Systematic analysis and reduction of combustion mechanisms for ignition of multi-component kerosene surrogate

Wang, Quan‐De; Fang, Ya-Mei; Wang, Fan; Li, Xiangyuan

doi:10.1016/j.proci.2012.06.011

Cited by 36 publications

(35 citation statements)

References 38 publications

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“…To check the chemical kinetics of the skeletal mechanism, the global reaction path analysis by employing the element flux analysis method is used, which is only briefly outlined. Generally, the element flux for an element (such as C) from species k 1 to k 2 at instantaneous time t is calculated via

E_{k_{1} \to k_{2}} ((), t) = \sum_{i = 1}^{I} \frac{ω_{i} N_{E, k_{1}} N_{E, k_{2}}}{N_{E, i}},

where

N_{E, k_{1}}

N_{E, k_{2}}

, and N E , i are the number of atom E in species k 1 , species k 2 , and reaction i , respectively. The global element flux during ignition simulations can be derived via time‐integrated method as

E_{int, k_{1} \to k_{2}} = \int_{0}^{τ} E_{k_{1} \to k_{2}} ((), t) italicdt .

Subsequently, the normalized weight of element flux from k 1 to k 2 to the total out flux of species k 1 can be easily derived as

E_{rel, k_{1} \to k_{2}} = \frac{E_{int, k_{1} \to k_{2}}}{\sum_{k}^{K} E_{int, k_{1} \to k}} = \frac{\int_{0}^{τ} E_{k_{1} \to k_{2}} ((), t) italicdt}{\sum_{k}^{K} \int_{0}^{τ} E_{k 1 \to k} ((), t) italicdt} .

…”

Section: Computational Methodologymentioning

confidence: 99%

“…Brute‐force sensitivity analysis and the CEMA are employed to identify dominant ignition chemistry. The percent sensitivity coefficient is defined by the following formulation:

Sensitivity = \frac{τ_{ign} ((), 2 k_{i}) - τ_{ign} ((), k_{i})}{τ_{ign} ((), k_{i})},

where k i is the rate of reaction i , τ ign (2 k i ) is the ignition delay when the rate of reaction i has been doubled, and τ ign ( k i ) is the nominal value of the ignition delay. Thus, a positive value for sensitivity means that the ignition delay becomes longer when the rate of reaction i is doubled and the reaction reactivity is inhibited.…”

Section: Computational Methodologymentioning

confidence: 99%

“…Based on the above considerations, this work intends to obtain a skeletal mechanism suitable for methanol combustion over a wide range of combustion relevant conditions. The skeletal mechanism should also maintain the combustion chemistry of methanol and is checked via a global reaction path analysis . The ignition dynamics for methanol combustion are analyzed by chemical explosive mode analysis (CEMA) .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Skeletal chemical kinetic mechanism generation for methanol combustion and systematic analysis on the ignition characteristics

Liang

Jia

Sun

et al. 2020

Asia-Pacific J Chem Eng

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A skeletal chemical kinetic mechanism for methanol combustion is developed based on a comprehensive detailed mechanism (AramcoMech 3.0), which consists of 581 species and 3,037 reactions. The systematic skeletal mechanism reduction methods are applied to the detailed mechanism to obtain a minimal skeletal mechanism. Systematic mechanism analysis including global reaction path and sensitivity analysis are performed to identify key reactions relevant to methanol oxidation. Species relevant to the combustion chemistry of methanol are analyzed through global reaction path and compared with other reduced mechanisms, which highlights the importance of maintaining realistic chemistry in skeletal mechanism. Brute-force sensitivity analysis and chemical explosive mode analysis are employed to analyze the ignition properties of methanol. The performance of the skeletal mechanism is validated against a wide range of pressures, temperatures, and equivalence ratios for ignition, species concentrations, and laminar flame speeds. This work not only presents a minimal skeletal mechanism for methanol combustion based on systematic mechanism reduction methods from very large detailed mechanisms but also provides insight into the chemical kinetics of methanol combustion. K E Y W O R D Scombustion kinetics, ignition, methanol, skeletal mechanism

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E_{k_{1} \to k_{2}} ((), t) = \sum_{i = 1}^{I} \frac{ω_{i} N_{E, k_{1}} N_{E, k_{2}}}{N_{E, i}},

where

N_{E, k_{1}}

N_{E, k_{2}}

, and N E , i are the number of atom E in species k 1 , species k 2 , and reaction i , respectively. The global element flux during ignition simulations can be derived via time‐integrated method as

E_{int, k_{1} \to k_{2}} = \int_{0}^{τ} E_{k_{1} \to k_{2}} ((), t) italicdt .

