys
Modified Inherent Strain Modeling of Residual Stress and Distortion in WAAM and LPBF Processes
Parent Grain Reconstruction Using Orientation Imaging Microscopy and Deep Learning
Phase Stability and Mechanical Properties of Ni-Al and Ni-Cr Binary Solid Solutions Using CASTEP Supercell Approach
Planar and Full-Process Modeling of the Powder-Bed Fusion Ti-6Al-4V Columnar-to-Equiaxed Transition Behavior
Powder Bed Packing Density Dependence on Particle Size Distribution: Simulation and Experimental Analysis
Prediction of Microstructure Formation Under Rapid Solidification Using a Deep Learning Approach
Printability and Failure Susceptibility of Different Powder Layer Thicknesses in Laser Powder Bed Fusion
Quantitative Analysis of Computed Tomography Characterization of Porosity in AM Ti64 Using Serial Sectioning Ground Truth
Rapid Qualification of Wire Feed Direct Energy Deposition Process Builds Using ICME Approach
Residual Stress Modeling during Wire Arc Additive Manufacturing of Low Temperature Transformation Alloy
Sparse Sampling for 3D Electron Backscatter Diffraction
Studying Melt Pool Variation and Its Effects on the Formation of Porous Defects via GPU-based Process Simulation
Tailoring Formation of TCP Phases during Additively Manufactured Inconel 625 by CALPHAD-based Simulations with Experimental Validations
The Effect of the Process Environment on Gas and Particle Entrainment in Laser Powder Bed Fusion
Thermal Modeling of Laser Powder Bed Fusion Additive Manufacturing of Refractory Materials
Thermomechanical Modeling of Axisymmetric Geometries for Laser Hot Wire Additive Manufacturing
Towards Qualification and Certification of Laser Powder Bed Fusion Ti-6Al-4V with In-Situ Process Monitoring and Automated Defect Detection
Uncertainty Quantification in Process-Structure-Properties Simulations of Additive Manufactured Ti-6Al-4V
Using Generative Adversarial Networks for the Design of Metamaterials to Reach New Property Spaces
Using Machine Learning to Characterize Powder Behavior and Surface Roughness in Powder Bed Fusion AM

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