Under Pressure: Digital Twins

How structural digital twins can transform the maintenance and inspection of pressure vessels.

ENGINEERING simulation software has been around for decades. It has been used ubiquitously in the design of large, complex assets and is an essential tool for engineers to develop better, more efficient products. It enjoys absolute anonymity from the untrained eye, but it’s behind every asset or piece of infrastructure in our modern world. Until recently, its application has been limited to design because the numerical method behind conventional software, finite element analysis (FEA), doesn’t have the computational speed required to simulate at the pace of operations. Thanks to US Department of Defense funded research at the mechanical engineering lab at MIT, 2012 saw a breakthrough – an accelerated version of the algorithm, reduced-basis finite element analysis (RB-FEA). RB-FEA has revolutionised simulation by allowing structural integrity assessments to be run holistically on operational assets, to support remote monitoring and near real-time assessment.

At Akselos, we’ve been working with asset integrity service company, CAN Group, and the UK Oil and Gas Technology Centre (OGTC) to apply RB-FEA to the simulation of pressure vessels to create near real-time, structural digital twins. As a result, a cross-disciplinary team has developed improved processes for managing pressure vessels by combining Akselos’ new engineering simulation techniques with robotics and non-intrusive inspection (NII) techniques. Together, these techniques are expected to deliver better operational efficiency, including a 45% reduction in downtime and a 25% reduction in maintenance and inspection costs.

Pursuit of maximum efficiency

A 2017 OGTC survey of major upstream oil and gas operators identified that adopting non-intrusive inspection technology for process pressure vessels could deliver increased production and lower maintenance costs worth up to £242m/y (US$313m/y) to the UK Continental Shelf (UKCS). The findings showed that potentially 80% of vessels could be examined non-intrusively, without requiring a shutdown. Consequently, cost savings could reach up to 80% compared to inspections that involve entry into a vessel, and crucially, improved safety with 80% fewer confined space entries required.

The research also found that the data from ultrasounds – typically used for non-intrusive inspection – were, more often than not, difficult to process and interpret. The procedure generated tens of millions of data points but lacked context and structure, rendering them meaningless.

OGTC has been proactively seeking out new ways to make non-intrusive methods the status quo, first and foremost to reduce and eliminate risks associated with intrusive inspection and to improve the overall operational efficiency of production facilities. 

When Akselos approached OGTC to test the use of a holistic simulation of the pressure vessel powerful enough to incorporate inspection data, it agreed to support what would be the industry’s first physics-based digital twin of a pressure vessel.

Identical twins: project development

Our task was to make a physics-based assessment of the ultrasonic inspection data to assess the structural integrity of the vessel.

The large high pressure vessel in question had been deployed in the North Sea and used for the separation of liquids during the production process offshore, and had a history of localised corrosion. The traditional approach for assessing the status of a pressure vessel, known as intrusive inspection, includes shutdown, isolation, and visual inspection of the vessel. This can impact profitability, as it often also requires a shutdown and isolation of the production plant too. In addition, inspecting pressure vessels involves a range of hazards including confined spaces, radioactive materials and potential exposure to toxic byproducts such as mercury and pyrophoric scale.

The traditional engineering approach of the asset operator involved a staged workflow to assess the risk on the asset presented by the inspection results based on the API 579 standard. However, this process can be time consuming where defects are detected.

Akselos collaborated with CAN Group, a UKAS 17020 Accredited Inspection body which has extensive experience working on NII data visualisation projects, to create a new, API 579 compliant workflow that could be run on operational vessels. It included semi-automated inspection data that was uploaded, mapped, and assessed within the digital twin in exact detail, to enable accurate validation of the pressure retention and structural integrity, and in turn fitness for service.

The run time workflow, which Akselos has automated, can be summarised as follows (see also the diagram below):

1. The near real-time digital twin has a mapped scan plan so the inspection can be automatically uploaded into the digital twin as soon as it has been collected.
2. The data is then mapped to ensure accuracy before being applied to the digital twin.
3. Once updated, the digital twin is processed through the API 579 Level 3 assessment against the different forms of possible deformation.
4. The results are displayed in Akselos’ software and a fitness-for-service report is automatically generated.

The high-fidelity simulation model enables a Level 3 assessment by building a digital thread from robotic inspection and data gathering, mapping that data onto the digital twin, running RB-FEA tests, and providing a pass or fail based on the API 579 threshold tests.

The workflow reduced a minimum 7-day day scope to under 3 hours, without the need to take the pressure vessel offline. Not only does this significantly reduce time, cost, and risk exposure, it allows for optimisation of the inspection frequency and eliminates the need for Level 1 and 2 assessments.

Achieving an accurate Level 3 assessment result with conventional methods is no easy task, nor is it 100% reliable. The conventional approach is to manually collect inspection data and create a model using FEA. The only way to achieve an accurate understanding of the condition of the vessel would be to create a number of sub-models of particular focus areas, or make a major compromise by creating a lower fidelity holistic model, which removes the details of pitting and other anomalies through giving an average thickness measurement over critical areas. Either way, the workflow that would produce a low fidelity model would still take at least seven days (typically weeks) and a US$30,000–50,000 bill for each assessment.

The next evolution

Thanks to OGTC’s stewardship, the project partners came together and developed a pioneering approach to pressure vessel inspection in less than a year, utilising emerging technology from both the hardware and software worlds. 

The project has shown that the use of a near real-time physics-based digital twin will:

• provide a full assessment of fitness for services within hours;
• fully automate the digital thread from the collection of the ultra-sound data to mapping onto the actual vessel BOD (injected data into the model overlaid based on the scan plan);
• automate the API 579 standards up to Level 3; and
• automate the results of fitness-for-service outputs to show areas of stress and inspection interest onto the dashboard.

In short, once the digital twin for the asset is set up, all the operator has to do following the upload of the c-scan data is press a button to get the latest status of the vessel and a corresponding fitness-for-service report.

We believe the additional benefits of selective inspections and fitness-for-service on demand with high-fidelity modelling, will increase the estimated £240m of annual savings to the UKCS from improved non-intrusive inspection and assessment.

As with most other projects led by OGTC, the beauty is that it won’t take long for the industry to follow suit, and for physics-based models to be the status quo for the maintenance and inspection of pressure vessels.