Five complimentary activities:
- Test methodology
- Material characterisation
- AI-enable material modelling
- Life-cycle assessment
- Digital thread
Yielding five distinct and tangible outcomes:
- Approach to accelerated fatigue test standard
- A repository of material data under fatigue loading
- A repository of multi-scale models capable of modelling “defect-free” layups and specimens with manufacturing defects
- Demonstrating the impact of our approach through TEA and LCA
- A roadmap aligned with EMCC/EMMC to include proposed ongoing research and development prospects
Addressing their objectives
By Developing fatigue behaviour models at the micro-and meso-scale levels, and AI surrogate models at the meso-scale level, a finite-element based, validated probabilistic meso-mechanical modelling framework for the prediction of the fatigue performance of laminates and exploiting AI trained surrogate models for fatigue prediction of macro-scale structures, D-STANDART provides:
Contribution to EMMC objectives
- “to promote modelling by means of physics-based and data-driven models in industry” – EMMC White Paper
- “The goal is to strengthen the link between materials modelling and experiments by developing improved post-processing models with the necessary physics contents […]” – EMMC website
- Contribution to EMCC objectives
- “To support establishing a community of European stakeholders in the process of developing and improving characterisation tools in order to bring […] advanced materials in Europe into end products more successfully.” – EMCC website
- “[…] roadmap for characterisation techniques for engineering and upscaling of […] advanced materials in Europe. […] support the strengthening of Europe’s industrial capacity and competitiveness” – EMCC website