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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
Atomization and Sprays
Article . 2024 . Peer-reviewed
Data sources: Crossref
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
Atomization and Sprays
Article . 2024 . Peer-reviewed
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COMPUTATIONAL STUDY OF HIGH-PRESSURE LIQUID INJECTION PROCESS BY MEANS OF LES AND PANS APPROACHES

Authors: Stipic, Marija; Basara, Branislav; Schmidt, Steffen; Adams, Nikolaus;

COMPUTATIONAL STUDY OF HIGH-PRESSURE LIQUID INJECTION PROCESS BY MEANS OF LES AND PANS APPROACHES

Abstract

For internal combustion engine, the determination of combustion characteristics and subsequent emissions formation relies heavily on the fuel injection process. With the increasing demand for enhanced fuel efficiency and reduced emissions, it becomes vital to develop fundamental understanding of physical process involved in the fuel injection process. In this study, an optimal numerical approach to predict high pressure liquid injection process in the context of industrial computations has been investigated. In particular, this study focuses on the respective performance of the Partially-Averaged Navier-Stokes and Large Eddy Simulation models to predict turbulent igniting sprays. Both approaches are coupled with widely used Lagrangian Discrete Droplet Method for spray modelling. The results are validated against well established ECN Spray A case in reactive and non reactive conditions. For reacting conditions, Flamelet Genrated Manifold (FGM) combustion model is employed in the present work. Comparative study and validation against experimental data showed that PANS turbulence model allows for coarser grids while still maintaining accurate results.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average