A Zonal Turbulence Modeling Approach for ICE Flow Simulation

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
Turbulence modeling is a key aspect for the accurate simulation of ICE related fluid flow phenomena. RANS-based turbulence closures are still the preferred modeling framework among industrial users, mainly because they are robust, not much demanding in terms of computational resources and capable to extract ensemble-averaged information on a complete engine cycle without the need for multiple cycles simulation. On the other hand, LES-like approaches are gaining popularity in recent years due to their inherent scale-resolving nature, which allows the detailed modeling of unsteady flow features such as cycle-to-cycle variations in a DI engine. An LES requires however a large number of simulated engine cycles to extract reliable flow statistics, which coupled to the higher spatial and temporal resolution compared to RANS still poses some limits to a wider application of such methodology on realistic engine geometries. In this paper a hybrid zonal RANS/LES simulation methodology is proposed, based on a Detached Eddy Simulation (DES) technique previously developed by the authors. The aim is to preserve the turbulence scale-resolving capabilities wherever actually needed, reducing at the same time the overall computational costs compared to standard LES. The resulting zonal model has been implemented into the open-source CFD package OpenFOAMĀ® and then assessed on geometries which reproduce the typical flow conditions at cylinders' intake ports. The presented numerical solutions have been compared with the available experimental benchmarks as well as with previous computational studies from other authors.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-0584
Pages
12
Citation
Bella, G., and Krastev, V., "A Zonal Turbulence Modeling Approach for ICE Flow Simulation," SAE Int. J. Engines 9(3):1425-1436, 2016, https://doi.org/10.4271/2016-01-0584.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-0584
Content Type
Journal Article
Language
English