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Digital Twin-Based Asset Management: Learning from the Offshore Industry

Digital Twin technology has special applications for optimized operational performance and for predicted life-cycle management.

A novel concept for lifetime extension and reduction of maintenance costs for offshore structures has been developed by Danish-headquartered consultancy Ramboll. The concept – known as True Digital Twin -- can be used in asset management for facilities in other parts of the energy sector. It has special applications for optimized operational performance and for predicted life-cycle management.

In the North Sea between the United Kingdom, Denmark, Norway, Sweden, Germany, the Netherlands, Belgium and France, more than 600 offshore structures have exceeded or will soon exceed their original design lifetime. The industry is facing extensive investments to upgrade or reinforce the existing infrastructure, to maintain the present oil and gas production in the future. The alternative for many installations is to consider decommissioning of outdated production facilities and consequently face significant reductions in the oil and gas production.

To be able to choose the best strategy, the decision-makers need thorough insight into the actual condition of their installations to establish a solution which ensures economic profitability, environmental protection and human safety. It is essential for the decision-makers to possess reliable prediction models of their assets.

These models - or digital twins - have been used for many years in the offshore industry. Essentially, a digital twin is a digital copy of a structure, which makes it possible to assess the structural health of an asset and provide valuable knowledge about its expected future behaviour.

But do they actually provide a sound and reliable prediction of the present condition?  Technical Development Manager at Ramboll Ulf T. Tygesen, who is the master mind behind the True Digital Twin technology, says: “The condition of an offshore platform may have changed multiple times during its operational life due to naturally occurring degradation mechanism’s and/or other structural changes like new platform extensions, increase in topside masses etc. During the lifetime of the structure, the prediction model therefore has to be modified to reflect the actual conditions of the structure.”

And this is where the True Digital Twin comes into the picture. To provide information on the performance and the level of uncertainty of the digital twin model, Ramboll has developed a methodology to facilitate a coupling between the real physical conditions and their digital twins. The real conditions are identified by means of a Structural Health and Monitoring System (SHMS), which provides information about the actual environmental loads and the corresponding structural response, and the data from the monitoring system are analysed through Ramboll’s advanced cloud computing solution for improving the performance of the digital twin.

Ulf T. Tygesen explains the true digital twin concept: “Throughout the past 24 years Ramboll has developed novel methods for assessing the real/measured uncertainties associated with the analysis of platforms. The concept of the True Digital Twin combines innovative structural health monitoring with digitalization, and it differs from other digital twin concepts by the introduced advanced methods for model updating, quantification of model uncertainties and the direct link to Risk- and Reliability-Based Inspection planning (RBI). With the new technology you go from costly and time-consuming experimental testing in the laboratory to cost-reducing full-scale testing in the field under real operational conditions. The digital twin allows for assessing, testing and optimizing the structures in a virtual world.”

Being part of Ramboll’s Digitalization & Innovation Strategy, the Digital Twin technology is based on disciplines normally not related with traditional civil engineering disciplines. The technology draws on Machine Learning, Data Mining and Pattern Recognition algorithms as well as Computer Science and Cloud Computing (HPC) and produces large amounts of data during operation using Big Data analytics.

Also, the implementation of the latest development techniques within reduced order modelling, sub-modelling and super-element modelling significantly increases analysis speed to a level never experienced before. “It is unique in the industry today and allows for on-line updating of the digital twin to large amounts of measured data in real time, which was not possible just a few years ago”, says Ulf T. Tygesen.

The concept was first used in 2006 for an offshore platform, and since then its validity has been verified on projects for all operators in the Danish part of the North Sea, including INEO, TOTAL and HESS. Earlier this year Ramboll also entered a contract with Equinor (former Statoil) for the use of the True Digital Twin technology for two offshore installations and a bridge in the Norwegian sector. Ramboll has during the last couple of years further developed this ground-breaking technology together with international universities, which are among others sponsored by Los Alamos National Laboratories, New Mexico, supporting state-of-the-art technology development.

“The True Digital Twin technology can be transferred to other parts of the energy sector. It is particularly relevant for wind turbines, towers for power transmission and power distribution solutions for further optimization of today’s analysis methods. The only requirement for application of the technology within other sectors than the offshore sector is the availability of the preferred prediction models and the availability of physical measurements from a set of sensors (e.g. IoT). A True Digital Twin is gradually established by advanced on-line model updating of the predictions models using Machine Learning algorithms against actual monitored behaviour of the real physical world”, concludes Ulf T. Tygesen.

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