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Meeting Materials Science & Technology 2020
Symposium Additive Manufacturing Modeling and Simulation: AM Materials, Processes, and Mechanics
Sponsorship TMS Additive Manufacturing Committee
Organizer(s) Jing Zhang, Indiana University – Purdue University Indianapolis
Brandon A. McWilliams, US Army Research Laboratory
Li Ma, Johns Hopkins University Applied Physics Laboratory
Yeongil Jung, Changwon National University
Scope This symposium will showcase the latest development in additive manufacturing (AM) modeling and simulation. Although there is extensive advance 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 and simulation of AM process to understand the process-structure-property relationship
2. Modeling of morphology evolution, phase transformation, and defect formation in AM parts
3. Modeling of residual stress, distortion, plasticity/damage, creep, and fatigue in AM parts
4. AM process monitoring and defect quantification
5. Multiscale/multiphysics modeling strategies, including any or all of the scales associated with the spatial, temporal, and/or material domains
6. Efficient computational methods using reduced order models or fast emulators for process control

Abstracts Due 04/15/2020
Proceedings Plan Planned: Online-only format

A Discrete Dendrite Dynamics Model for Fast Epitaxial Columnar Grain Growth in Metal Additive Manufacturing
A Process Parameter Prediction Framework for Metal Additive Manufacturing
A System Dynamics approach to submodels for Residual Stress Predictions of SLM Parts
Cellular Automata Modeling of Microstructure Resulting from Novel Scan Patterns in Selective Laser Melting
Control of High-temperature Drop-on-demand Metal Jetting through Numerical Modelling and Experimentation
Creep Modeling of 3D Printed 718 Nickel Alloys
Defect-based Fatigue Model for AlSi10Mg Produced by Laser Powder Bed Fusion Process
Design Optimization for Residual Stress in Complex Low-density Support Regions
Development of Temperature History Profiles for Production of Ti-6Al-4V Using a Semi-Analytical Model
Expanding Process Space of Laser Powder Bed Additive Manufacturing Using Alternative Scan Strategies
Experimental and Modeling Study of Gas Adsorption in Metal-organic Framework Coated on 3D Printed Plastics
Fabrication of Ceramic Core for Single Crystal Casting of Gas Turbine Blade
Feature Engineering for Surrogate Models of Consolidation Degree in Additive Manufacturing
In-situ Monitoring of Powder Flow in Direct Energy Deposition Additive Manufacturing
Mechanical and Surface Properties of Inconel 718 Alloy Fabricated by Additive Manufacturing
Modeling Hot Cracking in Metal Additive Manufacturing
Modeling of Electron Beam Physical Vapor Deposition Process for Fabricating Thermal Barrier Coatings
Modeling of Impact Property of 3D Printed 718 Nickel Alloys
Multi-Fidelity Surrogate Assisted Prediction of Melt Pool Geometry in Additive Manufacturing
Phase Field Modeling of AM Solidification Microstructure with Algorithmic Feature Extraction to Facilitate Reduced Order Model Development
Phase Field Simulations of Solid-state Precipitation in AM-processed 625 and 718 Alloys during Post-process Annealing
Probabilistic Process Design of Laser Powder Bed Fusion Using Coupled Monte Carlo and Inverse First Order Reliability Method
Property Measurements for Modeling the Process-structure-property Relationships in Additive Manufacturing
Reduced-order Process-structure Linkages during Post-Process Annealing of an Additively Manufactured Ni-base Alloy
Strength Improvement of The Ceramic Core by Applying Dual Polymers In 3D Printing Process
Stress State Dependent Plasticity and Fracture Properties of Additively Manufactured Stainless Steel 316L
Transient Evolution of Columnar Dendrites during Additive Manufacturing – Implications for Process Simulations
Virtual Reality Module for Additive Manufacturing Education

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