Coarse-Grained Models for Gas-Particle Flow: Dos and Don'ts

Radl, S. (Speaker)

Activity: Talk or presentationInvited talk at conference or symposiumScience to science

Description

Nowadays, Euler-Lagrange (EL) simulations of gas-particle flows with several million particles that are directly tracked are performed routinely. However, to observe industrial-scale processes involving billions (if not significantly more!) particles, some kind of coarse-graining (CG) is necessary. A coarse-graining approach effectively reduces the number of computational entities (i.e., “parcels”) that need to be tracked: CG may enable existing EL-based simulators to make predictions of wider industrial relevance with high confidence. The challenge associated with CG models is that they require deeper thoughts on how parcel-fluid and parcel-parcel interaction should be calculated. This is especially true for cohesive powders.

The first focus of my presentation is on summarizing advances in the past ten years in the field of CG models, and highlighting major shortcomings associated with them (i.e., the “Don’ts”). The second part is dedicated to the presentation of the most successful avenues to perform coarse graining, i.e., the “Dos”. This part will also include a new theory that allows the rational selection of parameters to be used in CG-based simulations. Specifically, this theory can increase the calculation speed by a factor of 30 - when accepting a minimal loss of predictive power - when applied to systems with different inter-particle potentials (i.e., cohesionless, as well as cohesive systems that are affected by liquid bridges or van der Waals forces).

I will close with a perspective on future needs to develop CG models, with an emphasis on (i) so-called “fluid coarsened” or “filtered” models, (ii) faster integration algorithms for CG-EL simulators, and (iii) multi-physics applications.
Period14 Mar 2019 - 15 Mar 2019
Held atCFDEM Conference 2019
Event typeConference
LocationLinz, Austria
Degree of RecognitionInternational

Keywords

  • computational fluid dynamics
  • particle
  • simulation
  • Information, Communication & Computing