Digital twin for real-time pressure vessels fatigue life prediction

Digital twins (DT) represent a groundbreaking advancement in industrial process management. They serve as faithful virtual replicas of a physical process or equipment, enabling a comprehensive understanding of its real-time behavior. These duplicates evolve over time in synchronization with the physical twin, being updated at a frequency and precision appropriate to the monitored issue. This article aims to develop a DT for monitoring fatigue damage in Pressure Vessels (PVs). This DT relies on the integration of several innovative technologies like Internet of Things (IoT) and simulation. IoT facilitates data transmission to the DT for real-time monitoring and continuous acquisition of the physical state. Integrated simulation provides a precise representation of the behavior of the physical vessel. To this end, a Finite Element (FE) numerical model is developed to simulate the mechanical behavior of the equipment under cyclic loading. This model is validated using experimental data obtained from inspections and instrumentation conducted on the PV, ensuring its alignment with the real physical model. Various fatigue criteria, both uniaxial and multiaxial, are examined and compared numerically to determine the most appropriate one for this specific case study. The approach based on the S/N curve, which employs the maximum principal stress as the equivalent stress to represent the simple multiaxial local state, is selected. Finally, all these components are integrated to allow the DT to regularly follow the fatigue damage state.