Dataset for: A Position-Encoded Physics-Informed Neural Network with Aleatoric Uncertainty-Based Adaptive Weighting for Extreme Multi-Scale ICF Implosion Modeling
Sun, Chenlei;
Dataset for: A Position-Encoded Physics-Informed Neural Network with Aleatoric Uncertainty-Based Adaptive Weighting for Extreme Multi-Scale ICF Implosion Modeling
This dataset contains the multi-scale radiation-hydrodynamic simulation data used in the paper "A Position-Encoded Physics-Informed Neural Network with Aleatoric Uncertainty-Based Adaptive Weighting for Extreme Multi-Scale ICF Implosion Modeling". Data Generation:The data models the glide and stagnation phases of the central ignition implosion process in Inertial Confinement Fusion (ICF). The simulations were generated using the open-source MULTI-2D radiation hydrodynamics code. Code Availability:The official PyTorch implementation for the PE-AUAW-PINN framework associated with this dataset is available on GitHub at: [sclwudao/PE-AUAW-PINN-for-ICF-Implosion_github]