PSI - Issue 80

M. Bennebach et al. / Procedia Structural Integrity 80 (2026) 136–145 Author name / Structural Integrity Procedia 00 (2019) 000–000

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Fig.11. Resistance SN curves for different fatigue classes

5. Conclusion In this work, a digital twin of a pressure vessel has been successfully developed to monitor and optimize maintenance of the equipment. The steps involved are: - Design, manufacturing of the physical twin and optimized deployment of sensors for a smart, connected device, - Conducting tests under representative loads, - Development of a representative FE model, - Dynamic modeling of the reactor behavior by machine learning from data, - Construction of the digital twin by hybridization of physical/data models. The proposed digital twin is able to estimate the progressive fatigue damage of the equipment. It can regularly monitor the evolution of loading in real-time and update itself with data from the physical model in service. Additionally, it can monitor hardly accessible critical areas, facilitating decisions making about future inspections. It can also be used offline to simulate different loading scenarios and evaluate their impact on the equipment’s life. Figure 12 shows the actual demonstrator in operation.

Fig. 12. The complete pressure vessel digital twin demonstrator