Abstract
We propose an artificial intelligence (AI) modeling method that utilizes an arbitrary voxelized mesh of a small PCB via structure, without relying on parametric geometry. Our AI model, based on a multilayer convolutional neural network (CNN), significantly reduces simulation time for small PCB via structures. By employing advanced AI techniques, we enhance the accuracy and quality of predictions while substantially reducing the size of the neural network model compared to our previous work using a fully connected neural network (FCN). The CNN-based model predicts 2-port scattering parameters with a median Huber error of 0.16%, achieving computational speeds over 13,000 times faster than traditional full-wave field solvers.