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

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 (C...

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Autores principales: Raj, A Gnana Sagaya, Mishra, Chandra Sekhar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189782/
https://www.ncbi.nlm.nih.gov/pubmed/35707243
http://dx.doi.org/10.1016/j.dib.2022.108340
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author Raj, A Gnana Sagaya
Mishra, Chandra Sekhar
author_facet Raj, A Gnana Sagaya
Mishra, Chandra Sekhar
author_sort Raj, A Gnana Sagaya
collection PubMed
description 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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spelling pubmed-91897822022-06-14 Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data Raj, A Gnana Sagaya Mishra, Chandra Sekhar Data Brief Data Article 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. Elsevier 2022-06-02 /pmc/articles/PMC9189782/ /pubmed/35707243 http://dx.doi.org/10.1016/j.dib.2022.108340 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Raj, A Gnana Sagaya
Mishra, Chandra Sekhar
Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data
title Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data
title_full Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data
title_fullStr Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data
title_full_unstemmed Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data
title_short Simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – A computational fluid dynamics cold flow data
title_sort simulation and experimental data resemblance of darmstadt spark ignition engine with different turbulence models – a computational fluid dynamics cold flow data
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189782/
https://www.ncbi.nlm.nih.gov/pubmed/35707243
http://dx.doi.org/10.1016/j.dib.2022.108340
work_keys_str_mv AT rajagnanasagaya simulationandexperimentaldataresemblanceofdarmstadtsparkignitionenginewithdifferentturbulencemodelsacomputationalfluiddynamicscoldflowdata
AT mishrachandrasekhar simulationandexperimentaldataresemblanceofdarmstadtsparkignitionenginewithdifferentturbulencemodelsacomputationalfluiddynamicscoldflowdata