首页|Accelerating the solving of mechanical equilibrium caused by lattice misfit through deep learning method
Accelerating the solving of mechanical equilibrium caused by lattice misfit through deep learning method
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Precipitation is a common phenomenon that occurs during heat treatments.There is internal stress around the precipitate owing to the lattice misfit between the pre-cipitate and matrix.This internal stress has a significant influence not only on the precipitation kinetics but also on the material properties.The misfit stress can be obtained by numerically solving the mechanical equilibrium equations.However,this process is complex and time-consuming.We developed a new approach based on deep learning to acceler-ate the solution process.The training data were first gener-ated by a phase-field model coupled with elastic mechanical equilibrium equations,which were solved using the finite difference method.The obtained precipitate morphologies and corresponding stress distributions were input data for training the physics-informed(PI)UNet model.The well-trained PI-UNet model can then be applied to predicting stress distributions with the precipitate morphology as the input.Prediction accuracy and efficiency are discussed in this study.The results showed that the PI-UNet model was an appropriate approach for quickly predicting the misfit stress between the precipitate and matrix.
Collaborative Innovation Center of Steel Technology,University of Science and Technology Beijing,Beijing 100083,People's Republic of China
Beijing Laboratory of Metallic Materials and Processing for Modern Transportation,University of Science and Technology Beijing,Beijing 100083,People's Republic of China
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