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Meeting 2021 TMS Annual Meeting & Exhibition
Symposium Algorithm Development in Materials Science and Engineering
Presentation Title Dislocation Dipole Study on Material Hardening/Softening
Author(s) Abu Siddique, Tariq A Khraishi, Hojun Lim
On-Site Speaker (Planned) Abu Siddique
Abstract Scope Dislocation dynamics simulations often reveal interesting phenomena in regards to material deformation which may not be captured by experiments. In this work, we investigate the effect of dislocation dipoles on plastic material properties under different dipole configurations (i.e. size of the dislocation sources, the distance between active glide planes, and the signs of two dislocations) using a Discrete Dislocation Dynamics code. The simulations show that a dipole is causing hardening effect when the Burgers vectors of the dislocations forming a dipole are of opposite sign and causing a softening effect when they are of the same sign. The distance between the two neighboring dislocations in a dipole was affecting the elastic limit of the material and not the flow stress of the material. Such hardening or flow stress results as in this study can be incorporated in higher scale modeling work.
Proceedings Inclusion? Planned:
Keywords Modeling and Simulation, Computational Materials Science & Engineering, Mechanical Properties

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Comparison of Correction Schemes for Charged Point Defects in 2D Materials
Computational Synthesis of Substrates by Crystal Cleavage
Deep Learning for Characterization of Deformation Induced Damage
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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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Understanding Grain Boundary Metastability Using the SOAP Descriptor and Unsupervised Machine Learning Techniques

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