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Meeting 2021 TMS Annual Meeting & Exhibition
Symposium Algorithm Development in Materials Science and Engineering
Presentation Title Analysis of Dendrite Growth and Microstructure Evolution during Solidification of Al 6061 via 2D and 3D Phase Field Models
Author(s) Neil Bailey, Yung C. Shin
On-Site Speaker (Planned) Yung C. Shin
Abstract Scope A 3-dimensional (3D) phase field model is developed and used to predict dendrite growth and microstructure development during the laser welding processes of Al 6061 alloy. A 2D version of the model is used to validate the model using isothermal solidification of an Al-4wt.%Cu alloy to compare, with good agreement between dendrite growth velocity and overall morphology. The 3D model is then used to simulate dendrite growth and microstructure development in a laser welding process using Al 6061. By using a validated, comprehensive laser welding model to calculate the complex and strongly transient temperature field, the predicted 2D cross-sections of the 3D simulated microstructure are compared with micrographs from an experimental workpiece as well as 2D simulated results. The 2D cross-sections taken from the 3D simulation results match well with the experimental micrographs and they are a better prediction of dendrite growth and solidification microstructure than the 2D simulation results.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, ICME, Joining

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A Simulation Survey of Recrystallization Behavior in Al-xSi Microstructures Under Shear Loading Conditions
Accelerating Atomistic Monte Carlo Simulations with Autoregressive Models
Advancements in Discrete Dislocation Modeling of Slip Transmission through Equilibrium and Non-equilibrium Grain Boundaries
AI-assisted Analysis of Flame Stability
Analysis of Dendrite Growth and Microstructure Evolution during Solidification of Al 6061 via 2D and 3D Phase Field Models
Application of a Shape Moment Descriptor Set Towards a Robust and Transferable Description of Local Atomic Environments
Automatic Segmentation of Microstructures in Steel Using Machine Learning Methods
Bayesian Data Assimilation for Phase-field Simulation of Solid-state Sintering
Characterizing Atomistic Geometries and Potential Functions Using Strain Functionals
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Comparison of Correction Schemes for Charged Point Defects in 2D Materials
Computational Synthesis of Substrates by Crystal Cleavage
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Exascale-motivated Algorithm Development for Nano and Mesoscale Materials Methods
Full-field Stress Computation from Measured Deformation Fields: A Hyperbolic Formulation
Global Local Modeling of Melt Pool Dynamics and Bead Formation in Laser Bed Powder Fusion Process Using a Comprehensive Multi-Physics Simulation
Grain Boundary Network Optimization through Human Computation and Machine Learning
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Real Time Boundary Condition Acquisition and Integration of Heats of Fusion and Phase Transformation Using an Implicit Finite Element Newton Raphson Based Approach for Thermal Behavior Prediction in Additively Manufactured Parts
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Tusas: A Modern Computational Approach for Microstructure Evolution Toward Exascale
Understanding Grain Boundary Metastability Using the SOAP Descriptor and Unsupervised Machine Learning Techniques

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