PSI - Issue 80

Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2022) 000–000 Available online at www.sciencedirect.com Structural Integrity Procedia 00 (2022) 000–000

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ScienceDirect

Procedia Structural Integrity 80 (2026) 136–145

Fracture, Damage and Structural Health Monitoring A digital twin to optimize monitoring and maintenance of pressure vessels

M. Bennebach a , I. Khaled a , JL. Iwaniack a, * a Centre technique des Industries Mécaniques, Senlis 60304, France a a a, a Centre technique des Industries Mécaniques, Senlis 60304, France

© 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Ferri Aliabadi When used online, the developed digital twin can 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. If used offline, it allows simulating different loading scenarios and evaluating their impact on the equipment’s life. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Professor Ferri Aliabadi Keywords: Digital twin, pressure vessel, fatigue, monitoring, predictive maintenance Abstract A digital twin is a virtual clone of a physical system or a process. It systematically implies the existence of a "digital model" coupled with the object it copies. Depending on the system concerned and the desired usage, it can be a geometric, multiphysical, functional, behavioral, and decision-making model. It can be used to improve the control, security and optimize production, ensuring digital continuity. Applied to pressure vessels, the digital twin appears as a reliable way to monitor operation, evaluate resistance and safety in real service conditions, and finally to capitalize on data to optimize the design of new products. This paper presents an application of the digital twin concept to optimize predictive maintenance of an industrial polymerization reactor. The steps involved in this work are: - Design, manufacturing of the physical twin and optimized deployment of sensors for a smart, connected device, - Fatigue testing under representative loads, - Modeling of the reactor behavior and construction of the digital twin by hybridization of physical / data models. When used online, the developed digital twin can 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. If used offline, it allows simulating different loading scenarios and evaluating their impact on the equipment’s life. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Professor Ferri Aliabadi Keywords: Digital twin, pressure vessel, fatigue, monitoring, predictive maintenance Abstract A digital twin is a virtual clone of a physical system or a process. It systematically implies the existence of a "digital model" coupled with the object it copies. Depending on the system concerned and the desired usage, it can be a geometric, multiphysical, functional, behavioral, and decision-making model. It can be used to improve the control, security and optimize production, ensuring digital continuity. Applied to pressure vessels, the digital twin appears as a reliable way to monitor operation, evaluate resistance and safety in real service conditions, and finally to capitalize on data to optimize the design of new products. This paper presents an application of the digital twin concept to optimize predictive maintenance of an industrial polymerization reactor. The steps involved in this work are: - Design, manufacturing of the physical twin and optimized deployment of sensors for a smart, connected device, - Fatigue testing under representative loads, - Modeling of the reactor behavior and construction of the digital twin by hybridization of physical / data models.

* Corresponding author. Tel.: +33 637454934. E-mail address: mohamed.bennebach@cetim.fr * Corresponding author. Tel.: +33 637454934. E-mail address: mohamed.bennebach@cetim.fr

2452-3216 © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Professor Ferri Aliabadi 2452-3216 © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Professor Ferri Aliabadi

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Ferri Aliabadi 10.1016/j.prostr.2026.02.013