Direct Numerical Simulation of Head-On Quenching of Statistically Planar Turbulent Premixed Methane-Air Flames Using a Detailed Chemical Mechanism

Direct Numerical Simulation of Head-On Quenching of Statistically Planar Turbulent Premixed Methane-Air Flames Using a Detailed Chemical Mechanism
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DOI:
10.1007/s10494-018-9907-5
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发表时间:
2018-12-01
影响因子:
2.4
通讯作者:
Chakraborty, Nilanjan
Chakraborty, Nilanjan
中科院分区:
工程技术3区
文献类型:
--
作者:
Lai, Jiawei;Klein, Markus;Chakraborty, Nilanjan

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采用三维可压缩直接数值模拟(DNS)方法研究了等温惰性壁面对统计平面化学计量比甲烷-空气火焰的迎头猝灭。甲烷-空气燃烧的多步化学机理用于详细的化学DNS的目的。对于化学计量比的甲烷-空气火焰的迎头淬熄,主要反应物物种如甲烷和氧气的质量分数在火焰淬熄期间趋于在壁面消失。在壁处没有OH引起在火焰淬火期间一氧化碳的积累,因为CO不能再被氧化。此外,它已被发现,低温反应引起的积累的HO 2和H2 O2在火焰淬火过程中的壁。此外,这些低温反应是负责非零的热释放率在壁面在火焰的相互作用。为了对简单和详细的化学DNS结果进行深入的比较,对具有代表性的单步Arrhenius型不可逆化学机制的相同湍流参数进行了相应的模拟。在相应的简单化学模拟中,一旦火焰到达离壁面的阈值距离,热释放速率就消失。对于简单的化学模拟,反应进程变量c和无量纲温度T的分布在远离壁面处是相同的,但在迎面淬火过程中,这种相等性不成立。c(基于CH 4质量分数定义)和T之间的不等式对于详细的化学模拟保持远离壁和靠近壁,但在近壁区域变得特别突出。对于简单和详细的化学层流和湍流情况,壁面热通量和壁面Peclet数(即T=0.9等值面的归一化壁面法线距离)的时间演变被发现是定性相似的。然而,小的差异已被观察到的最大归一化壁热通量的大小和最小佩克莱数(Pemin)L从简单而详细的化学层流迎面淬火计算获得的数值。对观察到的和(Pemin)L行为上的差异提供了详细的解释.通常的火焰表面密度(FSD)和标量耗散率(SDR)为基础的反应速率封闭不足以预测的平均反应速率的反应进程变量在近壁区的简单和详细的化学模拟。已经发现,最近提出的基于简单化学数据的先验DNS分析的基于FSD和SDR的反应速率闭合对于远离和靠近壁的详细化学情况也表现得令人满意,而无需对模型参数进行任何调整。
A three-dimensional compressible Direct Numerical Simulation (DNS) analysis has been carried out for head-on quenching of a statistically planar stoichiometric methane-air flame by an isothermal inert wall. A multi-step chemical mechanism for methane-air combustion is used for the purpose of detailed chemistry DNS. For head-on quenching of stoichiometric methane-air flames, the mass fractions of major reactant species such as methane and oxygen tend to vanish at the wall during flame quenching. The absence of OH at the wall gives rise to accumulation of carbon monoxide during flame quenching because CO cannot be oxidised anymore. Furthermore, it has been found that low-temperature reactions give rise to accumulation of HO2 and H2O2 at the wall during flame quenching. Moreover, these low temperature reactions are responsible for non-zero heat release rate at the wall during flame-wall interaction. In order to perform an in-depth comparison between simple and detailed chemistry DNS results, a corresponding simulation has been carried out for the same turbulence parameters for a representative single-step Arrhenius type irreversible chemical mechanism. In the corresponding simple chemistry simulation, heat release rate vanishes once the flame reaches a threshold distance from the wall. The distributions of reaction progress variable c and non-dimensional temperature T are found to be identical to each other away from the wall for the simple chemistry simulation but this equality does not hold during head-on quenching. The inequality between c (defined based on CH4 mass fraction) and T holds both away from and close to the wall for the detailed chemistry simulation but it becomes particularly prominent in the near-wall region. The temporal evolutions of wall heat flux and wall Peclet number (i.e. normalised wall-normal distance of T=0.9 isosurface) for both simple and detailed chemistry laminar and turbulent cases have been found to be qualitatively similar. However, small differences have been observed in the numerical values of the maximum normalised wall heat flux magnitude and the minimum Peclet number (Pemin)L obtained from simple and detailed chemistry based laminar head-on quenching calculations. Detailed explanations have been provided for the observed differences in behaviours of and (Pemin)L. The usual Flame Surface Density (FSD) and scalar dissipation rate (SDR) based reaction rate closures do not adequately predict the mean reaction rate of reaction progress variable in the near-wall region for both simple and detailed chemistry simulations. It has been found that recently proposed FSD and SDR based reaction rate closures based on a-priori DNS analysis of simple chemistry data perform satisfactorily also for the detailed chemistry case both away from and close to the wall without any adjustment to the model parameters.