Statistical and machine learning approaches for the characterisation of soils
  This Fellowship application aims to develop DEM simulation approaches to enable the large-scale simulation of industrial and engineering applications effectively, realistically and reliably. This will be done using physically based models for contact laws and particle shapes that are experimentally validated. Furthermore, statistical and machine learning approaches will be used to provide new calibration procedures and method that will further speed up the implementation, development and analysis of DEM simulations. This brings significant benefits to many industry/academy stakeholder and also increases the competitiveness of many sectors including pharmaceutics, mineral processing, ceramics and material handling, amongst others (in addition to direct benefits to geotechnical engineering where factors of safety used for routine design may be reduce with important cost reduction in construction projects.

  • Start Date:

    1 September 2023

  • End Date:

    31 August 2024

  • Activity Type:

    Externally Funded Research

  • Funder:

    Royal Academy of Engineering

  • Value:


Project Team