A Fast and Generalizable Fourier Neural Operator-Based Surrogate for Melt-Pool Prediction in Laser Processing
The episode discusses a Fourier Neural Operator model for predicting melt-pool behavior in laser processing. Hosts detail how this model rapidly maps process parameters to 3D temperature fields and boundaries across diverse regimes. This capability enables robust, real-time surrogate modeling, allowing for precise control systems in industrial manufacturing.