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CLC number: O643; V312.1

On-line Access: 2019-12-09

Received: 2019-08-17

Revision Accepted: 2019-10-16

Crosschecked: 2019-11-07

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Fei Qin

https://orcid.org/0000-0002-1440-1521

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Journal of Zhejiang University SCIENCE A 2019 Vol.20 No.12 P.908-917

http://doi.org/10.1631/jzus.A1900388


Development of skeletal chemical mechanisms with coupled species sensitivity analysis method


Author(s):  Rui Li, Guo-qiang He, Fei Qin, Xiang-geng Wei, Duo Zhang, Ya-jun Wang, Bing Liu

Affiliation(s):  Science and Technology on Combustion, Internal Flow and Thermal-structure Laboratory, Northwestern Polytechnical University, Xi'an 710072, China

Corresponding email(s):   qinfei@nwpu.edu.cn

Key Words:  Combustion chemical model, Skeletal reduction, Sensitivity analysis, Directed relation graph (DRG) method, Computational fluid dynamics (CFD)


Rui Li, Guo-qiang He, Fei Qin, Xiang-geng Wei, Duo Zhang, Ya-jun Wang, Bing Liu. Development of skeletal chemical mechanisms with coupled species sensitivity analysis method[J]. Journal of Zhejiang University Science A, 2019, 20(12): 908-917.

@article{title="Development of skeletal chemical mechanisms with coupled species sensitivity analysis method",
author="Rui Li, Guo-qiang He, Fei Qin, Xiang-geng Wei, Duo Zhang, Ya-jun Wang, Bing Liu",
journal="Journal of Zhejiang University Science A",
volume="20",
number="12",
pages="908-917",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1900388"
}

%0 Journal Article
%T Development of skeletal chemical mechanisms with coupled species sensitivity analysis method
%A Rui Li
%A Guo-qiang He
%A Fei Qin
%A Xiang-geng Wei
%A Duo Zhang
%A Ya-jun Wang
%A Bing Liu
%J Journal of Zhejiang University SCIENCE A
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%N 12
%P 908-917
%@ 1673-565X
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1900388

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T1 - Development of skeletal chemical mechanisms with coupled species sensitivity analysis method
A1 - Rui Li
A1 - Guo-qiang He
A1 - Fei Qin
A1 - Xiang-geng Wei
A1 - Duo Zhang
A1 - Ya-jun Wang
A1 - Bing Liu
J0 - Journal of Zhejiang University Science A
VL - 20
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SP - 908
EP - 917
%@ 1673-565X
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1900388


Abstract: 
In this paper, we propose a chemical kinetic mechanism reduction method based on coupled species sensitivity analysis (CSSA). Coupled species graph of uncertain species was calculated using the interaction coefficient in the directed relation graph (DRG) approach and listed first, whereas species having large interaction coefficients were regarded as one unit and removed in the sensitivity analysis process. The detailed mechanisms for ethylene with 111 species and 784 reactions, and for n-heptane with 561 species and 2539 reactions, under both low and high temperatures were tested using the proposed reduction method. Skeletal mechanisms were generated, comprising a 33-species mechanism for combustion of ethylene and a 79-species mechanism for n-heptane. Ignition delay times, laminar flame speeds, perfectly stirred reactor (PSR) modeling as well as species and temperature profiles, and brute-force sensitivity coefficients obtained using the skeletal mechanisms were in good agreement with those of the detailed mechanism. The results demonstrate that the CSSA reduction approach can achieve compact and accurate skeletal chemical mechanisms and is suitable for combustion modeling.

This work proposed a chemical kinetic mechanism reduction method, CSSA. With the method, a 33-species mechanism for combustion of ethylene and a 76-species for n-heptane have been achieved. Ignition delay times, laminar flame speeds, species concentration, temperature profiles and brute-force sensitivity coefficients were tested with experiments or the detailed models. According to the results, the CSSA method is better than the DRGEP method. I believe that the new method as well as the achieved chemical models will be helpful for other researchers and engineers that working in the fields of chemical kinetics and combustion CFDs.

燃烧化学动力学机理的框架简化:组分耦合的灵敏性分析简化方法

目的:发动机燃烧数值模拟需要高精度的、尺寸合适的化学反应机理,因此需要对复杂的详细化学反应机理进行简化. 由于现有的灵敏性分析简化方法效率低且计算时间长,因此本文希望得出一种效率更高、计算时间更短的灵敏性分析简化方法.
创新点:1. 利用直接关系图简化方法中的相互作用系数计算待删除组分之间的相互耦合关系,提出了组分耦合的灵敏性分析简化方法; 耦合关系较大的两个组分被视为一个整体,有助于提高灵敏性分析简化的效率、缩短计算时间. 2. 得到了较小尺寸的乙烯(33组分)和正庚烷(79组分)框架燃烧反应机理.
方法:1. 提出组分耦合的灵敏性分析简化方法,即先利用直接关系图简化方法中的相互作用系数计算待删除组分之间的相互耦合关系(公式(2)和(3),图2); 在简化过程中,耦合关系较大的两个组分被视为一个整体被删除. 2. 通过0维和一维计算验证得到的简化化学反应机理的精度.
结论:1. 本文所提出的组分耦合的灵敏性分析简化方法提高了灵敏性分析简化的效率、缩短了计算时间. 2. 利用此方法对含有111组分和784基元反应的乙烯以及561组分和2539基元反应的正庚烷的燃烧化学机理进行简化,最终得到33组分的乙烯框架机理和79组分和339基元反应的正庚烷框架反应机理. 3. 在较宽的工况范围内对得到的框架机理进行点火延时、层流火焰传播速度、温度曲线、组分浓度和反应的灵敏性分析等燃烧特性参数的验证与分析,结果表明得到的框架机理具有较高的精度和较小的尺寸,适用于燃烧数值模拟.

关键词:燃烧化学反应机理; 框架简化; 灵敏性分析; 直接关系图法; 计算流体动力学

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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