A Digital Twin Framework for Real-Time Damage Localization and Stress Field Prediction in Plate Structures

This paper reports on the progress of the ongoing Cal Poly Pomona Digital Twin Tech- nology for Aerospace Engineering (CPP-DiTTA) project. In its present form, CPP-DiTTA employs a set of trained neural networks to predict the location of damage in a plate struc- ture from a limited number of strain-gauge measurements, estimate the corresponding stress field under the applied load, and forecast the stress response under alternative load- ing conditions. These capabilities allow users not only to identify damage relative to the pristine configuration but also to evaluate how the structure behaves under different loads and to make more informed decisions about structural performance. CPP-DiTTA includes a visualization module that renders the predicted stress fields and is deployed on a publicly accessible website to support educational use and demonstration.