Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data

Autor: A Gnana Sagaya Raj, Chandra Sekhar Mishra
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Data in Brief, Vol 43, Iss , Pp 108340- (2022)
Druh dokumentu: article
ISSN: 2352-3409
DOI: 10.1016/j.dib.2022.108340
Popis: ABSTRACT: The modelling of turbulence for IC engine applications is quite a challenging task. Large Eddy Simulation (LES) is the best approach to model the turbulence as the flow is three dimensional, chaotic, transient, diffusive, dissipative and intermittent. In this paper, a Computational Fluid Dynamics (CFD) data of in-cylinder air movement on TUD (Technische universitat Darmstadt) through Reynolds Average Navier-Stokes (RANS) approach with two different turbulence model, viz. Re-Normalized Group (RNG), K-Epsilon (k-ε) and K-Omega (k-ω) turbulence models for a single-cylinder, spark-ignition engine is analyzed. A commercial code STAR-CD (Solver for turbulent flow in arbitrary regions-Computational Dynamics) which works based on finite volume method is used for numerical analysis. Qualitative and quantitative data resemblance at a particular crank angle of interest throughout the inlet and compression stroke is analysed. CFD data was compared using the experimental data conducted on a single cylinder engine using a high speed Particle Image Velocimetry (PIV) technique, which was obtained from Darmstadt Technical University. Experimental data from the published literature were difficult to obtain and hence the above data is used for comparison. The resemblance data presented here are in terms of trapped mass of air, in-cylinder pressure, fluid flow pattern into the cylinder and the spatial variation of velocity at a particular interest of location and plane on the cylinder. The data offered in this work will be useful for academic researchers attempting to undertake computational fluid dynamics studies in diesel engines.
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