A digital twin to optimize monitoring and maintenance of pressure vessels

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.