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About this Symposium
Meeting 2025 TMS Annual Meeting & Exhibition
Symposium Additive Manufacturing Modeling, Simulation and Machine Learning
Sponsorship TMS Materials Processing and Manufacturing Division
TMS: Additive Manufacturing Committee
TMS: Integrated Computational Materials Engineering Committee
Organizer(s) Jing Zhang, Purdue University in Indianapolis
Li Ma, Johns Hopkins University Applied Physics Laboratory
Charles R. Fisher, Naval Surface Warfare Center - Carderock
Brandon A. McWilliams, US Army Research Laboratory
Yeon-Gil Jung, Changwon National University
Scope This symposium will provide an excellent platform to exchange the latest knowledge in additive manufacturing (AM) modeling, simulation, artificial intelligence and machine learning. Despite extensive progress in AM field, there are still many challenges in predictive theoretical and computational approaches that hinder the advance of AM technologies. 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.AM process modeling, monitoring and defect detection
2.Modeling of microstructure evolution, phase transformation, and defect formation in AM parts
3.AM materials development using the Integrated computational materials engineering (ICME) approach
4.Modeling of residual stress, distortion, plasticity/damage, creep, and fatigue in AM parts
5.Modeling behaviors of AM materials in various environments (e.g., corrosion, high temperature, etc.)
6.Computational modeling of process-structure-property-performance relationships for qualification of additive manufacturing
7.Artificial intelligence (AI), machine learning (ML) and data science applications to AM
8.Calibration and validation data sets relevant to models, uncertainty quantification
9.Efficient computational methods using reduced-order models or fast emulators for process control
10.Multiscale/multiphysics modeling strategies, including any or all of the scales associated with the spatial, temporal, and/or material domains

Abstracts Due 07/15/2024
Proceedings Plan Planned:
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE

