Alignment with EMMC/EMCC

Priority to align with EMMC and EMCC objectives

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