Abstract
Wind turbine capacity is increasing every year with new innovations and so does the size of wind turbine jacket foundations. This paper presents the development of a Structural digital twin solution for a physical asset, namely the ‘lifting frame arrangement’ that is designed for up-righting wind farm jackets from a horizontally built condition to a vertical condition in a construction yard. The lifting frame arrangement is a crane-type structure with a fixed foundation, a fixed boom structure, and strand jacks mounted at the tip of the booms. The lifting frame is designed, fabricated, installed, operated, and maintained with strategic objectives to reduce the cost, schedule, and project risks.
The operational safety and structural integrity of the lifting frame system during the up-righting of jackets, were assured through several detailed design substantiation processes, which included certification by DNV. If we consider capital expenditure (CAPEX) cost as USD X Millions, then operating expenditure (OPEX) cost is about 0.05X Millions USD. OPEX cost of the lifting infrastructure increases at incremental rate year on year once the asset approaches its design life. Structural digital twin of the lifting frame has minimized OPEX costs by 50% while assuring the structural integrity of the complete system by near real time monitoring of asset health. This structural digital twin solution may also enable the enhancement in the capacity of the lifting frame, by revisiting the design safety factors based on the operational history and measured stresses and reactions, ensuring that the lifting frame becomes suitable for upending heavier jackets than designed.
This paper illustrates the stepwise details followed to develop the digital twin solution; the sensors used for monitoring operations as well as the status of the structural health of the lifting frame during operation. The reduced basis finite element analysis (RB-FEA-[2]) was followed using Akselos’ software for near real time integration of sensor data with analysis model.
