• See how continual remote monitoring of large assets can be achieved with Akselos Digital Twin simulation.
  • How to bridge the gap between data from sensors on mega assets and actionable insight for operations.
  • How digital twins help identify integrity hotspots for data-driven predictive maintenance and fitness for service assessments.
  • How Akselos technology scales up and accelerates Finite Element Analysis (FEA) using a new mathematical approach called Reduced-Basis Finite Element Analysis (RB-FEA).
  • Discover the Akselos Digital Twin generation workflow.
  • See how parameterized component-based workflow can help operators.
  • Learn about the unique attributes of Akselos’ Digital Twins.


Various sensors increasingly monitor large, complex and critical assets. There is an increasing drive to use the resulting data to obtain operational benefits such as risk-based inspection, predictive maintenance and life extension. However, in many cases, it is found that more than the data is needed to predict asset integrity and fitness for service. A physics-based framework is required to bridge the gap between the sensor data or other sources (e.g. reports) and their operational benefits. However, conventional simulation technology is not fast enough to keep pace with the data.

Akselos is a new simulation technology that can evaluate structural behaviour 1000x faster than traditional techniques. Akselos can produce high-fidelity, physics-based models of large complex assets, which may be connected to sensor data to regularly update the simulation model and provide the required assessments promptly. Such simulation models are termed Structural Digital Twins and provide a continual picture of structural integrity that can be used to optimise operations and maximise life. This webinar will show how Akselos may be used to create high-fidelity simulation models of large and complex assets that reflect the current loading and condition to provide a continual picture of integrity.

Read about our Simlab series.