Direct numerical simulation of a disintegrating liquid rivulet at a trailing edge

Adrian Schlottke (), Matthias Ibach, Jonas Steigerwald and Bernhard Weigand
Additional contact information
Adrian Schlottke: University of Stuttgart, Institute of Aerospace Thermodynamics (ITLR)

A chapter in High Performance Computing in Science and Engineering '21, 2023, pp 239-257 from Springer

Abstract: Abstract Water ingestion in gas turbines is used in industrial applications to improve the thermal efficiency by cooling the air before and throughout compression. However, this also leads to interactions between the liquid droplets and the compressor parts, which cause a faster degradation of the structure. The current work addresses the numerical investigation of the atomization process at the trailing edge of a compressor blade as there have only been experimental investigations in literature considering the ambient conditions in a gas turbine compressor. Direct numerical simulations (DNS) are carried out using the multiphase flow solver Free Surface 3D (FS3D). Therefore, a numerical setup has been developed to model the trailing edge as a thin plate corresponding to experiments performed at ITLR [22]. Four different cases have been performed to take the experimentally observed atomization processes into account. Additionally, the dependence of the simulation results on the grid resolution and with it the limits to reproduce the experimental findings has been investigated in a grid study. The results show that the developed numerical setup works well and the different atomization processes are reproduced qualitatively, with best results for very high grid resolutions. Furthermore, an investigation of the available compilers on the new Hawk supercomputer platform reveals that a performance gain up to 36% for the amount of completed calculation cycles per hour is possible compared to the standard compiler setup used as standard practice over the previous years. Optimization options as well as improvement during link time lead to a significant speed-up while simulation results remain unaffected.

Date: 2023
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:978-3-031-17937-2_14

Ordering information: This item can be ordered from
http://www.springer.com/9783031179372

DOI: 10.1007/978-3-031-17937-2_14

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 ().