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Meeting MS&T21: Materials Science & Technology
Symposium Additive Manufacturing Modeling and Simulation: Microstructure, Mechanics, and Process
Presentation Title Deep Learning Prediction of Stress Fields in Additively Manufactured Metals with Intricate Defect Networks
Author(s) Brendan P. Croom, Michael Berkson, Bobby Mueller, Michael Presley, Steven M Storck
On-Site Speaker (Planned) Brendan P. Croom
Abstract Scope In context of the universal presence of defects in additively manufactured (AM) metals, efficient computational tools are required to rapidly screen AM microstructures for mechanical integrity. To this end, a deep learning approach is used to predict the elastic stress fields in images of defect-containing metal microstructures. A large dataset consisting of the stress response of 100,000 random microstructure images is generated using high-resolution Fast Fourier Transform-based finite element (FFT-FE) calculations, which is then used to train a modified U-Net style convolutional neural network (CNN) model. The trained U-Net model more accurately predicted the stress response compared to previous CNN architectures, and exceeded the accuracy of low-resolution FFT-FE calculations. The model was applied to images of real AM microstructures with severe lack of fusion defects, and predicted a strong linear increase of maximum stress as a function of pore fraction.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Computational Approach for Establishing Microstructure-property Relationships for Additively Manufactured IN718
A Microstructure-informed Multiscale Computational Model for Additively Manufactured (AM) Metals and Alloys
Cellular Automaton Simulation of Three-dimensional Microstructure Evolution during Powder Bed Fusion Additive Manufacturing
CFD Simulations for Additive Manufacturing
Comparison of Commercial Additive Manufacturing Simulation Tools for Full Build Analysis
Deep Learning Prediction of Stress Fields in Additively Manufactured Metals with Intricate Defect Networks
Deep Reinforcement Learning for Defect Mitigation in Laser Powder Bed Fusion
Defect Prediction thru Part-scale Simulation
Distortion Modeling during Sintering of Binder Jet Printed Parts
Ductile Fracture of Ti-6Al-4V Made by Powder Bed Fusion Additive Manufacturing
Gas Adsorption Analysis in 3D Printed Metal Organic Frameworks
Grain-scale Residual Stress Modeling in Wire Arc Additive Manufacturing of Haynes 282 Super Alloy
Grain Refinement and Mechanical Properties for AISI304 Stainless Steel Single-tracks by Laser Melting Deposition: Mathematical Modelling versus Experimental Results
Improving the Mechanical Performance of AlSi10Mg Lattice Structures Manufactured by Laser Powder Bed Fusion (L-PBF)
Inherent Strain Method for Residual Stress Prediction in Ferritic-austenitic Steel Structure Fabricated by Directed Energy Deposition
Interfacial Properties in 3D Printed Stainless Steel Coated with Epoxy
Machine Learning – Assisted Navigation in the Additive Manufacturing Design Space
Mechanical Properties of Ceramic Core with SiO2-Na2O-Al2O3 Ternary Binder System
Melt Pool Scale Modeling of Austenitic Stainless Steel Solidification Features in Laser Powder Bed Fusion
Mitigating Stray Grain Nucleation during the Laser Powder Bed Fusion of Single Crystal CMSX-4
Model the Initiation of Hot Cracking during Laser Welding of Al6061
Modeling and Experimental Validation of Stresses in 3D Printed, Polymeric Biliary Stents
Modeling Collapse Behavior in Large-scale Thermoset Additive Manufacturing
Multiscale Material Modeling of Laser Powder Bed Fusion Additive Manufacturing Soft Magnetic Composites
Now On-Demand Only - Influence of Microstructure on Fatigue Crack Growth: An Combined Experiment and Model Investigation in EBM Nickel-Based Supper Alloy Haynes 282
Numerical Simulations of Fracture Tests of Uncharged and Hydrogen-charged Bend Specimens of Additively Manufactured 304 Stainless Steel Using Nodal Release Method and Cohesive Zone Model
Online Characterization of Melt Pool Dimensions Using Acoustic Monitoring and Deep Learning
P3-1: Creep Modeling of 3D Printed Nickel Based Superalloy
P3-2: Design A Syringe Pump Extruder Type 3D Bioprinter
P3-3: Finite Element Modeling of Coating Thickness Prediction in Electron Beam Physical Vapor Deposition Process
P3-4: Modeling Charpy Impact Property of 3D Printed 718 Nickel Alloys Using the Smoothed Particle Hydrodynamics Method
P3-5: Reinforcement Learning Aided Simulations for Determining Process Parameters for Optimizing Microstructure in LPBF Additive Manufacturing Parts
P3-6: Student Design Project of Design a Mechanical Ventilator Prototype during the Pandemic
P3-7: Virtual Reality Modules of 3D Printing Laboratories for Additive Manufacturing Education
Preparation of Ceramic Green Body with Uniform Density through Living Properties of Cycloaliphatic Epoxy Resins in DLP(Digital Light Processing) 3D Printing of Ceramics
Process Consistency in Laser Powder Bed Fusion Observed Through Large Scale Single Bead Melt Pool Measurements
Process Maps and Models For Highly Filled Polymers In Powder Fused Filament Fabrication (PF3) 3D Printing
Residual Stress Induced Cracking Modeling
Spattering and Associated Pore Formation Modeling for Laser Powder Bed Fusion of Inconel 718
Thermal History of LPBF Components Towards Predicting As-built Material Properties

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