Subsequently, the normalized weight of element flux from k 1 to k 2 to the total out flux of species k 1 can be easily derived as

E_{rel, k_{1} \to k_{2}} = \frac{E_{int, k_{1} \to k_{2}}}{\sum_{k}^{K} E_{int, k_{1} \to k}} = \frac{\int_{0}^{τ} E_{k_{1} \to k_{2}} ((), t) italicdt}{\sum_{k}^{K} \int_{0}^{τ} E_{k 1 \to k} ((), t) italicdt} .

…”

Section: Computational Methodologymentioning

confidence: 99%

“…Brute‐force sensitivity analysis and the CEMA are employed to identify dominant ignition chemistry. The percent sensitivity coefficient is defined by the following formulation:

Sensitivity = \frac{τ_{ign} ((), 2 k_{i}) - τ_{ign} ((), k_{i})}{τ_{ign} ((), k_{i})},

Section: Computational Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Skeletal chemical kinetic mechanism generation for methanol combustion and systematic analysis on the ignition characteristics

Liang

Jia

Sun

et al. 2020

Asia-Pacific J Chem Eng

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show abstract

“…This 22-species mechanism predicts accurately laminar burning velocities, major product species, extinction rates and some radicals, but fails to predict ignition times and C 2 species, obtaining however impressive speed-up in computational time. Other recent attempts to provide reduced mechanisms for kerosene surrogates using the fuel from [11] and a 34-species reduced mechanism through a combination of sensitivity analysis, flux analysis, QSSA and CEMA can be found in [37], while only recently [38], a slightly modified surrogate based on n-decane was accompanied by a 59-species reduced mechanism after DRGEP [39], PCA, path flux analysis and an optimisation procedure [40] and was finally tested in a PSR. DRGEP with an additional sensitivity analysis were also used in [41] to reduce a detailed mechanism [42] for n-decane from 2115 species to a high temperature 51 species mechanism, which reproduced accurately the ignition times, while laminar flame speeds and PSR results exhibited a small error.…”

Section: Reduced Mechanismsmentioning

confidence: 99%

Reduction of a detailed chemical mechanism for a kerosene surrogate via RCCE-CSP

Koniavitis

Rigopoulos

Jones

2018

Combustion and Flame

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“…Therefore, it should be useful to generate a reasonable downsized mechanism. Many research groups have performed reduction of detailed mechanism and proposed the simplified versions (Nagy and Turanyi, 2009;Luo et al, 2012;Lu and Law, 2008;An et al, 2014;Wang et al, 2013). However, the number of simplified mechanisms for the coal flame is very limited due to that the wide range of equivalence ratio and the wide variation of volatiles composition generally appear in the coal flame and it is difficult to distinguish the important chemical species and reactions in the huge reaction system.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of reaction kinetics of coal volatiles with a detailed chemistry and its simplification

Ahn

Watanabe

Shoji

et al. 2016

JTST

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Reaction kinetics of coal volatile were numerically investigated based on analyses during reaction mechanism reduction procedure in detail in this paper. Computation on a closed homogeneous reactor model was performed to clarify important chemical species and their reaction pathways with evaluating the capability of prediction of ignition delay time and chemical species concentration under a wide range of equivalence ratios and temperatures. The kinetics of large hydrocarbons such as polycyclic aromatic hydrocarbons (PAH) that comprise a large portion of combustion features for complex hydrocarbon materials was focused on in a coal flame. The data computed here was analyzed through the combined process of the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) and the computational singular perturbation (CSP) that can evaluate the roles of each species and reaction pathway respectively in the chemical system. Results show that hydrocarbons such as aromatics, methyl and ethyl groups play important role in the ignition and flame propagation processes. Finally, the skeletal mechanism including 64 species and 150 reactions was derived from the detailed mechanism that consists of 257 species and 1107 reactions within 30% error in the prediction of the ignition delay time and the mole fractions of major species in the propagating flame.

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Systematic analysis and reduction of combustion mechanisms for ignition of multi-component kerosene surrogate

Cited by 36 publications

References 38 publications

Skeletal chemical kinetic mechanism generation for methanol combustion and systematic analysis on the ignition characteristics

Skeletal chemical kinetic mechanism generation for methanol combustion and systematic analysis on the ignition characteristics

Reduction of a detailed chemical mechanism for a kerosene surrogate via RCCE-CSP

Numerical investigation of reaction kinetics of coal volatiles with a detailed chemistry and its simplification

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