Damage identification in offshore structures subject to extreme load events

Offshore structures can be subject to extreme weather events, such as e.g. unusually high waves, which may jeopardize the safety of the structures and increase the susceptibility to failures. Innovation Fund Denmark is funding a new R&D project, which will improve the data-driven decision-making relating to events that could potentially lead to damage of structures.

InnoSHM is a DKK 19 Million innovation project on Digital Twins and Big Data technology for Asset Integrity Management that will support the further development of structural health monitoring and data-driven decision-making, enabling detection of damages caused by for example extreme events. The knowledge acquired during the project can be applied to all types of structures.

A Collaboration Network
Behind the project is a consortium consisting of Danish Hydrocarbon Research and Technology Centre (DHRTC), Technical University of Denmark (DTU), TotalEnergies, Ramboll, Aalborg University (AAU) and Brincker Monitoring ApS. It is funded by Innovation Fund Denmark and supported by DHRTC, which also facilitates the project.

Especially TotalEnergies’ and Ramboll’s experience in modelling, analysis and design of offshore platforms will be utilized to create a wide digital set of simulated platforms, loads and responses, which will then be used by DTU and Aalborg University to pursue high-quality prognosis of various damage scenarios within an advanced probabilistic framework.

Further Development of Existing Methods
Today, existing methods can facilitate monitoring of the health of structures for e.g. lifetime extension of ageing structures and structural integrity management. It will now be further developed to provide important information in case of the rare occurrence of extreme events resulting in damage to the structures.
The “Innovative Structural Health Monitoring (SHM) and Risk-informed Structural Integrity Management” (InnoSHM) project will enable the operators of the structures to know immediately if anything critical has happened to the structures and hence, support critical decision-making processes effectively and safely.

"The R&D project will support the ongoing development of the novel technologies behind the existing data-driven methods within Big Data Technologies including Machine Learning, Artificial Intelligence and Cloud Computing, all in a probabilistic framework," states Ulf Tyge Tygesen, Technical Development Manager at Ramboll Energy. Ulf Tyge Tygesen is the creator of Ramboll’s existing True Digital Twin technology and has developed the technology over the last 20 years.

Paving the Way for Other Industries
The knowledge gained in the InnoSHM project will create additional value to operators of all structures, including offshore structures such as wind farms and oil and gas platforms, and other structures like buildings, bridges, towers, railways etc.

When it comes to asset integrity management based on real-time monitoring and data-driven decision-making, i.e. covering both lifetime extension, predictive maintenance and damage detection, the full cycle will be completed by the project.

"The project will develop and deliver new technologies facilitating that the built environment in the future may be developed and maintained more efficiently, resilient and sustainable – without compromising safety and functionality. At the same time, the project facilitates that the offshore oil and gas production, which society still needs to enable the global transition to renewable energies, may be undertaken safely for personnel and the environment", says Michael Faber, Professor at Aalborg University.