Numerical Investigation of Fuel Effects on Soot Emissions at Heavy-Duty Diesel Engine Conditions

Meng Tang, Y. Pei, Yu Zhang, M. Traver, David Cleary, Zhaoyu Luo, J. Naber, Seong-Young Lee
{"title":"Numerical Investigation of Fuel Effects on Soot Emissions at Heavy-Duty Diesel Engine Conditions","authors":"Meng Tang, Y. Pei, Yu Zhang, M. Traver, David Cleary, Zhaoyu Luo, J. Naber, Seong-Young Lee","doi":"10.1115/ICEF2018-9696","DOIUrl":null,"url":null,"abstract":"Gasoline compression ignition (GCI) engine technology has shown the potential to achieve high fuel efficiency with low criteria pollutant emissions. In order to guide the design and optimization of GCI combustion, it is essential to develop high-fidelity simulation tools. Building on the previous work in computational fluid dynamic (CFD) simulations of spray combustion, this work focuses on predicting the soot emissions in a constant-volume vessel representative of heavy-duty diesel engine applications for an ultra-low sulfur diesel (ULSD) and a high reactivity (Research Octane Number 60) gasoline, and comparing the soot evolution characteristics of the two fuels. Simulations were conducted using both Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) turbulence models. Extensive model validations were performed against the experimental soot emissions data for both fuels. It was found that the simulation results using the LES turbulence model agreed better with the measured ignition delays and liftoff lengths than the RANS turbulence model. In addition, two soot models were evaluated in the current study, including an empirical two-step soot formation and oxidation model, and a detailed soot model that involves poly-aromatic hydrocarbon (PAH) chemistry. Validations showed that the separation of the flame lift-off location and the soot lift-off location and the relative natural luminosity signals were better predicted by the detailed soot model combined with the LES turbulence model. Qualitative comparisons of simulated local soot concentration distributions against experimental measurements in the literature confirmed the model’s performance. CFD simulations showed that the transition of domination from soot formation to soot oxidation was fuel-dependent, and the two fuels exhibited different temporal and spatial characteristics of soot emissions. CFD simulations also confirmed the lower sooting propensity of gasoline compared to ULSD under all investigated conditions.","PeriodicalId":448421,"journal":{"name":"Volume 2: Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2: Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/ICEF2018-9696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Gasoline compression ignition (GCI) engine technology has shown the potential to achieve high fuel efficiency with low criteria pollutant emissions. In order to guide the design and optimization of GCI combustion, it is essential to develop high-fidelity simulation tools. Building on the previous work in computational fluid dynamic (CFD) simulations of spray combustion, this work focuses on predicting the soot emissions in a constant-volume vessel representative of heavy-duty diesel engine applications for an ultra-low sulfur diesel (ULSD) and a high reactivity (Research Octane Number 60) gasoline, and comparing the soot evolution characteristics of the two fuels. Simulations were conducted using both Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) turbulence models. Extensive model validations were performed against the experimental soot emissions data for both fuels. It was found that the simulation results using the LES turbulence model agreed better with the measured ignition delays and liftoff lengths than the RANS turbulence model. In addition, two soot models were evaluated in the current study, including an empirical two-step soot formation and oxidation model, and a detailed soot model that involves poly-aromatic hydrocarbon (PAH) chemistry. Validations showed that the separation of the flame lift-off location and the soot lift-off location and the relative natural luminosity signals were better predicted by the detailed soot model combined with the LES turbulence model. Qualitative comparisons of simulated local soot concentration distributions against experimental measurements in the literature confirmed the model’s performance. CFD simulations showed that the transition of domination from soot formation to soot oxidation was fuel-dependent, and the two fuels exhibited different temporal and spatial characteristics of soot emissions. CFD simulations also confirmed the lower sooting propensity of gasoline compared to ULSD under all investigated conditions.
重型柴油机工况下燃油对烟尘排放影响的数值研究
汽油压缩点火(GCI)发动机技术已经显示出实现低标准污染物排放的高燃油效率的潜力。为了指导GCI燃烧的设计和优化,开发高保真度的仿真工具至关重要。本研究在计算流体动力学(CFD)模拟喷雾燃烧的基础上,重点预测了超低硫柴油(ULSD)和高反应性汽油(研究辛烷值60)在重型柴油机应用中具有代表性的定容容器内的烟尘排放,并比较了两种燃料的烟尘演化特征。采用雷诺平均纳维-斯托克斯(RANS)和大涡模拟(LES)湍流模型进行了模拟。针对两种燃料的实验烟尘排放数据进行了广泛的模型验证。结果表明,与RANS湍流模型相比,LES湍流模型的仿真结果与实测的点火延迟和起飞长度更吻合。此外,本研究还评估了两种烟尘模型,包括经验两步烟尘形成和氧化模型,以及涉及多芳烃(PAH)化学的详细烟尘模型。验证表明,结合LES湍流模型的精细烟尘模型能较好地预测火焰起飞位置与烟尘起飞位置的分离以及相对自然亮度信号。对模拟的局部烟尘浓度分布与文献中实验测量值的定性比较证实了该模型的性能。CFD模拟结果表明,从烟尘形成到烟尘氧化的主导转变依赖于燃料,两种燃料的烟尘排放表现出不同的时空特征。CFD模拟也证实,在所有测试条件下,与ULSD相比,汽油的煤烟倾向更低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信