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PhD/post-doc on development of complex geometry reduced order models for multi-scale permeability simulation

This research focuses on the development of model order reduction methods to speed up the (repeated) multiscale prediction of permeability in composite manufacturing processes. The permeability of a composite material has a very large impact on the production process of components. It is therefore required to have an accurate knowledge and understanding of the permeability, which depends on the micro- and meso-scale geometry, in order to have a robust manufacturing process. One approach to analyze the permeability at the meso-scale (unit cell) level is through computational-fluid-dynamics techniques based on the Navier-Stokes equations. However, these simulations can be computationally demanding and, due to the inherent variability of the geometry of the microstructure for a typical material, it is practically infeasible to simulate a sufficient number of geometries in order to obtain a reliable average value of the textile permeability. To reduce this computational load into a feasible range, which will enable the use of these simulations in industry, this project aims to develop novel model order reduction techniques.

The research will focus on the following topics:

  •          Model reduction for steady-state and transient Navier-Stokes simulation
  •          Efficient spatial discretization for unit cells with complex geometries using model order reduction concepts
  •          Exploitation of parametric model order reduction methods for repeated simulations needed to capture different (in-space) distributed material configurations due to shearing and compaction
  •         Propagation of reduced order model response over multiple scales

 The project will benefit from collaboration with Siemens PLM Software (CFD software Star-CCM+). This project (MOR4MDesign, fits in the M3 R&D Program (, funded by SIM.

Applications both for a PhD (4 years) or a post-doc (3 years) positions will be considered.

A successful candidate should have the following profile:

  • Computational fluid dynamics theoretical knowledge and experience beyond simple use of commercial software
  • Theoretical knowledge and experience in application of numerical methods and programming
  • Ability to apply a CFD simulation to real life flow through porous or fibrous materials

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