A data driven framework to predict and bridge multiscale mechanical phenomenon in additively manufactured component
A Deep Learning Framework for Predicting Surface Deformation of Alloys under Uniaxial Tensile Loading at Microscopic Length Scale
A machine learning-based approach for process optimization in laser based 3-D printing of high-performance Al-alloys
A New Fast Solidification Cracking Indexing Tool for Metallic Alloys
A Numerical Analysis of Solidification Microstructure Dependence on Solidification Characteristics in Laser Based Additive Manufacturing
A Resource-Effective In-situ Process Monitoring Framework for Defect Detection and Quality Assurance
Abstract Title: Large Language Models for Distilling Knowledge in Additive Manufacturing
Accelerating Crystal Plasticity Fatigue Simulations of Additively Manufactured Metals Using the “Materialize” Framework
Additive Manufacturing Digital Twin (AMDT): Part Level Process Map Characterization Using Physics Based Simulation and Machine Learning
Additive Manufacturing Guided with High-Speed Photography and Machine Learning
Additive Manufacturing Process Modeling with Multi-Output Gaussian Processes
Additive Manufacturing User Interface (AMUI): An Intuitive Software Suite for Part Level Process Parameter Selection
AiDED - Accurate machine learning inference framework for process parameter optimization in laser Directed Energy Deposition
AlloyGPT: an agent-based LLM framework for the design of additively manufactured structural alloys in extreme environments
AM microstructure image prediction using dimension reduction
AMMap Library of Additive Manufacturing Design, Alloy Discovery, and Path Planning
Anomaly Detection via In-situ Monitoring and Machine Learning
Application of Multi-Physics Simulations and Machine Learning to Predict Spatter in Laser Powder Bed Fusion
Can Machine Learning Predict the Liquidus Temperature of Binary Alloys?
Characterization & modeling of highly directional SS316L microstructure as fabricated by the Area Printing® additive manufacturing process
Comprehensive analysis of 316L samples fabricated via Directed Energy Deposition: integrating simulation with microstructural and mechanical evaluations
Computational materials design for multimaterial additive manufacturing
Controlling Bubble Transport with External Magnetic Fields in Additive Manufacturing
Controlling microstructure and defect through physics-informed machine learning in laser powder bed fusion process
Correlating processing, microstructure and property with machine learning for powder-bed fusion additive manufacturing
Development of a Microstructure-Informed CPFE Model for the High-Temperature Application of SLM Inconel 718 Alloy
Development of a Steady-State 3D Heat Transfer and Materials Flow Model for Multi-Layer Additive Friction Stir Deposition
Digital Shadow Model Reference Control for Directed Energy Deposition
Effect of Interpass Temperature on the Residual Stress Evolution in a Nickel-Aluminum Bronze Wire-Arc Additive Manufacturing Build
Effect of nucleation model and data resolution on cellular automata texture strength prediction
Efficient Laser Powder Bed Fusion Microstructure and Texture Modeling
Elastoplastic Thermomechanical Simulation of Powder Bed Fusion Incorporating Isotropic Strain Hardening and Cyclic Hardening/Softening Effects: A Comprehensive Approach
Enabling Part-Scale Microstructure Modeling in Powder Bed Fusion
Evaluating Absorptivity from Surface Temperature Measurements of Tracks Produced by Direct Laser Metal Deposition
Finite Element Analysis of Deposition Strategies in Dissimilar Metal Additive Manufacturing
First-principle investigation and modeling of airborne acoustic emission mechanisms in selective laser-metal fusion printing processes
Full-Field Crystal Plasticity Surrogate Modeling for Rapid Defect Assessment in AM Materials
Gaussian Process Regression Modelling and Texture Control during Hot Deformation of Additively Manufactured Maraging Steels
Generative property optimization of stochastic microstructures
Hierarchical Machine Learning Framework for Optimizing Material Properties.
High-fidelity Numerical Simulation of Droplet-Powder Bed Interactions in Binder Jet Additive Manufacturing.
High fidelity modeling of laser absorptivity and molten pool geometry during powderbed fusion processes of Ti64Al4V with the stationary and moving laser beam sources
Hyperspectral In-Situ Process Monitoring with High-Speed Infrared Pyrometry, Eddy Current Testing, and Machine Learning, for Predictive Analysis of AM Part Properties
Impact of Infill Density and Raster Angle on 3D Printed High Impact Polystyrene (HIPS) Tensile Behavior
Implementation of alloy-specific thermo-fluid modelling for designing Mg alloys suitable for laser powder-bed fusion
Integrating CAFE with MOOSE for Microstructure Evolution Analysis in 316L Stainless Steel 3D Printing Process
Interpretable machine learning approach for exploring process-structure-property relationships in metal additive manufacturing
LLM Agents for 3D Printing Error Detection and Correction
Local Stress Analysis of Ti5553 Lattice Structures Under Mixed Mode Stresses
Machine Learning-Driven Predictions of Material Printability in Laser Powder Bed Fusion
Machine Learning Assisted Predictions of Thermal and Stress Profiles During Laser-based Additive Manufacturing
Machine Learning Enabled Process Optimization during 3D Printing of Tablets
Machine Learning Guided Prediction of Printability During Additive Manufacturing
Machine Vision-enabled Defect Characterization in Additively Manufactured Steels
Mathematical Quantification of Meniscus Fluctuations and Asymmetries in a Medium-Thin Slab Mold
Mathematical Study of Partial Blockage of SEN in Specific Zones on Flow Patterns in the Mold
Mechanical behavior of additively manufactured metamaterials under dynamic load
Mechanical Evaluation of Nested Structures Using Finite Element Analysis
Melt Pool Width Prediction With Machine Learning In Selective Laser Melting
Micromechanical Modeling Exploration of Microstructure-Properties of Additively Manufactured Pure Tantalum
Microstructural investigation and numerical analysis and observation of additively manufactured anti-tetra-chiral 316L stainless steel samples
Microstructure Evolution and the Influence on Material Properties in Additive Manufacturing
Microstructure Prediction in Laser Powder Bed Fusion via Physics-Based Modeling and In-situ Sensor Data Fusion
Modeling And Simulation Of The Shock Response Of Additively Manufactured High-Performance Steel
Modeling fatigue crack initiation and propagation life in additively manufactured alloys across fatigue regimes
Modeling GMA-DED Bead and Layer Geometry for Defect Elimination
Modeling the impact of defects on the mechanical performance of 3D printed natural carbon-enhanced polymer composite structures.
Multi-fidelity surrogate for integrating melt pool models across diverse input spaces
Multi-Objective Study on Optimization of WAAM Parameters for Optimal Material Properties
Multi-phase-field modeling and high-performance simulations for grain structures depending on scanning strategy during PBF additive manufacturing
Numerical analysis of the flow and orientation of reinforcements in a polymer matrix during flow through a nozzle in direct ink writing process
Numerical and experimental investigations of thermal debinding and sintering in low-temperature additive manufacturing of magnesium alloys
On the of rapid solidification in additive manufacturing conditions by combining multiscale simulations and in-situ monitoring techniques
Performance Optimization of Additively Manufactured β-TI5553 Alloy Lattice Structures: A Methodical Approach Integrating Topology and Strut-Level Microstructure
Physics-based and data-driven ICME for metal additive manufacturing: from feedstock to process optimization
Prediction of Thermal Profile of Heat-Affected Zone during Laser Cladding from a Long-wavelength Infrared Camera
Preventing Substrate Distortion Using Hybrid Additive and Subtractive Approach
Quantification of defects in additively manufactured steel using unsupervised machine learning
Quantifying the Characteristics of Pore Features using Gaussian Process Machine Learning in LPBF Process Parameter Space
Rapid Parameter Set Development and Printability Optimization for Laser Powder Bed Fusion using ICMD® Materials Design Software
Real-time Detection of Keyhole Pore Generation in Laser Powder Bed Fusion via A Multi-sensor System and Physics-informed Machine Learning
Residual stress evaluation in the laser powder bed fusion of hybrid alloys
Revisiting the Stefan Problem for Accurate AM Modeling
Self-supervised vision transformers for anomaly detection in 3D printing
Sensing-Based AM Process Mapping to Improve Reliability
Simulation and Testing of Additively Manufactured Polyethylene Terephthalate Glycol (PETG) Tensile Specimens
Simulation of Melt Pool Dynamics in Wire-based and Powder-based Directed Energy Deposition
Synchrotron-Based In Situ/Operando Characterization Capabilities at NSLS-II
Systematic procedure for converting a hollow 3D surface scan (3DSS) to a functional solid model for the use in Finite Element Analysis
Thermo-mechanical modeling and validation of residual stress during metal laser powder bed fusion and post-build stress relief heat treatment processes
Thermo-Mechanical Modeling of Additively Manufactured Ceramic Parts through Stereolithography
Topology of cellular structures with the targeted non-linear mechanical response
Towards a fully predictive Additive Manufacturing module.
Understanding Structure-Property Interplay in 3D Printed Gyroid TPMS Lattices
Use of Sacrificial Structures for Managing Distortion and Residual Stresses in Large-Scale Hybrid Additive and Subtractive Manufacturing
Using part-scale in-situ defect formation monitoring to assist post-build qualification and predict fatigue performance in LPBF


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