EconPapers    
Economics at your fingertips  
 

Large-Eddy Simulation of the Particle-Laden Turbulent Flow in a Cyclone Separator

Michael Alletto () and Michael Breuer ()
Additional contact information
Michael Alletto: Helmut-Schmidt-Universität Hamburg
Michael Breuer: Helmut-Schmidt-Universität Hamburg

A chapter in High Performance Computing in Science and Engineering ‘13, 2013, pp 377-391 from Springer

Abstract: Abstract A gas cyclone separator represents a classic field of application where turbulent particle-laden flows play a major role. In order to evaluate the performance of a recently developed Euler–Lagrange simulation tool based on the large-eddy simulation (LES) technique and the point-particle approach, this practically relevant flow problem is considered in the present study. As a first step towards a full simulation taking all interactions between the two phases (fluid–particle, particle–fluid and particle–particle) into account, a one-way coupled prediction is carried out. Nevertheless, the entire simulation methodology is described in detail including a sandgrain roughness model and a deterministic collision model. For the latter a performance analysis was carried out demonstrating that even for a high mass loading the computational effort for the collision detection remains below 10 % of the entire CPU-time. The predicted LES results for the cyclone flow are compared with corresponding measurements and a reasonable agreement is found.

Keywords: Vortex Core; Rough Wall; Circumferential Velocity; Cyclone Separator; Precess Vortex Core (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-02165-2_26

Ordering information: This item can be ordered from
http://www.springer.com/9783319021652

DOI: 10.1007/978-3-319-02165-2_26

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-06-26
Handle: RePEc:spr:sprchp:978-3-319-02165-2_26