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About this Symposium
Meeting MS&T22: Materials Science & Technology
Symposium Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
Sponsorship
Organizer(s) Jing Zhang, Indiana University – Purdue University Indianapolis
Brandon A. McWilliams, US Army Research Laboratory
Li Ma, Johns Hopkins University
Yeongil Jung, Changwon National University
Scope This symposium will provide a platform to exchange the latest information in additive manufacturing (AM) modeling, simulation, and machine learning. Although there are extensive advances in AM field, challenges in predictive theoretical and computational approaches still hinder the widespread adoption of AM. The symposium is interested in receiving contributions in the following non-exclusive areas: In particular, the following topics, but not limited to, are of interest:

1.Modeling of microstructure evolution, phase transformation, and defect formation in AM parts
2.Modeling of residual stress, distortion, plasticity/damage, creep, and fatigue in AM parts
3.AM process monitoring and defect quantification
4.Machine learning (ML) and artificial intelligence (AI) applications to AM
5.Efficient computational methods using reduced order models or fast emulators for process control
6.Multiscale/multiphysics modeling strategies, including any or all of the scales associated with the spatial, temporal, and/or material domains

Abstracts Due 05/15/2022
Proceedings Plan Planned: At-meeting proceedings
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE

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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