Digital Twin Method for Real-Time Stress Prediction Based on Surrogate Model

In response to the challenge of real-time monitoring and early warning of structural safety, a digital twin method for real-time stress prediction based on surrogate modeling is proposed. By employing techniques such as numerical simulation, surrogate model algorithms, and digital twin technology, a digital twin focusing on structural mechanical performance is constructed. It enables real-time prediction and three-dimensional visualization of structural stress under different conditional input data, thus laying the foundation for real-time monitoring, analysis, and safety early warning of equipment operating status. Moreover, it serves as a valuable tool to assist in making informed decisions. The feasibility of the proposed method is validated through a truss structure example.