Artificial intelligence-based fracture mechanics assessment for industrial applications
| Reference number | |
| Coordinator | Linköpings universitet - Institutionen för ekonomisk och industriell utveckling |
| Funding from Vinnova | SEK 5 508 000 |
| Project duration | September 2025 - August 2028 |
| Status | Ongoing |
| Venture | Advanced digitalization - Industrial needs-driven innovation |
| Call | Advanced digitalization - Industrial innovation 2025 |
Purpose and goal
The project aims to reform fracture mechanics assessment with artificial intelligence (AI). The potential lies in significantly reducing computational costs, improving reliability and accelerating design iterations when assessing complex components. In collaboration with the Swedish gas turbine industry, the project will use experimental data and numerical models to train the AI tool. The project leads to improved competitiveness, safety and sustainability.
Expected effects and result
The result will be AI-driven tools for everyday use and an employable PhD graduate, who contributes to the development of Swedish industry. Through dissemination and knowledge transfer, the project aims to provide engineers with innovative tools and promote collaboration between academia and industry. Ultimately, the project aims to improve the safety, reliability and efficiency of vital infrastructure and technical systems, which contributes to economic growth and technological innovation.
Planned approach and implementation
The project is being carried out as a PhD project with both mechanical testing, modelling and implementation. Development is done in stages, first 2D where training is based on elementary cases and crack growth data. Conventional models for TMF crack growth will be investigated. Extension to 3D, handling TMF loading, non-linearities, crack closure and growth. Training is based on conventional models. Comparison against conventional methods will be made for a demonstration case.