High-Performance Finite Element Methods with Application to Simulation of Diffusion MRI and Vertical Axis Wind Turbines

Time: Thu 2019-04-04 11.15 - 12.15

Lecturer: Van Dang Nguyen, CST/EECS/KTH

Location: Room 4532, Lindstedtsvägen 5, KTH, Stockholm

Abstract

The finite element methods have been developed over decades, and together with the growth of computer engineering, they are playing a more and more important role in solving scientific and industrial problems. We have developed high-performance finite element methods which allow for large-scale simulations of diffusion magnetic resonance imaging and of the turbulent flow past vertical axis wind turbines. In this talk, I will focus on the following research topics.

  1. Turbulence simulations of vertical axis wind turbines with a Direct Finite Element Simulation method [1, 5]
  2. Interface problems with a partition of unity finite element method in high-performance computing frameworks [3, 4]
  3. Diffusion simulation in thin media using manifold discretization [2]
  4. A Cloud-based simulation framework of diffusion MRI

References

[1] V.-D. Nguyen et al., Direct Finite Element Simulation of the turbulent flow past a vertical axis wind turbine, Renewable Energy, 2019.

[2] V.-D. Nguyen et al., Diffusion MRI simulation in thin-layer and thin-tube media using a discretization on manifolds, Journal of magnetic resonance, 2019.

[3] V.-D. Nguyen et al., A partition of unity finite element method for computational diffusion MRI, Journal of Computational Physics, 2018.

[4] V.-D. Nguyen et al., A fluid-structure interaction model with weak slip velocity boundary conditions on conforming internal interfaces, in 6th European Conference on Computational Mechanics (ECCM), 7th European Conference on Computational Fluid Dynamics (ECFD 7), 1115 June 2018, Glasgow, UK, 2018.

[5] V.-D. Nguyen et al., Modelling of rotating vertical axis turbines using a multiphase finite element method, in MARINE 2017: Computational Methods in Marine Engineering VII15 - 17 May 2017, Nantes, France, 2017, pp. 950-960.

Contact:

Belongs to: Computational Science and Technology
Last changed: Mar 20, 2019