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不同湍流模型下达姆施塔特火花点火发动机的模拟与实验数据相似性——计算流体动力学冷流数据

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

作者信息

Raj A Gnana Sagaya, Mishra Chandra Sekhar

机构信息

Department of Mechanical Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, India.

出版信息

Data Brief. 2022 Jun 2;43:108340. doi: 10.1016/j.dib.2022.108340. eCollection 2022 Aug.

DOI:10.1016/j.dib.2022.108340
PMID:35707243
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9189782/
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 (-ε) and K-Omega (-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.

摘要

对内燃机应用中的湍流进行建模是一项极具挑战性的任务。大涡模拟(LES)是对湍流进行建模的最佳方法,因为流动是三维的、混沌的、瞬态的、扩散的、耗散的和间歇性的。本文分析了通过雷诺平均纳维-斯托克斯(RANS)方法,采用两种不同湍流模型,即重整化群(RNG)、K-ε和K-ω湍流模型,对单缸火花点火发动机在达姆施塔特工业大学(TUD)气缸内空气运动的计算流体动力学(CFD)数据。使用基于有限体积法工作的商业代码STAR-CD(任意区域湍流流动求解器-计算动力学)进行数值分析。分析了在整个进气和压缩冲程中特定感兴趣曲柄角处的定性和定量数据相似性。使用从达姆施塔特工业大学获得的高速粒子图像测速(PIV)技术,将CFD数据与在单缸发动机上进行的实验数据进行比较。已发表文献中的实验数据难以获取,因此使用上述数据进行比较。这里给出的相似性数据涉及空气的捕获质量、气缸内压力、进入气缸的流体流动模式以及在气缸上特定感兴趣位置和平面处速度的空间变化。这项工作中提供的数据将对试图进行柴油机计算流体动力学研究的学术研究人员有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/51a0be4127bd/gr12.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/9ce180b78760/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/6f779f037e31/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/63e75768a667/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/fc0b6f24f15e/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/9ab8e721f94c/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/532cb8ace1b3/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/7e0e27dee358/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/8cb19cd0fc4e/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/d5d3c8553815/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/51a0be4127bd/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/643e5b919def/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/bd85721d7d3f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/9ce180b78760/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/6f779f037e31/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/63e75768a667/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/fc0b6f24f15e/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/9ab8e721f94c/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/532cb8ace1b3/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/7e0e27dee358/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/8cb19cd0fc4e/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/d5d3c8553815/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f4d/9189782/51a0be4127bd/gr12.jpg

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