Risks of structural damage on ships can be assessed and simulated using digital twins to manage hull inspection programmes
Digital twins can help owners, operators and class societies predict the structural performance of ships, said DNV GL principal specialist Gaute Storhaug at Riviera Maritime Media’s How digital twins drive vessel efficiency and voyage performance webinar on 13 May.
He described the importance of using digital twins to understand the structural performance of ships and to identify points vulnerable to damage.
“Structural damage can have severe consequences,” he said, such as hull breakup and sea pollution. “We have inspection regimes to mitigate these risks.” This involves full inspections every five years by class surveyors, but this could be extended to seven years for certain ships.
“We want to have an inspection regime that relates to the risk of your vessel,” Mr Storhaug said. The design assumptions could differ from real operations. Two similar ships, operating in varying environments could have different risks of structural damage, such as fatigue cracks to hull structures.
For a ship operating in calm environments, the period between class surveys could be extended. But for a tanker operating in harsher environments, this period could be shortened, with inspections focused on the most vulnerable points.
Digital twins of ships could be used to monitor structural performance. DNV GL has an indicator tool to calculate the risk of fatigue cracking and overloading on ships within a fleet.
“This uses machine learning, ship position (AIS) and global wave data, so we can reveal which ships are most at risk among a huge fleet,” said Mr Storhaug. A traffic light system is used – of green, orange and red indicating the most at risk – but it has limitations.
“You do not know the details of which critical structural details you should inspect,” he said. For that DNV GL creates a numerical twin of a ship’s hull structure based on design models and matches ship positions with wave data.
Engineers can virtually slice ship models to reveal critical details such as stiffeners for inspection. Another traffic light system indicates “where you should focus inspections” across the ship’s hull although there are uncertainties such as the wave conditions these structures face in real operations.
To account for this, DNV GL created a hybrid twin. “We mix the design model and the numerical twin with sensory information,” said Mr Storhaug. “This brings much better accuracy and complete modelling of the structure” including transferring loads across the structure.
By optimising the sensor positions, shipowners can gain more detail of stress on hull structures. “One of the benefits of the hybrid twin is you can calculate where you should have the sensors,” said Mr Storhaug. In his presentation, there were eight sensor positions along the ship’s hull providing stress data.
Owners can use this information to reduce operating and compliance costs.
“You can use this for maintenance planning or inspection planning, or your due diligence to select the right candidates for conversion,” said Mr Storhaug. “It can be useful for lifetime extension and troubleshooting,” he continued. “So, there can be many purposes for these different digital twin concepts.”
Mr Storhaug was joined on the panel during the webinar by Lappeenranta University of Technology associate professor Teemu Turunen-Saaresti and MacGregor vice president for digital and business transformation Dennis Mol.
Watch the How digital twins drive vessel efficiency and voyage performance webinar in our webinar library