Physics-Informed Neural Network for Sparse-Sensor Inverse Heat Conduction
This study develops a sparse-sensor physics-informed neural network (PINN) to reconstruct a transient two-dimensional thermalfield and identify thermal diffusivity, volumetric heat loss, and source amplitude from noisy point measurements. Sixteen interiorsensors provide 5424 observations for a moving-source benchmark....