AINeutralarXiv – CS AI · Mar 34/105
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Adaptive Uncertainty-Guided Surrogates for Efficient phase field Modeling of Dendritic Solidification
Researchers developed a new AI-powered surrogate model using XGBoost and CNNs to significantly reduce computational costs in phase field simulations for metal solidification processes. The adaptive uncertainty-guided approach achieves accurate predictions while requiring fewer expensive simulations and reducing CO2 emissions in additive manufacturing applications.