Predictive Digital Twins for Asset Life Extension

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Deployed by 10 companies

Akselos’s top predictive power for digital twins

Page last modified

April 11 2024

Akselos provides a software called Akselos Integra ®, with distinctive features:

Reduced Basis Finite Element Analysis (FEA) algorithm, which allows simulation 1,000 times faster than FEA with the same accuracy.
Parameterized 3D models, where components can be reconfigured in seconds, based on different loading conditions in seconds.
Cloud-based applications to run thousands of fast simulations with little in-house IT overhead.

The combination of these features allow analysis of many “what if” scenarios, study uncertainties in a model, and perform quantitative risk assessments.

Learn how Akselos is lowering costs to make widespread offshore wind generation a reality thanks to funding from Eureka

“The Bonga Main FPSO heralded a number of innovative ‘firsts’ when it was built back in 2004, so it’s fitting that it’s the first asset of its kind to deploy something as advanced as a structural Digital Twin. We are very excited about the new capabilities that Akselos brings and believe it will create a positive impact on the way we manage structural integrity. It is also a great example of digitalisation coming to life.”

- Elohor Aiboni, Asset Manager for Bonga | Shell.

Learn more about Akselos' successful deployment for Shell's Bonga main FPSO, world's largest structural Digital Twin.

Pros & Limitations

Run fully detailed global analysis of large-scale assets, based on real-life physical scenarios, in few seconds

Practically unlimited scalability to capture exact condition of an asset by incorporating real-life inspection data in the global model (e.g. cracks, corrosion, damage, fatigue regions)

Digital Twin calibration based on sensor and inspection data to allow integrity calculations based on real loads

Identify which exact component of your asset would fail, under thousands of different scenarios

Asset Life Extension through increased modelling accuracy and consideration of actual loading regime

Consider thousands of possible in-service conditions and scenarios to produce rich, physics based, predictive data sets for Machine Learning to fill gaps in data gathered from field operations and augment Digital Twins based on big data analytics.

Support for live asset monitoring and interpretation of sensor data

Asset-based license and cloud-based hosting to allow unrestricted deployment, seamless knowledge sharing and collaboration

Integration with asset management software

Focused on Structural Integrity but based on an open environment for integration to other simulation tools

Specification

Specification Title	Specification Description
Accuracy	Highly accurate and detailed structural digital twins using new analysis technology that has been extensively validated based on peer-reviewed research and industry applications.
Areas of Application	Structural integrity of critical assets (floating and fixed offshore, hulls, topsides, subsea, downstream, Offshore Wind, etc.).
Asset life extension	Akselos allows higher fidelity modelling of geometry and loads removing conservative assumptions and extending fatigue life.
Capabilities	Static, Dynamic, Thermal and acoustic analysis. RB-FEA Solver 1000x faster than conventional structural simulation methods. Fracture Mechanics (J-Integral). Hybrid approach allows nonlinear materials, deformation and contact simulation.
Cloud platform	Cloud platform to support end-to-end process driving automated simulation, presented to all stakeholders through clear dashboards.
Compliance	Generate code checks based on relevant standards (e.g. Lloyd’s Register, DNV-GL, ABS).
Condition based maintenance	Akselos can calculate structural integrity based the real loads and real condition of an Asset which facilitated the optimisation of operations.
Digitisation	Akselos can be integrated with sensors to help interpret anomalous readings and predict structural problems before they occur.
Machine learning	Akselos can produce rich data sets of physics based data to fill gaps in operational data and enhance the predictive capabilities of digital twins based on big data analytics.
Speed	RB-FEA Solver 1000x faster than conventional structural simulation methods.