jump to content
Filter By
Any
  • Any
  • Knowledge Transfer
  • Materials
  • Modelling
  • Sensors and Devices
  • STEM
Clear filter x
  • Image :NRN046 - Going lighter

    NRN046 - Going lighter

    • Materials

    Our research has targeted a new class of multicomponent alloys known for their combination of lightweight and strength: high-entropy alloys based on first raw metals.

    Read More
  • Image :NRN091 - Advancing the Techniques of Non-Standard Computed Tomography for Complex Material Analysis

    NRN091 - Advancing the Techniques of Non-Standard Computed Tomography for Complex Material Analysis

    • Materials

    The aim of this research is to bring the non-standard tomographic inspection techniques of tomosynthesis and laminography up to a standard where they can be applied to the industrial non-destructive testing (NDT) of multi-material and complex geometry components.

    Read More
  • Image :NRNC20 - Future Balancing Services for High Levels of Embedded  Electricity Generation

    NRNC20 - Future Balancing Services for High Levels of Embedded Electricity Generation

    • Sensors and Devices, 
    • Modelling, 
    • Knowledge Transfer, 
    • Materials

    The aim of this research is to develop 2020 to 2035 demand scenarios for extreme conditions considering low summer transmission demand and a significant increase of solar generation connected at the distribution level.

    Read More
  • Image :NRNC05 - Detection of closed cracks in  highly attenuative materials

    NRNC05 - Detection of closed cracks in highly attenuative materials

    • Materials

    Detection of Closed Cracks in Highly Attenuative Materials

    Read More
  • Image :NRNC25 - Data-drive multidisciplinary design optimization of aircraft structures (MOAD) under uncertainty

    NRNC25 - Data-drive multidisciplinary design optimization of aircraft structures (MOAD) under uncertainty

    • Sensors and Devices, 
    • Modelling, 
    • Knowledge Transfer, 
    • Materials

    The main aim of the NRN industrial fellowship with Airbus is to build a data-driven computational framework (MOAD) for robust design and optimization of aircraft (a/c) structures in a multidisciplinary framework.

    Read More