DNV’s Emergency Response Service (ERS™) has launched a new drift prediction feature to mitigate risk with disabled and drifting vessels, and to predict the path of oil spills and floating objects, including man overboard and containers.
An incident onboard a vessel can result in a disabled ship, oil spill, floating cargo or persons drifting in the water to create an unpredictable situation with safety and environmental risk that complicates emergency response. Shipping companies need to be able to determine the drift paths of floating assets, objects or spilled chemicals at an early stage after an incident so these can be plotted on their own navigational charts to plan a prompt and efficient response when time is of the essence. In many cases, efficient handling of such incidents is significantly increased by having access to a prediction of the associated drift path.
“The drift prediction feature is a powerful addition to the toolbox of data-enhanced services within ERS™ supporting a fast and effective emergency response demonstrated across 741 maritime incidents over the past three decades,” says DNV’s ERS™ Principal Engineer Rossen Panev.
Assisting SAR operations
For vessels drifting in the ocean, a drift prediction is vital to identify immediate risks and criticality. For search-and-rescue (SAR) operations, drift predictions are used to narrow down the SAR area, which increases the probability of a successful operation. Handling of oil spills is dependent on a prediction of both the drift path and the behaviour of the oil spill, which is highly dependent on the type of oil spilled.
The ERS™ drift prediction service employs state-of-the art computer modelling based on the open-source software package OpenDrift. This enables the ERS™ Duty Team to perform the necessary simulations and generate a predicted drift path considering local environmental conditions.
Drift simulations are executed through a web-based service developed and hosted by MET Norway (the Norwegian Meteorological Institute) that combines forecasts for current, wind and wave conditions from local and global sources to provide accurate trajectory modelling. This allows fast generation of predicted drift trajectory data over a long period of time that gives stakeholders sufficient time to plan, react and mitigate, in contrast to slower and less accurate manual prediction methods that can delay decision-making.
Advanced digital modelling
Celebrating its 30th anniversary this year, ERS™ already uses advanced 3D digital modelling for residual buoyancy, damage stability and strength calculations after an incident, having generated more than 15,500 such computer ship models to date.
As part of the development of the drift prediction service, DNV has developed a numerical model to calculate drift velocities for disabled vessels in different sea conditions and generate an approximate drift trajectory to evaluate navigational hazards along the predicted path.
Similarly, the service provides oil spill drift simulation as well as an ‘oil budget report’ that estimates the volume of oil that is dispersed, evaporated or still on the surface over the simulated period. The software also can generate drift path predictions for objects in the water such as life rafts and persons in the water to define the area for search-and-rescue operations, as well as lost containers, smaller vessels and EPIRBs.
“We may not be able to tame the sea, but precise data modelling now gives us predictability to counteract uncontrolled drift and greatly improve emergency response,” said Panev.