Towards a generalized surrogate model for truss structure analysis using graph learning

This study proposes a novel and efficient surrogate model for performing truss analysis based on graph theory and deep learning algorithms, which is applicable for various truss topologies with different load scenarios without requiring retraining as other Deep Learning (DL)-based counterparts.